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1

The importance of covariance in nuclear data uncertainty propagation studies  

SciTech Connect (OSTI)

A study has been undertaken to investigate what proportion of the uncertainty propagated through plutonium critical assembly calculations is due to the covariances between the fission cross section in different neutron energy groups. The uncertainties on k{sub eff} calculated show that the presence of covariances between the cross section in different neutron energy groups accounts for approximately 27-37% of the propagated uncertainty due to the plutonium fission cross section. This study also confirmed the validity of employing the sandwich equation, with associated sensitivity and covariance data, instead of a Monte Carlo sampling approach to calculating uncertainties for linearly varying systems. (authors)

Benstead, J. [AWE Plc, Aldermaston, Berkshire (United Kingdom)

2012-07-01T23:59:59.000Z

2

MONTE-CARLO BURNUP CALCULATION UNCERTAINTY QUANTIFICATION AND PROPAGATION DETERMINATION  

SciTech Connect (OSTI)

MONTEBURNS is a Monte-Carlo depletion routine utilizing MCNP and ORIGEN 2.2. Uncertainties exist in the MCNP transport calculation, but this information is not passed to the depletion calculation in ORIGEN or saved. To quantify this transport uncertainty and determine how it propagates between burnup steps, a statistical analysis of a multiple repeated depletion runs is performed. The reactor model chosen is the Oak Ridge Research Reactor (ORR) in a single assembly, infinite lattice configuration. This model was burned for a 25.5 day cycle broken down into three steps. The output isotopics as well as effective multiplication factor (k-effective) were tabulated and histograms were created at each burnup step using the Scott Method to determine the bin width. It was expected that the gram quantities and k-effective histograms would produce normally distributed results since they were produced from a Monte-Carlo routine, but some of results do not. The standard deviation at each burnup step was consistent between fission product isotopes as expected, while the uranium isotopes created some unique results. The variation in the quantity of uranium was small enough that, from the reaction rate MCNP tally, round off error occurred producing a set of repeated results with slight variation. Statistical analyses were performed using the {chi}{sup 2} test against a normal distribution for several isotopes and the k-effective results. While the isotopes failed to reject the null hypothesis of being normally distributed, the {chi}{sup 2} statistic grew through the steps in the k-effective test. The null hypothesis was rejected in the later steps. These results suggest, for a high accuracy solution, MCNP cell material quantities less than 100 grams and greater kcode parameters are needed to minimize uncertainty propagation and minimize round off effects.

Nichols, T.; Sternat, M.; Charlton, W.

2011-05-08T23:59:59.000Z

3

E-Print Network 3.0 - analytical uncertainty propagation Sample...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

and Information Sciences 2 CE 473573 Groundwater Introduction to uncertainty analysis and error propagation Summary: CE 473573 Groundwater Fall 2011 Introduction to...

4

Total Measurement Uncertainty for the Plutonium Finishing Plant (PFP) Segmented Gamma Scan Assay System  

SciTech Connect (OSTI)

This report presents the results of an evaluation of the Total Measurement Uncertainty (TMU) for the Canberra manufactured Segmented Gamma Scanner Assay System (SGSAS) as employed at the Hanford Plutonium Finishing Plant (PFP). In this document, TMU embodies the combined uncertainties due to all of the individual random and systematic sources of measurement uncertainty. It includes uncertainties arising from corrections and factors applied to the analysis of transuranic waste to compensate for inhomogeneities and interferences from the waste matrix and radioactive components. These include uncertainty components for any assumptions contained in the calibration of the system or computation of the data. Uncertainties are propagated at 1 sigma. The final total measurement uncertainty value is reported at the 95% confidence level. The SGSAS is a gamma assay system that is used to assay plutonium and uranium waste. The SGSAS system can be used in a stand-alone mode to perform the NDA characterization of a container, particularly for low to medium density (0-2.5 g/cc) container matrices. The SGSAS system provides a full gamma characterization of the container content. This document is an edited version of the Rocky Flats TMU Report for the Can Scan Segment Gamma Scanners, which are in use for the plutonium residues projects at the Rocky Flats plant. The can scan segmented gamma scanners at Rocky Flats are the same design as the PFP SGSAS system and use the same software (with the exception of the plutonium isotopics software). Therefore, all performance characteristics are expected to be similar. Modifications in this document reflect minor differences in the system configuration, container packaging, calibration technique, etc. These results are supported by the Quality Assurance Objective (QAO) counts, safeguards test data, calibration data, etc. for the PFP SGSAS system. Other parts of the TMU analysis utilize various modeling techniques such as Monte Carlo N-Particle (MCNP) and In Situ Object Counting Software (ISOCS).

WESTSIK, G.A.

2001-06-06T23:59:59.000Z

5

A Multi-Model Approach for Uncertainty Propagation and Model Calibration in CFD Applications  

E-Print Network [OSTI]

Proper quantification and propagation of uncertainties in computational simulations are of critical importance. This issue is especially challenging for CFD applications. A particular obstacle for uncertainty quantifications in CFD problems is the large model discrepancies associated with the CFD models used for uncertainty propagation. Neglecting or improperly representing the model discrepancies leads to inaccurate and distorted uncertainty distribution for the Quantities of Interest. High-fidelity models, being accurate yet expensive, can accommodate only a small ensemble of simulations and thus lead to large interpolation errors and/or sampling errors; low-fidelity models can propagate a large ensemble, but can introduce large modeling errors. In this work, we propose a multi-model strategy to account for the influences of model discrepancies in uncertainty propagation and to reduce their impact on the predictions. Specifically, we take advantage of CFD models of multiple fidelities to estimate the model ...

Wang, Jian-xun; Xiao, Heng

2015-01-01T23:59:59.000Z

6

Uncertainty of forest carbon stock changes – implications to the total uncertainty of GHG inventory of Finland  

Science Journals Connector (OSTI)

Uncertainty analysis facilitates identification of the most important categories affecting greenhouse gas (GHG) inventory uncertainty and helps in prioritisation of ... . This paper presents an uncertainty analys...

S. Monni; M. Peltoniemi; T. Palosuo; A. Lehtonen; R. Mäkipää…

2007-04-01T23:59:59.000Z

7

UNCERTAINTIES IN ATOMIC DATA AND THEIR PROPAGATION THROUGH SPECTRAL MODELS. I  

SciTech Connect (OSTI)

We present a method for computing uncertainties in spectral models, i.e., level populations, line emissivities, and emission line ratios, based upon the propagation of uncertainties originating from atomic data. We provide analytic expressions, in the form of linear sets of algebraic equations, for the coupled uncertainties among all levels. These equations can be solved efficiently for any set of physical conditions and uncertainties in the atomic data. We illustrate our method applied to spectral models of O III and Fe II and discuss the impact of the uncertainties on atomic systems under different physical conditions. As to intrinsic uncertainties in theoretical atomic data, we propose that these uncertainties can be estimated from the dispersion in the results from various independent calculations. This technique provides excellent results for the uncertainties in A-values of forbidden transitions in [Fe II].

Bautista, M. A.; Fivet, V. [Department of Physics, Western Michigan University, Kalamazoo, MI 49008 (United States); Quinet, P. [Astrophysique et Spectroscopie, Universite de Mons-UMONS, B-7000 Mons (Belgium); Dunn, J. [Physical Science Department, Georgia Perimeter College, Dunwoody, GA 30338 (United States); Gull, T. R. [Code 667, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Kallman, T. R. [Code 662, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Mendoza, C., E-mail: manuel.bautista@wmich.edu [Centro de Fisica, Instituto Venezolano de Investigaciones Cientificas (IVIC), P.O. Box 20632, Caracas 1020A (Venezuela, Bolivarian Republic of)

2013-06-10T23:59:59.000Z

8

Propagation of uncertainties in the nuclear DFT models  

E-Print Network [OSTI]

Parameters of the nuclear density functional theory (DFT) models are usually adjusted to experimental data. As a result they carry certain theoretical error, which, as a consequence, carries out to the predicted quantities. In this work we address the propagation of theoretical error, within the nuclear DFT models, from the model parameters to the predicted observables. In particularly, the focus is set on the Skyrme energy density functional models.

Markus Kortelainen

2014-09-04T23:59:59.000Z

9

Thermal hydraulic limits analysis using statistical propagation of parametric uncertainties  

SciTech Connect (OSTI)

The MIT Research Reactor (MITR) is evaluating the conversion from highly enriched uranium (HEU) to low enrichment uranium (LEU) fuel. In addition to the fuel element re-design, a reactor power upgraded from 6 MW to 7 MW is proposed in order to maintain the same reactor performance of the HEU core. Previous approach in analyzing the impact of engineering uncertainties on thermal hydraulic limits via the use of engineering hot channel factors (EHCFs) was unable to explicitly quantify the uncertainty and confidence level in reactor parameters. The objective of this study is to develop a methodology for MITR thermal hydraulic limits analysis by statistically combining engineering uncertainties with an aim to eliminate unnecessary conservatism inherent in traditional analyses. This method was employed to analyze the Limiting Safety System Settings (LSSS) for the MITR, which is the avoidance of the onset of nucleate boiling (ONB). Key parameters, such as coolant channel tolerances and heat transfer coefficients, were considered as normal distributions using Oracle Crystal Ball to calculate ONB. The LSSS power is determined with 99.7% confidence level. The LSSS power calculated using this new methodology is 9.1 MW, based on core outlet coolant temperature of 60 deg. C, and primary coolant flow rate of 1800 gpm, compared to 8.3 MW obtained from the analytical method using the EHCFs with same operating conditions. The same methodology was also used to calculate the safety limit (SL) for the MITR, conservatively determined using onset of flow instability (OFI) as the criterion, to verify that adequate safety margin exists between LSSS and SL. The calculated SL is 10.6 MW, which is 1.5 MW higher than LSSS. (authors)

Chiang, K. Y. [Nuclear Science and Engineering Dept., Massachusetts Inst. of Technology, 77 Massachusetts Ave, Cambridge, MA 02139 (United States); Hu, L. W. [Nuclear Reactor Laboratory, Massachusetts Inst. of Technology, Cambridge, MA 02139 (United States); Forget, B. [Nuclear Science and Engineering Dept., Massachusetts Inst. of Technology, 77 Massachusetts Ave, Cambridge, MA 02139 (United States)

2012-07-01T23:59:59.000Z

10

ERDC/CRRELTR-06-16 Propagation of Uncertainties in Sea Ice  

E-Print Network [OSTI]

of the global heat bal- ance. This capability is attributed to the unique location of sea ice at the interface in the polar region has precipitated increased efforts to measure sea ice thickness as an index for global heatERDC/CRRELTR-06-16 Propagation of Uncertainties in Sea Ice Thickness Calculations from Basin

Geiger, Cathleen

11

Propagating Uncertainty in Solar Panel Performance for Life Cycle Modeling in Early Stage Design  

E-Print Network [OSTI]

Propagating Uncertainty in Solar Panel Performance for Life Cycle Modeling in Early Stage Design. This work is conducted in the context of an amorphous photovoltaic (PV) panel, using data gathered from the National Solar Radiation Database, as well as realistic data collected from an experimental hardware setup

Yang, Maria

12

Integration of the NUREG-1150 analyses: Calculation of risk and propagation of uncertainties  

SciTech Connect (OSTI)

The calculation of risk and the propagation of uncertainties in the US Nuclear Regulatory Commission's reassessment of risk from commercial nuclear power stations (i.e., NUREG-1150) is described. The overall integration of the analysis performed for each nuclear power station considered in NUREG-1150 is based on: (1) relatively fast-running models for the individual parts of the analysis, (2) well-defined interfaces between the individual parts of the analysis, (3) definition of selected issues for uncertainty analysis, (4) use of Monte Carlo procedures in conjunction with an efficient sampling technique (i.e., Latin hypercubs sampling) to propagate uncertainties, and (5) automation of the overall analysis. The preceding approach is described and then illustrated with the analysis performed for the Peach Bottom nuclear power station. 56 refs., 4 figs., 3 tabs.

Helton, J.C.; Griesmeyer, J.M.; Haskin, F.E.; Iman, R.L.; Amos, C.N.; Murfin, W.B.

1987-01-01T23:59:59.000Z

13

Comparison of nuclear data uncertainty propagation methodologies for PWR burn-up simulations  

E-Print Network [OSTI]

Several methodologies using different levels of approximations have been developed for propagating nuclear data uncertainties in nuclear burn-up simulations. Most methods fall into the two broad classes of Monte Carlo approaches, which are exact apart from statistical uncertainties but require additional computation time, and first order perturbation theory approaches, which are efficient for not too large numbers of considered response functions but only applicable for sufficiently small nuclear data uncertainties. Some methods neglect isotopic composition uncertainties induced by the depletion steps of the simulations, others neglect neutron flux uncertainties, and the accuracy of a given approximation is often very hard to quantify. In order to get a better sense of the impact of different approximations, this work aims to compare results obtained based on different approximate methodologies with an exact method, namely the NUDUNA Monte Carlo based approach developed by AREVA GmbH. In addition, the impact of different covariance data is studied by comparing two of the presently most complete nuclear data covariance libraries (ENDF/B-VII.1 and SCALE 6.0), which reveals a high dependency of the uncertainty estimates on the source of covariance data. The burn-up benchmark Exercise I-1b proposed by the OECD expert group "Benchmarks for Uncertainty Analysis in Modeling (UAM) for the Design, Operation and Safety Analysis of LWRs" is studied as an example application. The burn-up simulations are performed with the SCALE 6.0 tool suite.

Carlos Javier Diez; Oliver Buss; Axel Hoefer; Dieter Porsch; Oscar Cabellos

2014-11-04T23:59:59.000Z

14

Study of Monte Carlo approach to experimental uncertainty propagation with MSTW 2008 PDFs  

E-Print Network [OSTI]

We investigate the Monte Carlo approach to propagation of experimental uncertainties within the context of the established "MSTW 2008" global analysis of parton distribution functions (PDFs) of the proton at next-to-leading order in the strong coupling. We show that the Monte Carlo approach using replicas of the original data gives PDF uncertainties in good agreement with the usual Hessian approach using the standard Delta(chi^2) = 1 criterion, then we explore potential parameterisation bias by increasing the number of free parameters, concluding that any parameterisation bias is likely to be small, with the exception of the valence-quark distributions at low momentum fractions x. We motivate the need for a larger tolerance, Delta(chi^2) > 1, by making fits to restricted data sets and idealised consistent or inconsistent pseudodata. Instead of using data replicas, we alternatively produce PDF sets randomly distributed according to the covariance matrix of fit parameters including appropriate tolerance values,...

Watt, G

2012-01-01T23:59:59.000Z

15

Propagation of Isotopic Bias and Uncertainty to Criticality Safety Analyses of PWR Waste Packages  

SciTech Connect (OSTI)

Burnup credit methodology is economically advantageous because significantly higher loading capacity may be achieved for spent nuclear fuel (SNF) casks based on this methodology as compared to the loading capacity based on a fresh fuel assumption. However, the criticality safety analysis for establishing the loading curve based on burnup credit becomes increasingly complex as more parameters accounting for spent fuel isotopic compositions are introduced to the safety analysis. The safety analysis requires validation of both depletion and criticality calculation methods. Validation of a neutronic-depletion code consists of quantifying the bias and the uncertainty associated with the bias in predicted SNF compositions caused by cross-section data uncertainty and by approximations in the calculational method. The validation is based on comparison between radiochemical assay (RCA) data and calculated isotopic concentrations for fuel samples representative of SNF inventory. The criticality analysis methodology for commercial SNF disposal allows burnup credit for 14 actinides and 15 fission product isotopes in SNF compositions. The neutronic-depletion method for disposal criticality analysis employing burnup credit is the two-dimensional (2-D) depletion sequence TRITON (Transport Rigor Implemented with Time-dependent Operation for Neutronic depletion)/NEWT (New ESC-based Weighting Transport code) and the 44GROUPNDF5 crosssection library in the Standardized Computer Analysis for Licensing Evaluation (SCALE 5.1) code system. The SCALE 44GROUPNDF5 cross section library is based on the Evaluated Nuclear Data File/B Version V (ENDF/B-V) library. The criticality calculation code for disposal criticality analysis employing burnup credit is General Monte Carlo N-Particle (MCNP) Transport Code. The purpose of this calculation report is to determine the bias on the calculated effective neutron multiplication factor, k{sub eff}, due to the bias and bias uncertainty associated with predicted spent fuel compositions (i.e., determine the penalty in reactivity due to isotopic composition bias and uncertainty) for use in disposal criticality analysis employing burnup credit. The method used in this calculation to propagate the isotopic bias and bias-uncertainty values to k{sub eff} is the Monte Carlo uncertainty sampling method. The development of this report is consistent with 'Test Plan for: Isotopic Validation for Postclosure Criticality of Commercial Spent Nuclear Fuel'. This calculation report has been developed in support of burnup credit activities for the proposed repository at Yucca Mountain, Nevada, and provides a methodology that can be applied to other criticality safety applications employing burnup credit.

Radulescu, Georgeta [ORNL

2010-06-01T23:59:59.000Z

16

Study of Monte Carlo approach to experimental uncertainty propagation with MSTW 2008 PDFs  

E-Print Network [OSTI]

We investigate the Monte Carlo approach to propagation of experimental uncertainties within the context of the established "MSTW 2008" global analysis of parton distribution functions (PDFs) of the proton at next-to-leading order in the strong coupling. We show that the Monte Carlo approach using replicas of the original data gives PDF uncertainties in good agreement with the usual Hessian approach using the standard Delta(chi^2) = 1 criterion, then we explore potential parameterisation bias by increasing the number of free parameters, concluding that any parameterisation bias is likely to be small, with the exception of the valence-quark distributions at low momentum fractions x. We motivate the need for a larger tolerance, Delta(chi^2) > 1, by making fits to restricted data sets and idealised consistent or inconsistent pseudodata. Instead of using data replicas, we alternatively produce PDF sets randomly distributed according to the covariance matrix of fit parameters including appropriate tolerance values, then we demonstrate a simpler method to produce an arbitrary number of random predictions on-the-fly from the existing eigenvector PDF sets. Finally, as a simple example application, we use Bayesian reweighting to study the effect of recent LHC data on the lepton charge asymmetry from W boson decays.

G. Watt; R. S. Thorne

2012-05-17T23:59:59.000Z

17

Fixed-flowrate total water network synthesis under uncertainty with risk management  

Science Journals Connector (OSTI)

Abstract This work addresses the problem of integrated water network synthesis under uncertainty with risk management. We consider a superstructure consisting of water sources, regenerators, and sinks that leads to a mixed-integer quadratically-constrained quadratic program (MIQCQP) for a fixed-flowrate total water network synthesis problem. Uncertainty in the problem is accounted for via a recourse-based two-stage stochastic programming formulation with discrete scenarios that gives rise to a multiscenario MIQCQP comprising network design in the first stage and its operation in the second stage acting as recourse. In addition, we extend the model to address risk management using the Conditional Value-at-Risk (CVaR) metric. Because a large number of scenarios is often required to capture the underlying uncertainty of the problem, causing the model to suffer from the curse of dimensionality, we propose a stepwise solution strategy to reduce the computational load. We illustrate this methodology on a case study inspired from the water network of a petroleum refinery in Malaysia. The presence of nonconvex bilinear terms necessitates the use of global optimization techniques for which we employ a new global MIQCQP solver, GAMS/GloMIQO and verify the solutions with BARON. Our computational results show that total water network synthesis under uncertainty with risk management problems can be solved to global optimality in reasonable time.

Cheng Seong Khor; Benoit Chachuat; Nilay Shah

2014-01-01T23:59:59.000Z

18

Preprint ANL/MCS-P1833-0111 Gradient-Enhanced Universal Kriging for Uncertainty Propagation in Nuclear Engineering  

E-Print Network [OSTI]

in Nuclear Engineering Brian A. Lockwood* and Mihai Anitescu+ * University of Wyoming, Department nuclear engineering system for use in uncertainty propagation. Building on our recent work using nuclear engineering simulation outputs. II. MODEL OVERVIEW For the GEUK model, the mean behavior

Anitescu, Mihai

19

Uncertainty propagation in a model for the estimation of the1 ground level concentration of dioxin/furans emitted from a waste2  

E-Print Network [OSTI]

Uncertainty propagation in a model for the estimation of the1 ground level concentration of dioxin concentration of dioxin/furans emitted from a waste gasification plant. Under the17 condition of insufficient

Paris-Sud XI, Université de

20

An algorithm for U-Pb isotope dilution data reduction and uncertainty propagation  

E-Print Network [OSTI]

High-precision U-Pb geochronology by isotope dilution-thermal ionization mass spectrometry is integral to a variety of Earth science disciplines, but its ultimate resolving power is quantified by the uncertainties of ...

McLean, Noah Morgan

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Characterization, propagation and analysis of aleatory and epistemic uncertainty in the 2008 performance assessment for the proposed repository for radioactive waste at Yucca Mountain, Nevada.  

SciTech Connect (OSTI)

The 2008 performance assessment (PA) for the proposed repository for high-level radioactive waste at Yucca Mountain (YM), Nevada, illustrates the conceptual structure of risk assessments for complex systems. The 2008 YM PA is based on the following three conceptual entities: a probability space that characterizes aleatory uncertainty; a function that predicts consequences for individual elements of the sample space for aleatory uncertainty; and a probability space that characterizes epistemic uncertainty. These entities and their use in the characterization, propagation and analysis of aleatory and epistemic uncertainty are described and illustrated with results from the 2008 YM PA.

Helton, Jon Craig; Sallaberry, Cedric M.; Hansen, Clifford W.

2010-10-01T23:59:59.000Z

22

Uncertainty Propagation in Hypersonic Flight Dynamics and Comparison of Different Methods  

E-Print Network [OSTI]

manner. As- sume solution of the stochastic di erential equation to be x(t; ). For second order processes, the solution for every component of x2uncertainty in the system param- eters, characterized...

Prabhakar, Avinash

2010-01-16T23:59:59.000Z

23

Total Measurement Uncertainty (TMU) for Nondestructive Assay of Transuranic (TRU) Waste at the WRAP Facility  

SciTech Connect (OSTI)

This report examines the contributing factors to NDA measurement uncertainty at WRAP The significance of each factor on the TMU is analyzed and a final method is given for determining the TMU for NDA measurements at WRAP. As more data becomes available and WRAP gains in operational experience this report will be reviewed semi annually and updated as necessary.

WILLS, C.E.

2000-01-06T23:59:59.000Z

24

Total  

Gasoline and Diesel Fuel Update (EIA)

Total Total .............. 16,164,874 5,967,376 22,132,249 2,972,552 280,370 167,519 18,711,808 1993 Total .............. 16,691,139 6,034,504 22,725,642 3,103,014 413,971 226,743 18,981,915 1994 Total .............. 17,351,060 6,229,645 23,580,706 3,230,667 412,178 228,336 19,709,525 1995 Total .............. 17,282,032 6,461,596 23,743,628 3,565,023 388,392 283,739 19,506,474 1996 Total .............. 17,680,777 6,370,888 24,051,665 3,510,330 518,425 272,117 19,750,793 Alabama Total......... 570,907 11,394 582,301 22,601 27,006 1,853 530,841 Onshore ................ 209,839 11,394 221,233 22,601 16,762 1,593 180,277 State Offshore....... 209,013 0 209,013 0 10,244 260 198,509 Federal Offshore... 152,055 0 152,055 0 0 0 152,055 Alaska Total ............ 183,747 3,189,837 3,373,584 2,885,686 0 7,070 480,828 Onshore ................ 64,751 3,182,782

25

Total............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Total................................................................... Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546

26

Total...................  

Gasoline and Diesel Fuel Update (EIA)

4,690,065 52,331,397 2,802,751 4,409,699 7,526,898 209,616 1993 Total................... 4,956,445 52,535,411 2,861,569 4,464,906 7,981,433 209,666 1994 Total................... 4,847,702 53,392,557 2,895,013 4,533,905 8,167,033 202,940 1995 Total................... 4,850,318 54,322,179 3,031,077 4,636,500 8,579,585 209,398 1996 Total................... 5,241,414 55,263,673 3,158,244 4,720,227 8,870,422 206,049 Alabama ...................... 56,522 766,322 29,000 62,064 201,414 2,512 Alaska.......................... 16,179 81,348 27,315 12,732 75,616 202 Arizona ........................ 27,709 689,597 28,987 49,693 26,979 534 Arkansas ..................... 46,289 539,952 31,006 67,293 141,300 1,488 California ..................... 473,310 8,969,308 235,068 408,294 693,539 36,613 Colorado...................... 110,924 1,147,743

27

Uncertainty propagation in puff-based dispersion models using polynomial chaos Umamaheswara Konda a,*, Tarunraj Singh a  

E-Print Network [OSTI]

-based dispersion model is used as a test case to study the effect of uncertainties in the model parameters and radiological incidents like the Chernobyl nuclear accident in 1986 (National Research Council (U.S.), 2003 of the releases, some of which are addressed in the (Environmental Protection Agency) EPA's Guide- line on Air

Singh, Tarunraj

28

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

7.1 7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1 2.8 2.4 2,500 to 2,999..................................................... 10.3 3.7 1.8 2.8 2.1 3,000 to 3,499..................................................... 6.7 2.0 1.4 1.7 1.6 3,500 to 3,999..................................................... 5.2 1.6 0.8 1.5 1.4 4,000 or More.....................................................

29

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

0.7 0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7 1.3 2,500 to 2,999..................................................... 10.3 3.0 1.8 0.5 0.7 3,000 to 3,499..................................................... 6.7 2.1 1.2 0.5 0.4 3,500 to 3,999..................................................... 5.2 1.5 0.8 0.3 0.4 4,000 or More.....................................................

30

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

25.6 25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.9 1.0 500 to 999........................................................... 23.8 4.6 3.9 9.0 6.3 1,000 to 1,499..................................................... 20.8 2.8 4.4 8.6 5.0 1,500 to 1,999..................................................... 15.4 1.9 3.5 6.0 4.0 2,000 to 2,499..................................................... 12.2 2.3 3.2 4.1 2.6 2,500 to 2,999..................................................... 10.3 2.2 2.7 3.0 2.4 3,000 to 3,499..................................................... 6.7 1.6 2.1 2.1 0.9 3,500 to 3,999..................................................... 5.2 1.1 1.7 1.5 0.9 4,000 or More.....................................................

31

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

4.2 4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to 2,999..................................................... 10.3 2.4 0.9 1.4 3,000 to 3,499..................................................... 6.7 0.9 0.3 0.6 3,500 to 3,999..................................................... 5.2 0.9 0.4 0.5 4,000 or More.....................................................

32

Total.........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Floorspace (Square Feet) Floorspace (Square Feet) Total Floorspace 2 Fewer than 500.................................................. 3.2 Q 0.8 0.9 0.8 0.5 500 to 999.......................................................... 23.8 1.5 5.4 5.5 6.1 5.3 1,000 to 1,499.................................................... 20.8 1.4 4.0 5.2 5.0 5.2 1,500 to 1,999.................................................... 15.4 1.4 3.1 3.5 3.6 3.8 2,000 to 2,499.................................................... 12.2 1.4 3.2 3.0 2.3 2.3 2,500 to 2,999.................................................... 10.3 1.5 2.3 2.7 2.1 1.7 3,000 to 3,499.................................................... 6.7 1.0 2.0 1.7 1.0 1.0 3,500 to 3,999.................................................... 5.2 0.8 1.5 1.5 0.7 0.7 4,000 or More.....................................................

33

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

. . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.4 500 to 999........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to 2,999..................................................... 10.3 2.2 1.7 0.6 3,000 to 3,499..................................................... 6.7 1.6 1.0 0.6 3,500 to 3,999..................................................... 5.2 1.1 0.9 0.3 4,000 or More.....................................................

34

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

7.1 7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4 2,500 to 2,999..................................................... 10.3 0.5 0.5 0.4 1.1 3,000 to 3,499..................................................... 6.7 0.3 Q 0.4 0.3 3,500 to 3,999..................................................... 5.2 Q Q Q Q 4,000 or More.....................................................

35

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

.. .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7 0.4 2,139 1,598 Q Q Q Q 2,500 to 2,999........................................ 10.1 Q Q Q Q Q Q Q 3,000 or More......................................... 29.6 0.3 Q Q Q Q Q Q Heated Floorspace (Square Feet) None...................................................... 3.6 1.8 1,048 0 Q 827 0 407 Fewer than 500......................................

36

Total...................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

2,033 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546 3,500 to 3,999................................................. 5.2 3,549 2,509 1,508

37

Total...........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8 2,500 to 2,999..................................... 10.3 1.2 2.2 2.3 1.7 2.9 0.6 2.0 3,000 to 3,499..................................... 6.7 0.9 1.4 1.5 1.0 1.9 0.4 1.4 3,500 to 3,999..................................... 5.2 0.8 1.2 1.0 0.8 1.5 0.4 1.3 4,000 or More...................................... 13.3 0.9 1.9 2.2 2.0 6.4 0.6 1.9 Heated Floorspace

38

Total...........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500.................................... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9 1.8 1.4 2.2 2.1 1.6 0.8 2,500 to 2,999..................................... 10.3 1.6 0.9 1.1 1.1 1.5 1.5 1.7 0.8 3,000 to 3,499..................................... 6.7 1.0 0.5 0.8 0.8 1.2 0.8 0.9 0.8 3,500 to 3,999..................................... 5.2 1.1 0.3 0.7 0.7 0.4 0.5 1.0 0.5 4,000 or More...................................... 13.3

39

Total................................................  

U.S. Energy Information Administration (EIA) Indexed Site

.. .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to 2,499.............................. 12.2 11.9 2,039 1,731 1,055 2,143 1,813 1,152 Q Q Q 2,500 to 2,999.............................. 10.3 10.1 2,519 2,004 1,357 2,492 2,103 1,096 Q Q Q 3,000 or 3,499.............................. 6.7 6.6 3,014 2,175 1,438 3,047 2,079 1,108 N N N 3,500 to 3,999.............................. 5.2 5.1 3,549 2,505 1,518 Q Q Q N N N 4,000 or More...............................

40

Direct Aerosol Forcing Uncertainty  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Understanding sources of uncertainty in aerosol direct radiative forcing (DRF), the difference in a given radiative flux component with and without aerosol, is essential to quantifying changes in Earth's radiation budget. We examine the uncertainty in DRF due to measurement uncertainty in the quantities on which it depends: aerosol optical depth, single scattering albedo, asymmetry parameter, solar geometry, and surface albedo. Direct radiative forcing at the top of the atmosphere and at the surface as well as sensitivities, the changes in DRF in response to unit changes in individual aerosol or surface properties, are calculated at three locations representing distinct aerosol types and radiative environments. The uncertainty in DRF associated with a given property is computed as the product of the sensitivity and typical measurement uncertainty in the respective aerosol or surface property. Sensitivity and uncertainty values permit estimation of total uncertainty in calculated DRF and identification of properties that most limit accuracy in estimating forcing. Total uncertainties in modeled local diurnally averaged forcing range from 0.2 to 1.3 W m-2 (42 to 20%) depending on location (from tropical to polar sites), solar zenith angle, surface reflectance, aerosol type, and aerosol optical depth. The largest contributor to total uncertainty in DRF is usually single scattering albedo; however decreasing measurement uncertainties for any property would increase accuracy in DRF. Comparison of two radiative transfer models suggests the contribution of modeling error is small compared to the total uncertainty although comparable to uncertainty arising from some individual properties.

Mccomiskey, Allison

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Orifice flow measurement uncertainty  

SciTech Connect (OSTI)

A computer program is now available from Union Carbide that evaluates the total flow uncertainty of orifice flowmeter systems. Tolerance values for every component in the system and the sensitivity of the measured flowrate to each component can be established using historical data and published hardware specifications. Knowing the tolerance and sensitivity values, a total measurement uncertainty can be estimated with a 95% confidence level. This computer program provides a powerful design tool to ensure correct component matching and total metering system optimization.

Samples, C.R.

1984-04-01T23:59:59.000Z

42

Assessment and Propagation of Model Uncertainty  

E-Print Network [OSTI]

1982). Outlook for World Oil Prices. Washington DC: U. S.run. But, in view of the oil price example, which is worse—Case N-2524-RC, of Oil Prices. Santa Monica, CA: RAND.

David Draper

2011-01-01T23:59:59.000Z

43

Propagation of Uncertainty in Chemically Activated Systems  

E-Print Network [OSTI]

represent the principal pathways of the radical conversion in many hydrocarbon oxidation and combustion processes. Low- temperature oxidation of hydrocarbons ( 800 K) is critically important in their use as fuels

Androulakis, Ioannis (Yannis)

44

Assessor Training Measurement Uncertainty  

E-Print Network [OSTI]

NVLAP Assessor Training Measurement Uncertainty #12;Assessor Training 2009: Measurement Uncertainty Training 2009: Measurement Uncertainty 3 Measurement Uncertainty ·Calibration and testing labs performing Training 2009: Measurement Uncertainty 4 Measurement Uncertainty ·When the nature of the test precludes

45

The Low energy structure of the Nucleon-Nucleon interaction: Statistical vs Systematic Uncertainties  

E-Print Network [OSTI]

We analyse the low energy NN interaction by extracting threshold parameters from the coupled channel effective range expansion up to $j \\le 5$. The statistical uncertainties are propagated from a previous Monte Carlo bootstrap approach. To give an estimate of the systematic uncertainties we consider six high quality potentials. We find that systematic uncertainties are typically an order of magnitude larger than statistical uncertainties.

R. Navarro Perez; J. E. Amaro; E. Ruiz Arriola

2014-10-29T23:59:59.000Z

46

The Low energy structure of the Nucleon-Nucleon interaction: Statistical vs Systematic Uncertainties  

E-Print Network [OSTI]

We analyse the low energy NN interaction by extracting threshold parameters from the coupled channel effective range expansion up to $j \\le 5$. The statistical uncertainties are propagated from a previous Monte Carlo bootstrap approach. To give an estimate of the systematic uncertainties we consider six high quality potentials. We find that systematic uncertainties are typically an order of magnitude larger than statistical uncertainties.

Perez, R Navarro; Arriola, E Ruiz

2014-01-01T23:59:59.000Z

47

A surrogate-based uncertainty quantification with quantifiable errors  

SciTech Connect (OSTI)

Surrogate models are often employed to reduce the computational cost required to complete uncertainty quantification, where one is interested in propagating input parameters uncertainties throughout a complex engineering model to estimate responses uncertainties. An improved surrogate construction approach is introduced here which places a premium on reducing the associated computational cost. Unlike existing methods where the surrogate is constructed first, then employed to propagate uncertainties, the new approach combines both sensitivity and uncertainty information to render further reduction in the computational cost. Mathematically, the reduction is described by a range finding algorithm that identifies a subspace in the parameters space, whereby parameters uncertainties orthogonal to the subspace contribute negligible amount to the propagated uncertainties. Moreover, the error resulting from the reduction can be upper-bounded. The new approach is demonstrated using a realistic nuclear assembly model and compared to existing methods in terms of computational cost and accuracy of uncertainties. Although we believe the algorithm is general, it will be applied here for linear-based surrogates and Gaussian parameters uncertainties. The generalization to nonlinear models will be detailed in a separate article. (authors)

Bang, Y.; Abdel-Khalik, H. S. [North Carolina State Univ., Raleigh, NC 27695 (United States)

2012-07-01T23:59:59.000Z

48

RUMINATIONS ON NDA MEASUREMENT UNCERTAINTY COMPARED TO DA UNCERTAINTY  

SciTech Connect (OSTI)

It is difficult to overestimate the importance that physical measurements performed with nondestructive assay instruments play throughout the nuclear fuel cycle. They underpin decision making in many areas and support: criticality safety, radiation protection, process control, safeguards, facility compliance, and waste measurements. No physical measurement is complete or indeed meaningful, without a defensible and appropriate accompanying statement of uncertainties and how they combine to define the confidence in the results. The uncertainty budget should also be broken down in sufficient detail suitable for subsequent uses to which the nondestructive assay (NDA) results will be applied. Creating an uncertainty budget and estimating the total measurement uncertainty can often be an involved process, especially for non routine situations. This is because data interpretation often involves complex algorithms and logic combined in a highly intertwined way. The methods often call on a multitude of input data subject to human oversight. These characteristics can be confusing and pose a barrier to developing and understanding between experts and data consumers. ASTM subcommittee C26-10 recognized this problem in the context of how to summarize and express precision and bias performance across the range of standards and guides it maintains. In order to create a unified approach consistent with modern practice and embracing the continuous improvement philosophy a consensus arose to prepare a procedure covering the estimation and reporting of uncertainties in non destructive assay of nuclear materials. This paper outlines the needs analysis, objectives and on-going development efforts. In addition to emphasizing some of the unique challenges and opportunities facing the NDA community we hope this article will encourage dialog and sharing of best practice and furthermore motivate developers to revisit the treatment of measurement uncertainty.

Salaymeh, S.; Ashley, W.; Jeffcoat, R.

2010-06-17T23:59:59.000Z

49

Handling uncertainty in science  

Science Journals Connector (OSTI)

...techniques to predict uncertainty in...techniques used to predict uncertainty in...economy, or of the outbreak of life-threatening pandemic flu, have parallels...weather forecast model. (b) Example...ocean-atmosphere model. Source: European...

2011-01-01T23:59:59.000Z

50

Uncertainty and Risk  

Science Journals Connector (OSTI)

This chapter shows how multiple realizations can be used to support the assessment of uncertainty and risk.

Mario E. Rossi; Clayton V. Deutsch

2014-01-01T23:59:59.000Z

51

Uncertainty Analysis for Photovoltaic Degradation Rates (Poster)  

SciTech Connect (OSTI)

Dependable and predictable energy production is the key to the long-term success of the PV industry. PV systems show over the lifetime of their exposure a gradual decline that depends on many different factors such as module technology, module type, mounting configuration, climate etc. When degradation rates are determined from continuous data the statistical uncertainty is easily calculated from the regression coefficients. However, total uncertainty that includes measurement uncertainty and instrumentation drift is far more difficult to determine. A Monte Carlo simulation approach was chosen to investigate a comprehensive uncertainty analysis. The most important effect for degradation rates is to avoid instrumentation that changes over time in the field. For instance, a drifting irradiance sensor, which can be achieved through regular calibration, can lead to a substantially erroneous degradation rates. However, the accuracy of the irradiance sensor has negligible impact on degradation rate uncertainty emphasizing that precision (relative accuracy) is more important than absolute accuracy.

Jordan, D.; Kurtz, S.; Hansen, C.

2014-04-01T23:59:59.000Z

52

Uncertainties in Gapped Graphene  

E-Print Network [OSTI]

Motivated by graphene-based quantum computer we examine the time-dependence of the position-momentum and position-velocity uncertainties in the monolayer gapped graphene. The effect of the energy gap to the uncertainties is shown to appear via the Compton-like wavelength $\\lambda_c$. The uncertainties in the graphene are mainly contributed by two phenomena, spreading and zitterbewegung. While the former determines the uncertainties in the long-range of time, the latter gives the highly oscillation to the uncertainties in the short-range of time. The uncertainties in the graphene are compared with the corresponding values for the usual free Hamiltonian $\\hat{H}_{free} = (p_1^2 + p_2^2) / 2 M$. It is shown that the uncertainties can be under control within the quantum mechanical law if one can choose the gap parameter $\\lambda_c$ freely.

Eylee Jung; Kwang S. Kim; DaeKil Park

2011-07-27T23:59:59.000Z

53

Uncertainty Propagation for Quality Assurance in Reinforcement Learning  

E-Print Network [OSTI]

be obtained. Finally we verify this observation on an application to gas turbine control. I. INTRODUCTION]. Antos et.al. [7] provided a broad capacity analysis of Bellman residual minimisation in batch RL

54

Uncertainty propagation on damage evolution of a concrete structure subjected  

E-Print Network [OSTI]

the structure is subjected to. To investigate the influence of the material properties variability on the long-term for concrete materials 1. Introduction Deep nuclear waste disposal facilities need to be studied over periods rock in a deep underground storage. Calcium leaching leads to important changes in the concrete

Paris-Sud XI, Université de

55

TOTAL Full-TOTAL Full-  

E-Print Network [OSTI]

Conducting - Orchestral 6 . . 6 5 1 . 6 5 . . 5 Conducting - Wind Ensemble 3 . . 3 2 . . 2 . 1 . 1 Early- X TOTAL Full- Part- X TOTAL Alternative Energy 6 . . 6 11 . . 11 13 2 . 15 Biomedical Engineering 52 English 71 . 4 75 70 . 4 74 72 . 3 75 Geosciences 9 . 1 10 15 . . 15 19 . . 19 History 37 1 2 40 28 3 3 34

Portman, Douglas

56

Total Imports  

U.S. Energy Information Administration (EIA) Indexed Site

Data Series: Imports - Total Imports - Crude Oil Imports - Crude Oil, Commercial Imports - by SPR Imports - into SPR by Others Imports - Total Products Imports - Total Motor Gasoline Imports - Finished Motor Gasoline Imports - Reformulated Gasoline Imports - Reformulated Gasoline Blended w/ Fuel Ethanol Imports - Other Reformulated Gasoline Imports - Conventional Gasoline Imports - Conv. Gasoline Blended w/ Fuel Ethanol Imports - Conv. Gasoline Blended w/ Fuel Ethanol, Ed55 & Ed55 Imports - Other Conventional Gasoline Imports - Motor Gasoline Blend. Components Imports - Motor Gasoline Blend. Components, RBOB Imports - Motor Gasoline Blend. Components, RBOB w/ Ether Imports - Motor Gasoline Blend. Components, RBOB w/ Alcohol Imports - Motor Gasoline Blend. Components, CBOB Imports - Motor Gasoline Blend. Components, GTAB Imports - Motor Gasoline Blend. Components, Other Imports - Fuel Ethanol Imports - Kerosene-Type Jet Fuel Imports - Distillate Fuel Oil Imports - Distillate F.O., 15 ppm Sulfur and Under Imports - Distillate F.O., > 15 ppm to 500 ppm Sulfur Imports - Distillate F.O., > 500 ppm to 2000 ppm Sulfur Imports - Distillate F.O., > 2000 ppm Sulfur Imports - Residual Fuel Oil Imports - Propane/Propylene Imports - Other Other Oils Imports - Kerosene Imports - NGPLs/LRGs (Excluding Propane/Propylene) Exports - Total Crude Oil and Products Exports - Crude Oil Exports - Products Exports - Finished Motor Gasoline Exports - Kerosene-Type Jet Fuel Exports - Distillate Fuel Oil Exports - Residual Fuel Oil Exports - Propane/Propylene Exports - Other Oils Net Imports - Total Crude Oil and Products Net Imports - Crude Oil Net Imports - Petroleum Products Period: Weekly 4-Week Avg.

57

Deconvolution of variability and uncertainty in the Cassini safety analysis  

SciTech Connect (OSTI)

The standard method for propagation of uncertainty in a risk analysis requires rerunning the risk calculation numerous times with model parameters chosen from their uncertainty distributions. This was not practical for the Cassini nuclear safety analysis, due to the computationally intense nature of the risk calculation. A less computationally intense procedure was developed which requires only two calculations for each accident case. The first of these is the standard 'best-estimate' calculation. In the second calculation, variables and parameters change simultaneously. The mathematical technique of deconvolution is then used to separate out an uncertainty multiplier distribution, which can be used to calculate distribution functions at various levels of confidence.

Kampas, Frank J.; Loughin, Stephen [Lockheed Martin Missiles and Space, P.O. Box 8555, Philadelphia, Pennsylvania 19101 (United States); WAM Systems, 650 Loraine Street, Ardmore, Pennsylvania 19003 (United States)

1998-01-15T23:59:59.000Z

58

Hadronic uncertainties in the elastic scattering of supersymmetric dark matter  

SciTech Connect (OSTI)

We review the uncertainties in the spin-independent and spin-dependent elastic scattering cross sections of supersymmetric dark matter particles on protons and neutrons. We propagate the uncertainties in quark masses and hadronic matrix elements that are related to the {pi}-nucleon {sigma} term and the spin content of the nucleon. By far the largest single uncertainty is that in spin-independent scattering induced by our ignorance of the matrix elements linked to the {pi}-nucleon {sigma} term, which affects the ratio of cross sections on proton and neutron targets as well as their absolute values. This uncertainty is already impacting the interpretations of experimental searches for cold dark matter. We plead for an experimental campaign to determine better the {pi}-nucleon {sigma} term. Uncertainties in the spin content of the proton affect significantly, but less strongly, the calculation of rates used in indirect searches.

Ellis, John [TH Division, Physics Department, CERN, 1211 Geneva 23 (Switzerland); Olive, Keith A.; Savage, Christopher [William I. Fine Theoretical Physics Institute, School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455 (United States)

2008-03-15T23:59:59.000Z

59

Mathematical treatment of uncertainty in the speech recognition process  

Science Journals Connector (OSTI)

One of the main difficulties in the speech recognition process is the treatment of the imprecisions around it. They have origin in the differences between the articulatory system of each person and the physical properties of the sound propagation. Moreover, ... Keywords: Hidden Markov model, fuzzy, interval analysis, mathematical treatment, speech recognition, uncertainty

Hesdras Oliveira Viana; Diogo Pereira Silva De Novais; Roque Mendes Prado Trindade

2010-11-01T23:59:59.000Z

60

Characterizing orbit uncertainty due to atmospheric uncertainty  

E-Print Network [OSTI]

transition matrix which can be determined by the following: 4(t, tQ) = A 4'(i, tQ), (3. 17) where A can be determined from Eq. (3. 4) as Of(z) Ox (3. 18) and C (tQ, tQ) is the identity matrix. We can propagate just the state by using x(t ) = e(t, tQ) x(tQ... transition matrix which can be determined by the following: 4(t, tQ) = A 4'(i, tQ), (3. 17) where A can be determined from Eq. (3. 4) as Of(z) Ox (3. 18) and C (tQ, tQ) is the identity matrix. We can propagate just the state by using x(t ) = e(t, tQ) x(tQ...

Wilkins, Matthew Paul

2012-06-07T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Managing uncertainty in integrated environmental modelling: The UncertWeb framework  

Science Journals Connector (OSTI)

Web-based distributed modelling architectures are gaining increasing recognition as potentially useful tools to build holistic environmental models, combining individual components in complex workflows. However, existing web-based modelling frameworks ... Keywords: Interoperability, Model web, UncertWeb, Uncertainty, Uncertainty propagation, Visualisation, Web services

Lucy Bastin; Dan Cornford; Richard Jones; Gerard B. M. Heuvelink; Edzer Pebesma; Christoph Stasch; Stefano Nativi; Paolo Mazzetti; Matthew Williams

2013-01-01T23:59:59.000Z

62

Image Segmentation and Uncertainty  

Science Journals Connector (OSTI)

From the Publisher:Presents the first unified theory of image segmentation, written by the winners of the 1985 Pattern Recognition Society medal. Until now, image processing algorithms have always been beset by uncertainties, no one method proving completely ...

Roland 1949- Wilson; Michael Spann

1988-02-01T23:59:59.000Z

63

Evaluating prediction uncertainty  

SciTech Connect (OSTI)

The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented.

McKay, M.D. [Los Alamos National Lab., NM (United States)

1995-03-01T23:59:59.000Z

64

Uncertainty Analysis Economic Evaluations  

E-Print Network [OSTI]

uncertainties in typical oil and gas projects: 1. The oil price, 2. The investments (capex) and operating 4.1 Oil Prices...............................................................................................14 4.1.1 Analysis of historical oil prices........................................................15

Bhulai, Sandjai

65

Managing Model Data Introduced Uncertainties in Simulator Predictions for Generation IV Systems via Optimum Experimental Design  

SciTech Connect (OSTI)

An optimization technique has been developed to select optimized experimental design specifications to produce data specifically designed to be assimilated to optimize a given reactor concept. Data from the optimized experiment is assimilated to generate posteriori uncertainties on the reactor concept’s core attributes from which the design responses are computed. The reactor concept is then optimized with the new data to realize cost savings by reducing margin. The optimization problem iterates until an optimal experiment is found to maximize the savings. A new generation of innovative nuclear reactor designs, in particular fast neutron spectrum recycle reactors, are being considered for the application of closing the nuclear fuel cycle in the future. Safe and economical design of these reactors will require uncertainty reduction in basic nuclear data which are input to the reactor design. These data uncertainty propagate to design responses which in turn require the reactor designer to incorporate additional safety margin into the design, which often increases the cost of the reactor. Therefore basic nuclear data needs to be improved and this is accomplished through experimentation. Considering the high cost of nuclear experiments, it is desired to have an optimized experiment which will provide the data needed for uncertainty reduction such that a reactor design concept can meet its target accuracies or to allow savings to be realized by reducing the margin required due to uncertainty propagated from basic nuclear data. However, this optimization is coupled to the reactor design itself because with improved data the reactor concept can be re-optimized itself. It is thus desired to find the experiment that gives the best optimized reactor design. Methods are first established to model both the reactor concept and the experiment and to efficiently propagate the basic nuclear data uncertainty through these models to outputs. The representativity of the experiment to the design concept is quantitatively determined. A technique is then established to assimilate this data and produce posteriori uncertainties on key attributes and responses of the design concept. Several experiment perturbations based on engineering judgment are used to demonstrate these methods and also serve as an initial generation of the optimization problem. Finally, an optimization technique is developed which will simultaneously arrive at an optimized experiment to produce an optimized reactor design. Solution of this problem is made possible by the use of the simulated annealing algorithm for solution of optimization problems. The optimization examined in this work is based on maximizing the reactor cost savings associated with the modified design made possible by using the design margin gained through reduced basic nuclear data uncertainties. Cost values for experiment design specifications and reactor design specifications are established and used to compute a total savings by comparing the posteriori reactor cost to the a priori cost plus the cost of the experiment. The optimized solution arrives at a maximized cost savings.

Paul J. Turinsky; Hany S.Abdel-Khalik; Tracy E. Stover

2011-03-31T23:59:59.000Z

66

Error propagation and scaling for tropical forest biomass estimates  

Science Journals Connector (OSTI)

...propagation and scaling for tropical forest biomass estimates Jerome Chave 1 * Richard Condit...34002-0948, USA The above-ground biomass (AGB) of tropical forests is a crucial...inferences about long-term changes in biomass stocks, it is essential to know the uncertainty...

2004-01-01T23:59:59.000Z

67

A Stochastic Nonlinear Water Wave Model for Efficient Uncertainty Quantification  

E-Print Network [OSTI]

A major challenge in next-generation industrial applications is to improve numerical analysis by quantifying uncertainties in predictions. In this work we present a stochastic formulation of a fully nonlinear and dispersive potential flow water wave model for the probabilistic description of the evolution waves. This model is discretized using the Stochastic Collocation Method (SCM), which provides an approximate surrogate of the model. This can be used to accurately and efficiently estimate the probability distribution of the unknown time dependent stochastic solution after the forward propagation of uncertainties. We revisit experimental benchmarks often used for validation of deterministic water wave models. We do this using a fully nonlinear and dispersive model and show how uncertainty in the model input can influence the model output. Based on numerical experiments and assumed uncertainties in boundary data, our analysis reveals that some of the known discrepancies from deterministic simulation in compa...

Bigoni, Daniele; Eskilsson, Claes

2014-01-01T23:59:59.000Z

68

PROPAGATING WAVES ALONG SPICULES  

SciTech Connect (OSTI)

Alfvenic waves are thought to play an important role in coronal heating and acceleration of solar wind. Here we investigate the statistical properties of Alfvenic waves along spicules (jets that protrude into the corona) in a polar coronal hole using high-cadence observations of the Solar Optical Telescope on board Hinode. We developed a technique for the automated detection of spicules and high-frequency waves. We detected 89 spicules and found (1) a mix of upward propagating, downward propagating, as well as standing waves (occurrence rates of 59%, 21%, and 20%, respectively); (2) the phase speed gradually increases with height; (3) upward waves dominant at lower altitudes, standing waves at higher altitudes; (4) standing waves dominant in the early and late phases of each spicule, while upward waves were dominant in the middle phase; (5) in some spicules, we find waves propagating upward (from the bottom) and downward (from the top) to form a standing wave in the middle of the spicule; and (6) the medians of the amplitude, period, and velocity amplitude were 55 km, 45 s, and 7.4 km s{sup -1}, respectively. We speculate that upward propagating waves are produced near the solar surface (below the spicule) and downward propagating waves are caused by reflection of (initially) upward propagating waves off the transition region at the spicule top. The mix of upward and downward propagating waves implies that exploiting these waves to perform seismology of the spicular environment requires careful analysis and may be problematic.

Okamoto, Takenori J. [National Astronomical Observatory, 2-21-1 Osawa, Mitaka, Tokyo 181-8588 (Japan); De Pontieu, Bart, E-mail: joten.okamoto@nao.ac.jp [Lockheed Martin Solar and Astrophysics Laboratory, B/252, 3251 Hanover Street, Palo Alto, CA 94304 (United States)

2011-08-01T23:59:59.000Z

69

Expressing scientific uncertainty  

Science Journals Connector (OSTI)

......situations where the risk probabilities are not...proposition. Keywords: risk uncertainty; standards...sums of money and in political controversies with major...misdemeanors' is inherently a political process in which the...flight, minimizing the risk of harm to the officer......

Charles Weiss

2003-03-01T23:59:59.000Z

70

Action Under Uncertainty  

Science Journals Connector (OSTI)

......that agents actually plan by theorem proving...In Section 2, the standard dynamic logic account...properties desired in a plan are taken to be effectiveness...uncertainty 3.1 Review of epistemic logic...familiarity with the standard [3] representation...I assume that the plan constructors......

SAM STEEL

1994-10-01T23:59:59.000Z

71

Policy implications of uncertainty  

Science Journals Connector (OSTI)

...by T. N. Palmer and P. J. Hardaker Policy implications of uncertainty Chris Smith...to be enough for governments and public policy-makers to make sensible decisions about...difficult decisions with regard to public policy over the course of the next 20 or 30 years...

2011-01-01T23:59:59.000Z

72

Refinery Planning under Uncertainty  

Science Journals Connector (OSTI)

The planning/scheduling of the supply chain under uncertainty is important in light of the ever-changing market conditions. ... Examples of the open-shop mode, such as the news vendor model26 in which the sales of holiday lights disappear after Christmas, for instance, can be found in the real world. ...

Wenkai Li; Chi-Wai Hui; Pu Li; An-Xue Li

2004-09-10T23:59:59.000Z

73

Communicating scientific uncertainty  

Science Journals Connector (OSTI)

...affect your preferred energy portfolio...approach asks experts to audit existing studies for...Conveying Uncertainty. An audit like that in Fig...them. For example, energy models often neglect social factors (e...electricity pilot studies . Energy Policy 62 : 401 – 409...

Baruch Fischhoff; Alex L. Davis

2014-01-01T23:59:59.000Z

74

A new uncertainty principle  

E-Print Network [OSTI]

By examining two counterexamples to the existing theory, it is shown, with mathematical rigor, that as far as scattered particles are concerned the true distribution function is in principle not determinable (indeterminacy principle or uncertainty principle) while the average distribution function over each predetermined finite velocity solid-angle element can be calculated.

C. Y. Chen

2008-12-23T23:59:59.000Z

75

Uncertainty Quantification of Calculated Temperatures for the AGR-1 Experiment  

SciTech Connect (OSTI)

This report documents an effort to quantify the uncertainty of the calculated temperature data for the first Advanced Gas Reactor (AGR-1) fuel irradiation experiment conducted in the INL’s Advanced Test Reactor (ATR) in support of the Next Generation Nuclear Plant (NGNP) R&D program. Recognizing uncertainties inherent in physics and thermal simulations of the AGR-1 test, the results of the numerical simulations can be used in combination with the statistical analysis methods to improve qualification of measured data. Additionally, the temperature simulation data for AGR tests can be used for validation of the fuel transport and fuel performance simulation models. The crucial roles of the calculated fuel temperatures in ensuring achievement of the AGR experimental program objectives require accurate determination of the model temperature uncertainties. The report is organized into three chapters. Chapter 1 introduces the AGR Fuel Development and Qualification program and provides overviews of AGR-1 measured data, AGR-1 test configuration and test procedure, and thermal simulation. Chapters 2 describes the uncertainty quantification procedure for temperature simulation data of the AGR-1 experiment, namely, (i) identify and quantify uncertainty sources; (ii) perform sensitivity analysis for several thermal test conditions; (iii) use uncertainty propagation to quantify overall response temperature uncertainty. A set of issues associated with modeling uncertainties resulting from the expert assessments are identified. This also includes the experimental design to estimate the main effects and interactions of the important thermal model parameters. Chapter 3 presents the overall uncertainty results for the six AGR-1 capsules. This includes uncertainties for the daily volume-average and peak fuel temperatures, daily average temperatures at TC locations, and time-average volume-average and time-average peak fuel temperatures.

Binh T. Pham; Jeffrey J. Einerson; Grant L. Hawkes

2013-03-01T23:59:59.000Z

76

Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment, main report  

SciTech Connect (OSTI)

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the risks presented by nuclear installations based on postulated frequencies and magnitudes of potential accidents. In 1991, the US Nuclear Regulatory Commission (NRC) and the Commission of the European Communities (CEC) began a joint uncertainty analysis of the two codes. The ultimate objective of the joint effort was to develop credible and traceable uncertainty distributions for the input variables of the codes. Expert elicitation was identified as the best technology available for developing a library of uncertainty distributions for the selected consequence parameters. The study was formulated jointly and was limited to the current code models and to physical quantities that could be measured in experiments. Experts developed their distributions independently. To validate the distributions generated for the wet deposition input variables, samples were taken from these distributions and propagated through the wet deposition code model. Resulting distributions closely replicated the aggregated elicited wet deposition distributions. To validate the distributions generated for the dispersion code input variables, samples from the distributions and propagated through the Gaussian plume model (GPM) implemented in the MACCS and COSYMA codes. Project teams from the NRC and CEC cooperated successfully to develop and implement a unified process for the elaboration of uncertainty distributions on consequence code input parameters. Formal expert judgment elicitation proved valuable for synthesizing the best available information. Distributions on measurable atmospheric dispersion and deposition parameters were successfully elicited from experts involved in the many phenomenological areas of consequence analysis. This volume is the first of a three-volume document describing the project.

Harper, F.T.; Young, M.L.; Miller, L.A. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States); Lui, C.H. [Nuclear Regulatory Commission, Washington, DC (United States); Goossens, L.H.J.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Paesler-Sauer, J. [Research Center, Karlsruhe (Germany); Helton, J.C. [and others

1995-01-01T23:59:59.000Z

77

Essays on uncertainty in economics  

E-Print Network [OSTI]

This thesis consists of four essays about "uncertainty" and how markets deal with it. Uncertainty is about subjective beliefs, and thus it often comes with heterogeneous beliefs that may be present temporarily or even ...

Simsek, Alp

2010-01-01T23:59:59.000Z

78

Cognitive neuroscience: Decision amid uncertainty  

Science Journals Connector (OSTI)

... their task, the less-than-perfect reliability of a cue) and unexpected uncertainty (a surreptitious switch in the relevant cue). They propose that information about these forms of uncertainty ...

Jonathan D. Cohen; Gary Aston-Jones

2005-07-27T23:59:59.000Z

79

Quantification of uncertainty during history matching  

E-Print Network [OSTI]

technology requirements and possibly marginal investment indicators. Our method of quantifying uncertainty uses a set of history-match runs and includes a method to determine the probability density function (pdf) of future oil production (reserves... side)?????. 29 3.16 Marginal cumulative oil production correlates well with total error?.. 32 ix FIGURE Page 3.17 Weighted standard deviation is smaller than non weighted?..?..?? 37 3.18 Shows sets of weighted and non weighted mean...

Alvarado, Martin Guillermo

2004-09-30T23:59:59.000Z

80

Electoral Competition, Political Uncertainty and Policy Insulation  

E-Print Network [OSTI]

Uncertainty and Policy Insulation Horn, Murray. 1995. TheUncertainty and Policy Insulation United States Congress.UNCERTAINTY AND POLICY INSULATION Rui J. P. de Figueiredo,

de Figueiredo, Rui J. P. Jr.

2001-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Elevated temperature crack propagation  

SciTech Connect (OSTI)

This paper is a summary of two NASA contracts on high temperature fatigue crack propagation in metals. The first evaluated the ability of fairly simple nonlinear fracture parameters to correlate crack propagation. Hastelloy-X specimens were tested under isothermal and thermomechanical cycling at temperatures up to 980 degrees C (1800 degrees F). The most successful correlating parameter was the crack tip opening displacement derived from the J-integral. The second evaluated the ability of several path-independent integrals to correlate crack propagation behavior. Inconel 718 specimens were tested under isothermal, thermomechanical, temperature gradient, and creep conditions at temperatures up to 650 degrees C (1200 degrees F). The integrals formulated by Blackburn and by Kishimoto correlated the data reasonably well under all test conditions.

Orange, T.W.

1994-02-01T23:59:59.000Z

82

Unquenching the gluon propagator with Schwinger-Dyson equations  

Science Journals Connector (OSTI)

In this article we use the Schwinger–Dyson equations to compute the nonperturbative modifications caused to the infrared finite gluon propagator (in the Landau gauge) by the inclusion of a small number of quark families. Our basic operating assumption is that the main bulk of the effect stems from the “one-loop dressed” quark loop contributing to the full gluon self-energy. This quark loop is then calculated, using as basic ingredients the full quark propagator and quark-gluon vertex; for the quark propagator we use the solution obtained from the quark-gap equation, while for the vertex we employ suitable Ansätze, which guarantee the transversality of the answer. The resulting effect is included as a correction to the quenched gluon propagator, obtained in recent lattice simulations. Our main finding is that the unquenched propagator displays a considerable suppression in the intermediate momentum region, which becomes more pronounced as we increase the number of active quark families. The influence of the quarks on the saturation point of the propagator cannot be reliably computed within the present scheme; the general tendency appears to be to decrease it, suggesting a corresponding increase in the effective gluon mass. The renormalization properties of our results, and the uncertainties induced by the unspecified transverse part of the quark-gluon vertex, are discussed. Finally, the gluon propagator is compared with the available unquenched lattice data, showing rather good agreement.

A. C. Aguilar; D. Binosi; J. Papavassiliou

2012-07-27T23:59:59.000Z

83

Propagation of Ornamental Plants.  

E-Print Network [OSTI]

is well filled with roots. In the other types of layering, select shooi 1 of young growth that bend easily. It usuall: is advisable to wound the stem where it is covered with soil. This cut limits free movemen: ! of food materials and induces root... cuttings. lecent research findings have taken much of uesswork out of this type of propagation t now can be done for many plants with rlrative ease by the home gardener. Some alants remain difficult to propagate by any ' method, but most...

DeWerth, A. F.

1955-01-01T23:59:59.000Z

84

Deconvolution of variability and uncertainty in the Cassini safety analysis  

SciTech Connect (OSTI)

The standard method for propagation of uncertainty in a risk analysis requires rerunning the risk calculation numerous times with model parameters chosen from their uncertainty distributions. This was not practical for the Cassini nuclear safety analysis, due to the computationally intense nature of the risk calculation. A less computationally intense procedure was developed which requires only two calculations for each accident case. The first of these is the standard {open_quotes}best-estimate{close_quotes} calculation. In the second calculation, variables and parameters change simultaneously. The mathematical technique of deconvolution is then used to separate out an uncertainty multiplier distribution, which can be used to calculate distribution functions at various levels of confidence. {copyright} {ital 1998 American Institute of Physics.}

Kampas, F.J. [Lockheed Martin Missiles and Space, P.O. Box 8555, Philadelphia, Pennsylvania 19101 (United States); Loughin, S. [WAM Systems, 650 Loraine Street, Ardmore, Pennsylvania 19003 (United States)

1998-01-01T23:59:59.000Z

85

IPA Phase 2 sensitivity and uncertainty analysis  

SciTech Connect (OSTI)

The NRC`s Phase 2 Iterative Performance Assessment (IPA) used Monte Carlo techniques to propagate uncertainty for up to 297 independent variables and nine scenarios through computer models representing the performance of the Yucca Mountain repository. The NRC staff explored the use of a number of parametric and non-parametric tests and graphical methods to display the probabilistic results. Parametric tests included regression and differential analysis. Non-parametric tests included the Kolmogorov-Smirnov test and Sign test. Graphical methods included the Complementary Cumulative Distribution Function (CCDF), hair diagram, scatter plots, histograms and box plots. Multiple linear regression of raw, ranked, standardized and other transformed variables determined the gross sensitivity over the parameter space. CCDF`s were also generated from subsets of the 400 vector sets formed by screening the vectors according to values of derived variables related to the behavior of the engineered and natural systems. While no single statistical or graphical technique proved to be useful in all cases, diverse methods of sensitivity and uncertainty analysis identified the same important input parameters.

Colten-Bradley, V.; Codell, R.; Byrne, M.R. [Nuclear Regulatory Commission, Washington, DC (United States)

1994-12-31T23:59:59.000Z

86

Barge Truck Total  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Barge Truck Total delivered cost per short ton Shipments with transportation rates over total shipments Total delivered cost per short ton Shipments with transportation rates over...

87

Propagators in Lagrangian space  

SciTech Connect (OSTI)

It has been found recently that propagators, e.g. the cross correlation spectra of the cosmic fields with the initial density field, decay exponentially at large k in an Eulerian description of the dynamics. We explore here similar quantities defined for a Lagrangian space description. We find that propagators in Lagrangian space do not exhibit the same properties: they are found not to be monotonic functions of time, and to track back the linear growth rate at late time (but with a renormalized amplitude). These results have been obtained with a novel method which we describe alongside. It allows the formal resummation of the same set of diagrams as those that led to the known results in Eulerian space. We provide a tentative explanation for the marked differences seen between the Eulerian and the Lagrangian cases, and we point out the role played by the vorticity degrees of freedom that are specific to the Lagrangian formalism. This provides us with new insights into the late-time behavior of the propagators.

Bernardeau, Francis; Valageas, Patrick [Institut de Physique Theorique, CEA/DSM/IPhT, Unite de recherche associee au CNRS, CEA/Saclay, 91191 Gif-sur-Yvette cedex, France and Canadian Institute for Theoretical Astrophysics, University of Toronto, 60 St. George Street, Toronto, Ontario M5S 3H8 (Canada); Service de Physique Theorique, CEA/DSM/SPhT, Unite de recherche associee au CNRS, CEA/Saclay, 91191 Gif-sur-Yvette cedex (France)

2008-10-15T23:59:59.000Z

88

Uncertainty Analysis of the Adequacy Assessment Model of a Distributed Generation System  

E-Print Network [OSTI]

of evidence theory, the hybrid propagation approach is introduced. A demonstration is given on a DG system enables end-users to install renewable generators (e.g. solar generators and wind turbines) on1 Uncertainty Analysis of the Adequacy Assessment Model of a Distributed Generation System Yanfu Li

Paris-Sud XI, Université de

89

1 INTRODUCTION Uncertainty analysis is a fundamental part of the risk  

E-Print Network [OSTI]

- precision due to lack of knowledge and information on the system. The former type of uncertainty is of- ten. In Section 2, some basic concepts about possi- bility theory are summarized; in Section 3, the de- tails about the integrated propagation framework are given; in Section 4, approaches for constructing pos

Paris-Sud XI, Université de

90

Uncertainty in emissions projections for climate models  

E-Print Network [OSTI]

Future global climate projections are subject to large uncertainties. Major sources of this uncertainty are projections of anthropogenic emissions. We evaluate the uncertainty in future anthropogenic emissions using a ...

Webster, Mort David.; Babiker, Mustafa H.M.; Mayer, Monika.; Reilly, John M.; Harnisch, Jochen.; Hyman, Robert C.; Sarofim, Marcus C.; Wang, Chien.

91

The Low energy structure of the Nucleon-Nucleon interaction: Statistical vs Systematic Uncertainties  

E-Print Network [OSTI]

We analyze the low energy NN interaction by extracting threshold parameters uncertainties from the coupled channel effective range expansion up to j $\\leq$ 5. This is based on the Granada-2013 database where a statistically meaningful partial wave analysis comprising a total of 6713 np and pp published scattering data from 1950 till 2013 below pion production threshold has been made. We find that for threshold parameters systematic uncertainties are generally at least an order of magnitude larger than statistical uncertainties.

R. Navarro Perez; J. E. Amaro; E. Ruiz Arriola

2014-12-12T23:59:59.000Z

92

Oil and Gas Production Optimization; Lost Potential due to Uncertainty  

E-Print Network [OSTI]

Oil and Gas Production Optimization; Lost Potential due to Uncertainty Steinar M. Elgsaeter Olav.ntnu.no) Abstract: The information content in measurements of offshore oil and gas production is often low, and when in the context of offshore oil and gas fields, can be considered the total output of production wells, a mass

Johansen, Tor Arne

93

Predicting System Performance with Uncertainty  

E-Print Network [OSTI]

inexpensive way. We propose using Gaussian Processes for system performance predictions and explain the types of uncertainties included. As an example, we use a Gaussian Process to predict chilled water use and compare the results with Neural Network...

Yan, B.; Malkawi, A.

2012-01-01T23:59:59.000Z

94

Political uncertainty and risk premia  

Science Journals Connector (OSTI)

Abstract We develop a general equilibrium model of government policy choice in which stock prices respond to political news. The model implies that political uncertainty commands a risk premium whose magnitude is larger in weaker economic conditions. Political uncertainty reduces the value of the implicit put protection that the government provides to the market. It also makes stocks more volatile and more correlated, especially when the economy is weak. We find empirical evidence consistent with these predictions.

?uboš Pástor; Pietro Veronesi

2013-01-01T23:59:59.000Z

95

Reducing Petroleum Despendence in California: Uncertainties About...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Petroleum Despendence in California: Uncertainties About Light-Duty Diesel Reducing Petroleum Despendence in California: Uncertainties About Light-Duty Diesel 2002 DEER Conference...

96

Uncertainty quantification for large-scale ocean circulation predictions.  

SciTech Connect (OSTI)

Uncertainty quantificatio in climate models is challenged by the sparsity of the available climate data due to the high computational cost of the model runs. Another feature that prevents classical uncertainty analyses from being easily applicable is the bifurcative behavior in the climate data with respect to certain parameters. A typical example is the Meridional Overturning Circulation in the Atlantic Ocean. The maximum overturning stream function exhibits discontinuity across a curve in the space of two uncertain parameters, namely climate sensitivity and CO{sub 2} forcing. We develop a methodology that performs uncertainty quantificatio in the presence of limited data that have discontinuous character. Our approach is two-fold. First we detect the discontinuity location with a Bayesian inference, thus obtaining a probabilistic representation of the discontinuity curve location in presence of arbitrarily distributed input parameter values. Furthermore, we developed a spectral approach that relies on Polynomial Chaos (PC) expansions on each sides of the discontinuity curve leading to an averaged-PC representation of the forward model that allows efficient uncertainty quantification and propagation. The methodology is tested on synthetic examples of discontinuous data with adjustable sharpness and structure.

Safta, Cosmin; Debusschere, Bert J.; Najm, Habib N.; Sargsyan, Khachik

2010-09-01T23:59:59.000Z

97

Winter Weather Uncertainty  

Gasoline and Diesel Fuel Update (EIA)

5 of 15 5 of 15 Notes: Heating Degree Days (HDDs): The "normal" numbers are the expected values for winter 2000-2001 used in EIA's Short-Term Energy Outlook. The chart indicates the extent to which last winter exhibited below-normal heating degree-days (and thus below-normal heating demand). Temperatures were consistently warmer than normal throughout the 1999-2000 heating season, despite the cold spell in the Northeast spanning January/February. This was particularly true in November 1999, February and March 2001. For the heating season as a whole (October through March), the 1999-2000 winter yielded total HDDs 10.7% below normal (less HDDs means warmer temperatures). Normal temperatures this coming winter would be expected to bring about 11% higher heating demand than we saw last year.

98

Total Cross Sections for Neutron Scattering  

E-Print Network [OSTI]

Measurements of neutron total cross-sections are both extensive and extremely accurate. Although they place a strong constraint on theoretically constructed models, there are relatively few comparisons of predictions with experiment. The total cross-sections for neutron scattering from $^{16}$O and $^{40}$Ca are calculated as a function of energy from $50-700$~MeV laboratory energy with a microscopic first order optical potential derived within the framework of the Watson expansion. Although these results are already in qualitative agreement with the data, the inclusion of medium corrections to the propagator is essential to correctly predict the energy dependence given by the experiment.

C. R. Chinn; Ch. Elster; R. M. Thaler; S. P. Weppner

1994-10-19T23:59:59.000Z

99

Variations of Total Domination  

Science Journals Connector (OSTI)

The study of locating–dominating sets in graphs was pioneered by Slater [186, 187...], and this concept was later extended to total domination in graphs. A locating–total dominating set, abbreviated LTD-set, in G

Michael A. Henning; Anders Yeo

2013-01-01T23:59:59.000Z

100

Experimental Uncertainties (Errors) Sources of Experimental Uncertainties (Experimental Errors)  

E-Print Network [OSTI]

the preparation of the lab report. A calculator should 1. Bevington, P. R., Data Reduction and Error Analysis for the Physical Sciences, New York: McGraw-Hill, 1969. 2. Taylor, J. R., An introduction to uncertainty analysis in the lab. In this laboratory, we keep to a very simple form of error analysis, our purpose being more

Mukasyan, Alexander

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Total Crude by Pipeline  

U.S. Energy Information Administration (EIA) Indexed Site

Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 2007 2008 2009 2010 2011 2012 View

102

Slanted-wall beam propagation.  

SciTech Connect (OSTI)

We present a new algorithm for wide-angle propagation through a general class of optical-waveguide structures defined by dielectric interfaces that may be slanted with respect to the direction of propagation. No regularity of the structure shapes is assumed, no coordinate transformations are employed, and the movement of each grid point between propagation steps is arbitrary within modest angular limitations. When used with an appropriate grid-generation algorithm, this method allows the modeling of an extremely wide variety of high-index-contrast waveguide structures, including meanders and tapers, with good phase accuracy and energy conservation.

Hadley, G. Ronald

2007-01-01T23:59:59.000Z

103

A novel belief function reasoning approach to MCDM under uncertainty  

Science Journals Connector (OSTI)

This paper presents a novel belief function reasoning approach to the multiple criteria decision-making problem under uncertainty. In contrast to exist approaches, which make decisions based on the expected utility values derived directly from the combined belief function distributions, we introduce an alternative two-level reasoning transferable belief model approach to the aggregation and decision-making phases. Within this framework, the analyst can combine the beliefs regarding various sub-criteria at the credal level, and calculate the expected utility values for decision making at the pignistic level based on real probability distributions. We also propose a measure of uncertainty to capture the degrees of total uncertainty involved in different belief assessments. This measure can assist the decision maker in making rational decisions based on incomplete information.

Yuliang Fan; Anne T.A. Nguyen

2011-01-01T23:59:59.000Z

104

Impact of orifice metering uncertainties  

SciTech Connect (OSTI)

In a recent utility study, attributed 38% of its unaccounted-for UAF gas to orifice metering uncertainty biasing caused by straightening vanes. How this was determined and how this applied to the company's orifice meters is described. Almost all (97%) of the company's UAF gas was found to be attributed to identifiable accounting procedures, measurement problems, theft and leakage.

Stuart, J.W. (Pacific Gas and Electric Co., San Francisco, CA (USA))

1990-12-01T23:59:59.000Z

105

Economic History Revisited: New Uncertainties  

E-Print Network [OSTI]

to the southern and midwestern regions of the United States. However, the large run-up in oil prices is increasingEconomic History Revisited: New Uncertainties I n the last Sitar-Rutgers Regional Report, we are paying ever-increasing prices for fewer available sites. Warehouse sites in the southern portion

106

Propagating buckles in corroded pipelines  

Science Journals Connector (OSTI)

Rigid–plastic solutions for the steady-state, quasi-static buckle propagation pressure in corroded pipelines are derived and compared to finite element predictions (ABAQUS). The corroded pipeline is modeled as an infinitely long, cylindrical shell with a section of reduced thickness that is used to describe the corrosion. A five plastic hinge mechanism is used to describe plastic collapse of the corroded pipeline. Closed-form expressions are given for the buckle propagation pressure as a function of the amount of corrosion in an X77 steel pipeline. Buckles that propagate down the pipeline are caused by either global or snap-through buckling, depending on the amount of corrosion. Global buckling occurs when the angular extent of the corrosion is greater than 90°. When the angular extent is less than 90° and the corrosion is severe, snap-through buckling takes place. The buckle propagation pressure and the corresponding collapse modes also compare well to finite element predictions.

Michelle S. Hoo Fatt; Jianghong Xue

2001-01-01T23:59:59.000Z

107

Fuel cycle cost uncertainty from nuclear fuel cycle comparison  

SciTech Connect (OSTI)

This paper examined the uncertainty in fuel cycle cost (FCC) calculation by considering both model and parameter uncertainty. Four different fuel cycle options were compared in the analysis including the once-through cycle (OT), the DUPIC cycle, the MOX cycle and a closed fuel cycle with fast reactors (FR). The model uncertainty was addressed by using three different FCC modeling approaches with and without the time value of money consideration. The relative ratios of FCC in comparison to OT did not change much by using different modeling approaches. This observation was consistent with the results of the sensitivity study for the discount rate. Two different sets of data with uncertainty range of unit costs were used to address the parameter uncertainty of the FCC calculation. The sensitivity study showed that the dominating contributor to the total variance of FCC is the uranium price. In general, the FCC of OT was found to be the lowest followed by FR, MOX, and DUPIC. But depending on the uranium price, the FR cycle was found to have lower FCC over OT. The reprocessing cost was also found to have a major impact on FCC.

Li, J.; McNelis, D. [Institute for the Environment, University of North Carolina, Chapel Hill (United States); Yim, M.S. [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology (Korea, Republic of)

2013-07-01T23:59:59.000Z

108

Total Space Heat-  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...

109

Optimal consumption strategies under model uncertainty  

E-Print Network [OSTI]

Optimal consumption strategies under model uncertainty Christian Burgert, Ludger R of finding optimal consumption strategies in an incomplete semimartingale market model under model uncertainty. The quality of a consumption strategy is measured by not only one probability measure

Rüschendorf, Ludger

110

The impact of uncertainty and risk measures  

E-Print Network [OSTI]

xi Chapter 1 The Effects of Oil Price Uncertainty on theLIST OF FIGURES Figure Figure Figure Figure Figure Oil priceOil price uncertainty with and without realized

Jo, Soojin; Jo, Soojin

2012-01-01T23:59:59.000Z

111

The impact of uncertainty and risk measures  

E-Print Network [OSTI]

Evidence from TEXAS oil drilling. NBER Working Paper,uncertainty using Texas oil well drilling data and expecta-

Jo, Soojin; Jo, Soojin

2012-01-01T23:59:59.000Z

112

Applying Calibration to Improve Uncertainty Assessment  

E-Print Network [OSTI]

. INTRODUCTION AND BACKGROUND 1.1 Introduction The oil and gas industry is full of uncertainty. In addition to significant subsurface uncertainty and uncertainty in oil and gas prices, there are other risks, e.g., political, that contribute to uncertainty... that is commonly applied in other industries for assessing forecasts and was initially developed to assess weather forecasts (Brier, 1950). Lichtenstein and Fischhoff (1977) summarized the background for the 3 Brier score and its components. The Brier score...

Fondren, Mark Edward

2013-08-02T23:59:59.000Z

113

Patent Protection, Market Uncertainty, and R&D Investment  

E-Print Network [OSTI]

Uncertainty, and Investment,” Journal of EconomicOptions, Irreversible Investment and Firm Uncertainty: NewWhat do we know about investment under uncertainty? ”

Toole, Andrew A; Czarnitzki, Dirk

2006-01-01T23:59:59.000Z

114

The Propagation of Ornamental Plants.  

E-Print Network [OSTI]

of the 8-inch pot and pack the rooting medium in between the two pots. Note: If vermiculite is used, fill this space, but do not pack it. Water the medium in well with water containing a few drops of a wetting agent. Then stick cuttings in concentric... ready for planting in permanent location. Materials required for self-watering propagator. Make the cutting. Preparation of self-watering propagator. Insert cutting into rooting medium. :?-de+d self-watering -.:sqgotor filled with cuttings...

DeWerth, A. F.

1970-01-01T23:59:59.000Z

115

Risk uncertainty analysis methods for NUREG-1150  

SciTech Connect (OSTI)

Evaluation and display of risk uncertainties for NUREG-1150 constitute a principal focus of the Severe Accident Risk Rebaselining/Risk Reduction Program (SARRP). Some of the principal objectives of the uncertainty evaluation are: (1) to provide a quantitative estimate that reflects, for those areas considered, a credible and realistic range of uncertainty in risk; (2) to rank the various sources of uncertainty with respect to their importance for various measures of risk; and (3) to characterize the state of understanding of each aspect of the risk assessment for which major uncertainties exist. This paper describes the methods developed to fulfill these objectives.

Benjamin, U.S.; Boyd, G.J.

1986-01-01T23:59:59.000Z

116

Quantifying galactic propagation uncertainty in WIMP dark matter search with AMS01 Z=-1 spectrum  

E-Print Network [OSTI]

A search for a WIMP dark matter annihilation signal is carried out in the AMS01 negatively charged (Z=-I) particle spectrum, following a set of supersymmetric benchmark scenarios in the mSUGRA framework. The result is ...

Xiao, Sa, Ph. D. Massachusetts Institute of Technology

2009-01-01T23:59:59.000Z

117

How to Describe and Propagate Uncertainty When Processing Time Series: Metrological and  

E-Print Network [OSTI]

, Aline Jaimes, Craig Tweedie, and Vladik Kreinovich Abstract Time series comes from measurements, and measurements are never abso- lutely accurate. Traditionally, when we deal with an individual measurement or with a sample of measurement results, we subdivide a measurement error into random and systematic components

Ward, Karen

118

A reduced-basis method for input-output uncertainty propagation in stochastic PDEs  

E-Print Network [OSTI]

Recently there has been a growing interest in quantifying the effects of random inputs in the solution of partial differential equations that arise in a number of areas, including fluid mechanics, elasticity, and wave ...

Vidal Codina, Ferran

2013-01-01T23:59:59.000Z

119

A framework for optimization and quantification of uncertainty and sensitivity for developing carbon capture systems  

SciTech Connect (OSTI)

Under the auspices of the U.S. Department of Energy’s Carbon Capture Simulation Initiative (CCSI), a Framework for Optimization and Quantification of Uncertainty and Sensitivity (FOQUS) has been developed. This tool enables carbon capture systems to be rapidly synthesized and rigorously optimized, in an environment that accounts for and propagates uncertainties in parameters and models. FOQUS currently enables (1) the development of surrogate algebraic models utilizing the ALAMO algorithm, which can be used for superstructure optimization to identify optimal process configurations, (2) simulation-based optimization utilizing derivative free optimization (DFO) algorithms with detailed black-box process models, and (3) rigorous uncertainty quantification through PSUADE. FOQUS utilizes another CCSI technology, the Turbine Science Gateway, to manage the thousands of simulated runs necessary for optimization and UQ. This computational framework has been demonstrated for the design and analysis of a solid sorbent based carbon capture system.

John C Eslick, John C; Ng, Brenda Ng; Gao, Qianwen; Tong, Charles H.; Sahinidis, Nikolaos V.; Miller, David C.

2014-01-01T23:59:59.000Z

120

Inverse Sensitivity/Uncertainty Methods Development for Nuclear Fuel Cycle Applications  

Science Journals Connector (OSTI)

Abstract The Standardized Computer Analyses for Licensing Evaluation (SCALE) software package developed at the Oak Ridge National Laboratory includes codes that propagate uncertainties available in the nuclear data libraries to compute uncertainties in nuclear application performance parameters. We report on our recent efforts to extend this capability to develop an inverse sensitivity/uncertainty (IS/U) methodology that identifies the improvements in nuclear data that are needed to compute application responses within prescribed tolerances, while minimizing the cost of such data improvements. We report on our progress to date and present a simple test case for our method. Our methodology is directly applicable to thermal and intermediate neutron energy systems because it addresses the implicit neutron resonance self-shielding effects that are essential to accurate modeling of thermal and intermediate systems. This methodology is likely to increase the efficiency of nuclear data efforts.

G. Arbanas; M.E. Dunn; M.L. Williams

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Survey of sampling-based methods for uncertainty and sensitivity analysis.  

SciTech Connect (OSTI)

Sampling-based methods for uncertainty and sensitivity analysis are reviewed. The following topics are considered: (1) Definition of probability distributions to characterize epistemic uncertainty in analysis inputs, (2) Generation of samples from uncertain analysis inputs, (3) Propagation of sampled inputs through an analysis, (4) Presentation of uncertainty analysis results, and (5) Determination of sensitivity analysis results. Special attention is given to the determination of sensitivity analysis results, with brief descriptions and illustrations given for the following procedures/techniques: examination of scatterplots, correlation analysis, regression analysis, partial correlation analysis, rank transformations, statistical tests for patterns based on gridding, entropy tests for patterns based on gridding, nonparametric regression analysis, squared rank differences/rank correlation coefficient test, two dimensional Kolmogorov-Smirnov test, tests for patterns based on distance measures, top down coefficient of concordance, and variance decomposition.

Johnson, Jay Dean; Helton, Jon Craig; Sallaberry, Cedric J. PhD. (.; .); Storlie, Curt B. (Colorado State University, Fort Collins, CO)

2006-06-01T23:59:59.000Z

122

21 briefing pages total  

Broader source: Energy.gov (indexed) [DOE]

briefing pages total p. 1 briefing pages total p. 1 Reservist Differential Briefing U.S. Office of Personnel Management December 11, 2009 p. 2 Agenda - Introduction of Speakers - Background - References/Tools - Overview of Reservist Differential Authority - Qualifying Active Duty Service and Military Orders - Understanding Military Leave and Earnings Statements p. 3 Background 5 U.S.C. 5538 (Section 751 of the Omnibus Appropriations Act, 2009, March 11, 2009) (Public Law 111-8) Law requires OPM to consult with DOD Law effective first day of first pay period on or after March 11, 2009 (March 15 for most executive branch employees) Number of affected employees unclear p. 4 Next Steps

123

Barge Truck Total  

U.S. Energy Information Administration (EIA) Indexed Site

Barge Barge Truck Total delivered cost per short ton Shipments with transportation rates over total shipments Total delivered cost per short ton Shipments with transportation rates over total shipments Year (nominal) (real) (real) (percent) (nominal) (real) (real) (percent) 2008 $6.26 $5.77 $36.50 15.8% 42.3% $6.12 $5.64 $36.36 15.5% 22.2% 2009 $6.23 $5.67 $52.71 10.8% 94.8% $4.90 $4.46 $33.18 13.5% 25.1% 2010 $6.41 $5.77 $50.83 11.4% 96.8% $6.20 $5.59 $36.26 15.4% 38.9% Annual Percent Change First to Last Year 1.2% 0.0% 18.0% - - 0.7% -0.4% -0.1% - - Latest 2 Years 2.9% 1.7% -3.6% - - 26.6% 25.2% 9.3% - - - = No data reported or value not applicable STB Data Source: The Surface Transportation Board's 900-Byte Carload Waybill Sample EIA Data Source: Form EIA-923 Power Plant Operations Report

124

Summary Max Total Units  

Broader source: Energy.gov (indexed) [DOE]

Max Total Units Max Total Units *If All Splits, No Rack Units **If Only FW, AC Splits 1000 52 28 28 2000 87 59 35 3000 61 33 15 4000 61 33 15 Totals 261 153 93 ***Costs $1,957,500.00 $1,147,500.00 $697,500.00 Notes: added several refrigerants removed bins from analysis removed R-22 from list 1000lb, no Glycol, CO2 or ammonia Seawater R-404A only * includes seawater units ** no seawater units included *** Costs = (total units) X (estimate of $7500 per unit) 1000lb, air cooled split systems, fresh water Refrig Voltage Cond Unit IF-CU Combos 2 4 5 28 References Refrig Voltage C-U type Compressor HP R-404A 208/1/60 Hermetic SA 2.5 R-507 230/1/60 Hermetic MA 2.5 208/3/60 SemiHerm SA 1.5 230/3/60 SemiHerm MA 1.5 SemiHerm HA 1.5 1000lb, remote rack systems, fresh water Refrig/system Voltage Combos 12 2 24 References Refrig/system Voltage IF only

125

Total Precipitable Water  

SciTech Connect (OSTI)

The simulation was performed on 64K cores of Intrepid, running at 0.25 simulated-years-per-day and taking 25 million core-hours. This is the first simulation using both the CAM5 physics and the highly scalable spectral element dynamical core. The animation of Total Precipitable Water clearly shows hurricanes developing in the Atlantic and Pacific.

None

2012-01-01T23:59:59.000Z

126

Total Sustainability Humber College  

E-Print Network [OSTI]

1 Total Sustainability Management Humber College November, 2012 SUSTAINABILITY SYMPOSIUM Green An Impending Global Disaster #12;3 Sustainability is NOT Climate Remediation #12;Our Premises "We cannot, you cannot improve it" (Lord Kelvin) "First rule of sustainability is to align with natural forces

Thompson, Michael

127

Generating propagators for finite set constraints  

Science Journals Connector (OSTI)

Ideally, programming propagators as implementations of constraints should be an entirely declarative specification process for a large class of constraints: a high-level declarative specification is automatically translated into an efficient propagator. ...

Guido Tack; Christian Schulte; Gert Smolka

2006-09-01T23:59:59.000Z

128

Nonlinear Saturation of Vertically Propagating Rossby Waves  

E-Print Network [OSTI]

The interaction between vertical Rossby wave propagation and wave breaking is studied in the idealized context of a beta-plane channel model. Considering the problem of propagation through a uniform zonal flow in an ...

Giannitsis, Constantine

129

ARM - PI Product - Direct Aerosol Forcing Uncertainty  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ProductsDirect Aerosol Forcing Uncertainty ProductsDirect Aerosol Forcing Uncertainty Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Direct Aerosol Forcing Uncertainty Site(s) NSA SGP TWP General Description Understanding sources of uncertainty in aerosol direct radiative forcing (DRF), the difference in a given radiative flux component with and without aerosol, is essential to quantifying changes in Earth's radiation budget. We examine the uncertainty in DRF due to measurement uncertainty in the quantities on which it depends: aerosol optical depth, single scattering albedo, asymmetry parameter, solar geometry, and surface albedo. Direct radiative forcing at the top of the atmosphere and at the surface as well as sensitivities, the changes in DRF in response to unit changes in

130

Incorporating Forecast Uncertainty in Utility Control Center  

SciTech Connect (OSTI)

Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)

Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian

2014-07-09T23:59:59.000Z

131

Stochastic Programming of Vehicle to Building Interactions with Uncertainty  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Stochastic Programming of Vehicle to Building Interactions with Uncertainty Stochastic Programming of Vehicle to Building Interactions with Uncertainty in PEVs Driving for a Medium Office Building Title Stochastic Programming of Vehicle to Building Interactions with Uncertainty in PEVs Driving for a Medium Office Building Publication Type Conference Paper LBNL Report Number LBNL-6416E Year of Publication 2013 Authors Cardoso, Gonçalo, Michael Stadler, Mohammad Bozchalui, Ratnesh Sharma, Chris Marnay, Ana Barbosa-Póvoa, and Paulo Ferrão Conference Name 39th Annual Conference of the IEEE Industrial Electronics Society Date Published 10/2013 Conference Location Vienna, Austria Abstract The large scale penetration of electric vehicles (EVs) will introduce technical challenges to the distribution grid, but also carries the potential for vehicle-to-grid services. Namely, if available in large enough numbers, EVs can be used as a distributed energy resource (DER) and their presence can influence optimal DER investment and scheduling decisions in microgrids. In this work, a novel EV fleet aggregator model is introduced in a stochastic formulation of DER-CAM, an optimization tool used to address DER investment and scheduling problems. This is used to assess the impact of EV interconnections on optimal DER solutions considering uncertainty in EV driving schedules. Optimization results indicate that EVs can have a significant impact on DER investments, particularly if considering short payback periods. Furthermore, results suggest that uncertainty in driving schedules carries little significance to total energy costs, which is corroborated by results obtained with the stochastic formulation of the problem.

132

Stochastic model of MHF propagation  

SciTech Connect (OSTI)

A Monte Carlo model of the propagation of a hydraulic fracture through an inhomogeneous medium was constructed for use in the Western Gas Sands Project. The region through which the two-dimensional fracture propagates has a random variation of minimum in situ stress imposed upon it. By dividing the fracture into a number of sectors, the stress-intensity factor of each sector tip is calculated and compared with the fracture toughness at that point. The model produces an irregular fracture profile and fluctuations in the bottomhole fluid pressure. The irregularity in the profile is quite marked for the case of a stress distribution with mean 5000 psi and standard deviation 100 psi imposed randomly on a grid of resolution 40 feet. Many Monte Carlo trials will lead to a statistical probability of achieving a certain fracture radius (or wing length) and provide a relation between magnitude of pressure fluctuations and variations of minimum in situ stress.

Palmer, I.D.; Carroll, H.B. Jr.

1980-06-01T23:59:59.000Z

133

Atmospheric propagation of THz radiation.  

SciTech Connect (OSTI)

In this investigation, we conduct a literature study of the best experimental and theoretical data available for thin and thick atmospheres on THz radiation propagation from 0.1 to 10 THz. We determined that for thick atmospheres no data exists beyond 450 GHz. For thin atmospheres data exists from 0.35 to 1.2 THz. We were successful in using FASE code with the HITRAN database to simulate the THz transmission spectrum for Mauna Kea from 0.1 to 2 THz. Lastly, we successfully measured the THz transmission spectra of laboratory atmospheres at relative humidities of 18 and 27%. In general, we found that an increase in the water content of the atmosphere led to a decrease in the THz transmission. We identified two potential windows in an Albuquerque atmosphere for THz propagation which were the regions from 1.2 to 1.4 THz and 1.4 to 1.6 THz.

Wanke, Michael Clement; Mangan, Michael A.; Foltynowicz, Robert J.

2005-11-01T23:59:59.000Z

134

Research yields precise uncertainty equations  

SciTech Connect (OSTI)

Results of a study of orifice-meter accuracy by Chevron Oil Field Research Co. at its Venice, La., calibration facility have important implications for natural gas custody-transfer measurement. The calibration facility, data collection, and equipment calibration were described elsewhere. This article explains the derivation of uncertainty factors and details the study's findings. The results were based on calibration of two 16-in. orifice-meter runs. The experimental data cover a beta-ratio range of from 0.27 to 0.71 and a Reynolds number range of from 4,000,000 to 35,000,000. Discharge coefficients were determined by comparing the orifice flow to the flow from critical-flow nozzles.

Jones, E.H.; Ferguson, K.R.

1987-08-03T23:59:59.000Z

135

The impact of uncertainty and risk measures  

E-Print Network [OSTI]

peak, and finds that this nonlinear transformation of the oiland oil price growth rates. As seen in the above illustration, uncertainty is at its peak

Jo, Soojin; Jo, Soojin

2012-01-01T23:59:59.000Z

136

The Retail Planning Problem under Demand Uncertainty.  

E-Print Network [OSTI]

and Rajaram K. , (2000), “Accurate Retail Testing of FashionThe Retail Planning Problem Under Demand Uncertainty GeorgeAbstract We consider the Retail Planning Problem in which

Georgiadis, G.; Rajaram, K.

2012-01-01T23:59:59.000Z

137

Uncertainty analysis of geothermal energy economics.  

E-Print Network [OSTI]

?? This dissertation research endeavors to explore geothermal energy economics by assessing and quantifying the uncertainties associated with the nature of geothermal energy and energy… (more)

Sener, Adil Caner

2009-01-01T23:59:59.000Z

138

Harvesting a renewable resource under uncertainty  

E-Print Network [OSTI]

is pervasive for renewable resources, and it can play aConsider a valuable renewable resource whose biomass X2003. “Harvesting a renewable resource under uncertainty,”

Saphores, Jean-Daniel M

2003-01-01T23:59:59.000Z

139

Uncertainty Quantification Techniques for Sensor Calibration...  

Office of Scientific and Technical Information (OSTI)

Uncertainty Quantification Techniques for Sensor Calibration Monitoring in Nuclear Power Plants Re-direct Destination: Temp Data Fields Ramuhalli, Pradeep; Lin, Guang; Crawford,...

140

Total isomerization gains flexibility  

SciTech Connect (OSTI)

Isomerization extends refinery flexibility to meet changing markets. TIP (Total Isomerization Process) allows conversion of paraffin fractions in the gasoline boiling region including straight run naptha, light reformate, aromatic unit raffinate, and hydrocrackate. The hysomer isomerization is compared to catalytic reforming. Isomerization routes are graphed. Cost estimates and suggestions on the use of other feedstocks are given. TIP can maximize gas production, reduce crude runs, and complement cat reforming. In four examples, TIP reduces reformer severity and increases reformer yield.

Symoniak, M.F.; Holcombe, T.C.

1983-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Inflation uncertainty, growth uncertainty, oil prices, and output growth in the UK  

Science Journals Connector (OSTI)

This study examines the transmission and response of inflation uncertainty and output uncertainty on inflation and output growth in the UK using a bi-variate EGARCH model. Results suggest that inflation uncertain...

Ramprasad Bhar; Girijasankar Mallik

2013-12-01T23:59:59.000Z

142

Uncertainty in Contaminant Concentration Fields Resulting from Atmospheric Boundary Layer Depth Uncertainty  

Science Journals Connector (OSTI)

The relationship between atmospheric boundary layer (ABL) depth uncertainty and uncertainty in atmospheric transport and dispersion (ATD) simulations is investigated by examining profiles of predicted concentrations of a contaminant. Because ...

Brian P. Reen; Kerrie J. Schmehl; George S. Young; Jared A. Lee; Sue Ellen Haupt; David R. Stauffer

2014-11-01T23:59:59.000Z

143

A stochastic approach to estimate the uncertainty of dose mapping caused by uncertainties in b-spline registration  

SciTech Connect (OSTI)

Purpose: In fractionated radiation therapy, image guidance with daily tomographic imaging becomes more and more clinical routine. In principle, this allows for daily computation of the delivered dose and for accumulation of these daily dose distributions to determine the actually delivered total dose to the patient. However, uncertainties in the mapping of the images can translate into errors of the accumulated total dose, depending on the dose gradient. In this work, an approach to estimate the uncertainty of mapping between medical images is proposed that identifies areas bearing a significant risk of inaccurate dose accumulation. Methods: This method accounts for the geometric uncertainty of image registration and the heterogeneity of the dose distribution, which is to be mapped. Its performance is demonstrated in context of dose mapping based on b-spline registration. It is based on evaluation of the sensitivity of dose mapping to variations of the b-spline coefficients combined with evaluation of the sensitivity of the registration metric with respect to the variations of the coefficients. It was evaluated based on patient data that was deformed based on a breathing model, where the ground truth of the deformation, and hence the actual true dose mapping error, is known. Results: The proposed approach has the potential to distinguish areas of the image where dose mapping is likely to be accurate from other areas of the same image, where a larger uncertainty must be expected. Conclusions: An approach to identify areas where dose mapping is likely to be inaccurate was developed and implemented. This method was tested for dose mapping, but it may be applied in context of other mapping tasks as well.

Hub, Martina; Thieke, Christian; Kessler, Marc L.; Karger, Christian P. [Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg (Germany); Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany and Department of Radiation Oncology, University Clinic Heidelberg, 69120 Heidelberg (Germany); Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan 48109 (United States); Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg (Germany)

2012-04-15T23:59:59.000Z

144

A High-Performance Embedded Hybrid Methodology for Uncertainty Quantification With Applications  

SciTech Connect (OSTI)

Multiphysics processes modeled by a system of unsteady di#11;erential equations are natu- rally suited for partitioned (modular) solution strategies. We consider such a model where probabilistic uncertainties are present in each module of the system and represented as a set of random input parameters. A straightforward approach in quantifying uncertainties in the predicted solution would be to sample all the input parameters into a single set, and treat the full system as a black-box. Although this method is easily parallelizable and requires minimal modi#12;cations to deterministic solver, it is blind to the modular structure of the underlying multiphysical model. On the other hand, using spectral representations polynomial chaos expansions (PCE) can provide richer structural information regarding the dynamics of these uncertainties as they propagate from the inputs to the predicted output, but can be prohibitively expensive to implement in the high-dimensional global space of un- certain parameters. Therefore, we investigated hybrid methodologies wherein each module has the exibility of using sampling or PCE based methods of capturing local uncertainties while maintaining accuracy in the global uncertainty analysis. For the latter case, we use a conditional PCE model which mitigates the curse of dimension associated with intru- sive Galerkin or semi-intrusive Pseudospectral methods. After formalizing the theoretical framework, we demonstrate our proposed method using a numerical viscous ow simulation and benchmark the performance against a solely Monte-Carlo method and solely spectral method.

Iaccarino, Gianluca

2014-04-01T23:59:59.000Z

145

Uncertainty and Inference for Verification Measures  

Science Journals Connector (OSTI)

When a forecast is assessed, a single value for a verification measure is often quoted. This is of limited use, as it needs to be complemented by some idea of the uncertainty associated with the value. If this uncertainty can be quantified, it is ...

Ian T. Jolliffe

2007-06-01T23:59:59.000Z

146

COMMON KNOWLEDGE, COHERENT UNCERTAINTIES AND CONSENSUS  

E-Print Network [OSTI]

COMMON KNOWLEDGE, COHERENT UNCERTAINTIES AND CONSENSUS by Yakov Ben-Haim TECHNICAL REPORT ETR-2001 of Mechanical Engineering #12;Working Paper Common Knowledge, Coherent Uncertainties and Consensus Yakov Ben- and knowledge-functions, common knowledge and consensus. Our main results are that knowledge is constricted

Rimon, Elon

147

Including Ocean Model Uncertainties in Climate Predictions  

E-Print Network [OSTI]

Including Ocean Model Uncertainties in Climate Predictions Chris Brierley, Alan Thorpe, Mat Collins's to perform the integrations Currently uses a `slab' ocean #12;An Ocean Model Required to accurately model transient behaviour Will have its own uncertainties Requires even more computing power Create new models

Jones, Peter JS

148

Total Sales of Kerosene  

U.S. Energy Information Administration (EIA) Indexed Site

End Use: Total Residential Commercial Industrial Farm All Other Period: End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

149

Determination of Total Solids in Biomass and Total Dissolved...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Total Solids in Biomass and Total Dissolved Solids in Liquid Process Samples Laboratory Analytical Procedure (LAP) Issue Date: 3312008 A. Sluiter, B. Hames, D. Hyman, C. Payne,...

150

Total Marketed Production ..............  

Gasoline and Diesel Fuel Update (EIA)

billion cubic feet per day) billion cubic feet per day) Total Marketed Production .............. 68.95 69.77 70.45 71.64 71.91 71.70 71.46 71.57 72.61 72.68 72.41 72.62 70.21 71.66 72.58 Alaska ......................................... 1.04 0.91 0.79 0.96 1.00 0.85 0.77 0.93 0.97 0.83 0.75 0.91 0.93 0.88 0.87 Federal GOM (a) ......................... 3.93 3.64 3.44 3.82 3.83 3.77 3.73 3.50 3.71 3.67 3.63 3.46 3.71 3.70 3.62 Lower 48 States (excl GOM) ...... 63.97 65.21 66.21 66.86 67.08 67.08 66.96 67.14 67.92 68.18 68.02 68.24 65.58 67.07 68.09 Total Dry Gas Production .............. 65.46 66.21 66.69 67.79 68.03 67.83 67.61 67.71 68.69 68.76 68.50 68.70 66.55 67.79 68.66 Gross Imports ................................ 8.48 7.60 7.80 7.95 8.27 7.59 7.96 7.91 7.89 7.17 7.61 7.73 7.96 7.93 7.60 Pipeline ........................................

151

Adjoint-Based Implicit Uncertainty Analysis for Figures of Merit in a Laser Inertial Fusion Engine  

SciTech Connect (OSTI)

A primary purpose of computational models is to inform design decisions and, in order to make those decisions reliably, the confidence in the results of such models must be estimated. Monte Carlo neutron transport models are common tools for reactor designers. These types of models contain several sources of uncertainty that propagate onto the model predictions. Two uncertainties worthy of note are (1) experimental and evaluation uncertainties of nuclear data that inform all neutron transport models and (2) statistical counting precision, which all results of a Monte Carlo codes contain. Adjoint-based implicit uncertainty analyses allow for the consideration of any number of uncertain input quantities and their effects upon the confidence of figures of merit with only a handful of forward and adjoint transport calculations. When considering a rich set of uncertain inputs, adjoint-based methods remain hundreds of times more computationally efficient than Direct Monte-Carlo methods. The LIFE (Laser Inertial Fusion Energy) engine is a concept being developed at Lawrence Livermore National Laboratory. Various options exist for the LIFE blanket, depending on the mission of the design. The depleted uranium hybrid LIFE blanket design strives to close the fission fuel cycle without enrichment or reprocessing, while simultaneously achieving high discharge burnups with reduced proliferation concerns. Neutron transport results that are central to the operation of the design are tritium production for fusion fuel, fission of fissile isotopes for energy multiplication, and production of fissile isotopes for sustained power. In previous work, explicit cross-sectional uncertainty analyses were performed for reaction rates related to the figures of merit for the depleted uranium hybrid LIFE blanket. Counting precision was also quantified for both the figures of merit themselves and the cross-sectional uncertainty estimates to gauge the validity of the analysis. All cross-sectional uncertainties were small (0.1-0.8%), bounded counting uncertainties, and were precise with regard to counting precision. Adjoint/importance distributions were generated for the same reaction rates. The current work leverages those adjoint distributions to transition from explicit sensitivities, in which the neutron flux is constrained, to implicit sensitivities, in which the neutron flux responds to input perturbations. This treatment vastly expands the set of data that contribute to uncertainties to produce larger, more physically accurate uncertainty estimates.

Seifried, J E; Fratoni, M; Kramer, K J; Latkowski, J F; Peterson, P F; Powers, J J; Taylor, J M

2010-12-03T23:59:59.000Z

152

Cosmic ray propagation and dark matter in light of the latest AMS-02 data  

E-Print Network [OSTI]

The AMS-02 experiment is measuring the high energy charged cosmic rays with unprecedented accuracy. We explore the possibility of determining the cosmic-ray propagation models using the AMS-02 data $alone$. A global Bayesian analysis of the constraints on the cosmic-ray propagation models from the latest AMS-02 data on the Boron to Carbon nuclei flux ratio and proton flux is performed, with the assumption that the primary nucleon source is a broken power law in rigidity. The ratio of the diffusion coefficient $D_{0}$ to the diffusive halo height $Z_{h}$ is found to be determined with high accuracy $D_{0}/Z_{h}\\simeq 2.00\\pm0.07\\text{cm}^{2}\\text{s}^{-1}\\text{kpc}^{-1}$. The best-fit value of the halo width is $Z_{h}\\simeq 3.3$ kpc with uncertainty less than $50\\$. As a consequence, the typical uncertainties in the positron fraction is within a factor of two, and that in the antiproton flux is within an order of magnitude. Both of them are significantly smaller than that from the analyses prior to AMS-02. Taking into account all the uncertainties and correlations in the propagation parameters we derive conservative upper limits on the cross sections for DM annihilating into various standard model final states from the current PAMELA antiproton data. We also investigate the reconstruction capability of the future AMS-02 antiproton data on the DM properties. The result shows that for DM particles lighter than 100 GeV and with typical thermal annihilation cross section, the cross section can be well reconstructed with uncertainties about a factor of two for the AMS-02 three-year data taking.

Hong-Bo Jin; Yue-Liang Wu; Yu-Feng Zhou

2014-10-21T23:59:59.000Z

153

5Calculating Total Radiation Dosages at Mars The NASA, Mars Radiation Environment Experiment (MARIE) measured the daily  

E-Print Network [OSTI]

Radiation for astronauts orbiting Mars. The biggest uncertainty is in the SPE dose estimate. We had important than GCRs as a source of radiation? Explain why or why not in terms of estimation uncertainties5Calculating Total Radiation Dosages at Mars The NASA, Mars Radiation Environment Experiment (MARIE

154

Neutron total cross section measurements of gold and tantalum at the nELBE photoneutron source  

E-Print Network [OSTI]

Neutron total cross sections of 197 Au and nat Ta have been measured at the nELBE photoneutron source in the energy range from 0.1 - 10 MeV with a statistical uncertainty of up to 2 % and a total systematic uncertainty of 1 %. This facility is optimized for the fast neutron energy range and combines an excellent t ime structure of the neutron pulses (electron bunch width 5 ps) with a short flight path of 7 m. Because of the low instantaneous neutron flux transmission measurements of neutron total cross sections are possible, that exhibit very different beam and back ground conditions than found at other neutron sources.

Hannaske, Roland; Beyer, Roland; Junghans, Arnd; Bemmerer, Daniel; Birgersson, Evert; Ferrari, Anna; Grosse, Eckart; Kempe, Mathias; Kögler, Toni; Marta, Michele; Massarczyk, Ralph; Matic, Andrija; Schramm, Georg; Schwengner, Ronald; Wagner, Andreas

2014-01-01T23:59:59.000Z

155

Theoretical uncertainty of orifice flow measurement  

SciTech Connect (OSTI)

Orifice meters are the most common meters used for fluid flow measurement, especially for measuring hydrocarbons. Meters are rugged, mechanically simple, and well suited for field use under extreme weather conditions. Because of their long history of use and dominance in the fluid flow measurement, their designs, installation requirements, and equations for flow rate calculation have been standardized by different organizations in the United States and internationally. These standards provide the guideline for the users to achieve accurate flow measurement. and minimize measurement uncertainty. This paper discusses different factors that contribute to the measurement inaccuracy and provide an awareness to minimize or eliminate these errors. Many factors which influence the overall measurement uncertainty are associated with the orifice meter application. Major contributors to measurement uncertainty include the predictability of flow profile, fluid properties at flowing condition, precision of empirical equation for discharge coefficient, manufacturing tolerances in meter components, and the uncertainty associated with secondary devices monitoring the static line pressure, differential pressure across the orifice plate, flowing temperature, etc. Major factors contributing to the measurement uncertainty for a thin, concentric, square-edged orifice flowmeter are as follows: (a) Tolerances in prediction of coefficient of discharge, (b) Predictability in defining the physical properties of the flowing fluid, (c) Fluid flow condition, (d) Construction tolerances in meter components, (e) Uncertainty of secondary devices/instrumentation, and (f) Data reduction and computation. Different factors under each of the above areas are discussed with precautionary measures and installation procedures to minimize or eliminate measurement uncertainty.

Husain, Z.D. [Daniel Flow Products, Inc., Houston, TX (United States)

1995-12-01T23:59:59.000Z

156

Tacnet, J.M et al., 2010. International Snow Science Workshop Squaw Valley, USA (ISSW 2010) APPLYING NEW UNCERTAINTY RELATED THEORIES AND MULTICRITERIA DECISION  

E-Print Network [OSTI]

) APPLYING NEW UNCERTAINTY RELATED THEORIES AND MULTICRITERIA DECISION ANALYSIS METHODS TO SNOW AVALANCHE decision making and existing theories attempting to represent and propagate information imperfections decision analysis (MCDA) to model the decision-making process and fuzzy sets theory, possibility theory

Paris-Sud XI, Université de

157

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings* ........................... 3,037 115 397 384 52 1,143 22 354 64 148 357 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 386 19 43 18 11 93 7 137 8 12 38 5,001 to 10,000 .......................... 262 12 35 17 5 83 4 56 6 9 35 10,001 to 25,000 ........................ 407 20 46 44 8 151 3 53 9 19 54 25,001 to 50,000 ........................ 350 15 55 50 9 121 2 34 7 16 42 50,001 to 100,000 ...................... 405 16 57 65 7 158 2 29 6 18 45 100,001 to 200,000 .................... 483 16 62 80 5 195 1 24 Q 31 56 200,001 to 500,000 .................... 361 8 51 54 5 162 1 9 8 19 43 Over 500,000 ............................. 383 8 47 56 3 181 2 12 8 23 43 Principal Building Activity

158

Uncertainty Quantification on Prompt Fission Neutrons Spectra  

Science Journals Connector (OSTI)

Uncertainties in the evaluated prompt fission neutrons spectra present in ENDF/B-VII.0 are assessed in the framework of the Los Alamos model. The methodology used to quantify the uncertainties on an evaluated spectrum is introduced. We also briefly review the Los Alamos model and single out the parameters that have the largest influence on the calculated results. Using a Kalman filter, experimental data and uncertainties are introduced to constrain model parameters, and construct an evaluated covariance matrix for the prompt neutrons spectrum. Preliminary results are shown in the case of neutron-induced fission of 235U from thermal up to 15 MeV incident energies.

P. Talou; D.G. Madland; T. Kawano

2008-01-01T23:59:59.000Z

159

Robust quantification of parametric uncertainty for surfactant–polymer flooding  

Science Journals Connector (OSTI)

Uncertainty in surfactant–polymer flooding is an important challenge to the wide- ... uncertainty in an efficient manner. Monte Carlo simulation is the traditional uncertainty quantification approach that ... unc...

Ali Alkhatib; Peter King

2014-02-01T23:59:59.000Z

160

Decision Theory under Complex Uncertainty Durham 15 May 2008  

E-Print Network [OSTI]

Decision Theory under Complex Uncertainty Durham 15 May 2008 Decision Theory under Complex #12;Decision Theory under Complex Uncertainty Durham 15 May 2008 Decision Theory under Complex Robert Hable University of Bayreuth #12;Decision Theory under Complex Uncertainty Decision Theory

Hable, Robert

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Error Detection and Recovery for Robot Motion Planning with Uncertainty  

E-Print Network [OSTI]

Robots must plan and execute tasks in the presence of uncertainty. Uncertainty arises from sensing errors, control errors, and uncertainty in the geometry of the environment. The last, which is called model error, has ...

Donald, Bruce Randall

1987-07-01T23:59:59.000Z

162

Determination of Total Petroleum Hydrocarbons (TPH) Using Total Carbon Analysis  

SciTech Connect (OSTI)

Several methods have been proposed to replace the Freon(TM)-extraction method to determine total petroleum hydrocarbon (TPH) content. For reasons of cost, sensitivity, precision, or simplicity, none of the replacement methods are feasible for analysis of radioactive samples at our facility. We have developed a method to measure total petroleum hydrocarbon content in aqueous sample matrixes using total organic carbon (total carbon) determination. The total carbon content (TC1) of the sample is measured using a total organic carbon analyzer. The sample is then contacted with a small volume of non-pokar solvent to extract the total petroleum hydrocarbons. The total carbon content of the resultant aqueous phase of the extracted sample (TC2) is measured. Total petroleum hydrocarbon content is calculated (TPH = TC1-TC2). The resultant data are consistent with results obtained using Freon(TM) extraction followed by infrared absorbance.

Ekechukwu, A.A.

2002-05-10T23:59:59.000Z

163

Slanted-wall beam propagation : erratum.  

SciTech Connect (OSTI)

Recently, a new algorithm for wide-angle beam propagation was reported that allowed grid points to move in an arbitrary fashion between propagation planes and was thus capable of modeling waveguides whose widths or centerlines varied with propagation distance. That algorithm was accurate and stable for TE polarization but unstable for wide-angle TM propagation. This deficiency has been found to result from an omission in one of the wide-angle terms in the derivation of the finite-difference equation and is remedied here, resulting in a complete algorithm accurate for both polarizations.

Hadley, G. Ronald

2009-01-01T23:59:59.000Z

164

Neural network construction via back-propagation  

SciTech Connect (OSTI)

A method is presented that combines back-propagation with multi-layer neural network construction. Back-propagation is used not only to adjust the weights but also the signal functions. Going from one network to an equivalent one that has additional linear units, the non-linearity of these units and thus their effective presence is then introduced via back-propagation (weight-splitting). The back-propagated error causes the network to include new units in order to minimize the error function. We also show how this formalism allows to escape local minima.

Burwick, T.T.

1994-06-01T23:59:59.000Z

165

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

166

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

167

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Babb, MT Havre, MT Port of Morgan, MT Pittsburg, NH Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to India Freeport, TX Sabine Pass, LA Total to Japan Cameron, LA Kenai, AK Sabine Pass, LA Total to Mexico Douglas, AZ Nogales, AZ Calexico, CA Ogilby Mesa, CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass, TX El Paso, TX Hidalgo, TX McAllen, TX Penitas, TX Rio Bravo, TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to United Kingdom Sabine Pass, LA Period: Monthly Annual

168

Communication of uncertainty in temperature forecasts  

Science Journals Connector (OSTI)

We used experimental economics to test whether undergraduate students presented with a temperature forecast with uncertainty information in a table and bar graph format were able to use the extra information to interpret a given forecast. ...

Pricilla Marimo; Todd R. Kaplan; Ken Mylne; Martin Sharpe

169

Valuation Made Simple: No Uncertainties, Just Time  

Science Journals Connector (OSTI)

Finance deals with time and uncertainty. This chapter introduces the very basics of financial economics in a deterministic setting. Leaving aside any consideration of risk is obviously restrictive, yet importa...

L. M. Abadie; J. M. Chamorro

2013-01-01T23:59:59.000Z

170

Estimating uncertainties in integrated reservoir studies  

E-Print Network [OSTI]

between mismatch and closeness to the true reserves value. The integrated mismatch method does not need a large number of simulation runs for the uncertainty analysis, while some other methods need hundreds of runs....

Zhang, Guohong

2004-09-30T23:59:59.000Z

171

Market Clearing under Uncertainty: Wind Energy  

Science Journals Connector (OSTI)

Power systems are subject to a great variety of uncertainties. Restructuring and competition in electricity systems are definitely contingent on the available means to overcome the difficulties brought by thes...

Antonio J. Conejo; Miguel Carrión…

2010-01-01T23:59:59.000Z

172

Uncertainty in climate change policy analysis  

E-Print Network [OSTI]

Achieving agreement about whether and how to control greenhouse gas emissions would be difficult enough even if the consequences were fully known. Unfortunately, choices must be made in the face of great uncertainty, about ...

Jacoby, Henry D.; Prinn, Ronald G.

173

Analysis of S-Circuit Uncertainty  

E-Print Network [OSTI]

The theory of sensori-computational circuits provides a capable framework for the description and optimization of robotic systems, including on-line optimizations. This theory, however, is inadequate in that it does not account for uncertainty in a...

Ahmed, Taahir

2011-08-08T23:59:59.000Z

174

Infection processes on networks with structural uncertainty  

E-Print Network [OSTI]

Over the last ten years, the interest in network phenomena and the potential for a global pandemic have produced a tremendous volume of research exploring the consequences of human interaction patterns for disease propagation. ...

Zager, Laura (Laura A.)

2008-01-01T23:59:59.000Z

175

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... havior of the ratio of total quanta to total energy (Q : W) within the spectral region of photosynthetic ..... For blue-green waters, where hRmax lies.

2000-01-02T23:59:59.000Z

176

Review of uncertainty-based multidisciplinary design optimization methods for aerospace vehicles  

Science Journals Connector (OSTI)

This paper presents a comprehensive review of Uncertainty-Based Multidisciplinary Design Optimization (UMDO) theory and the state of the art in UMDO methods for aerospace vehicles. UMDO has been widely acknowledged as an advanced methodology to address competing objectives of aerospace vehicle design, such as performance, cost, reliability and robustness. However the major challenges of UMDO, namely the computational complexity and organizational complexity caused by both time-consuming disciplinary analysis models and UMDO algorithms, still greatly hamper its application in aerospace engineering. In recent years there is a surge of research in this field aiming at solving these problems. The purpose of this paper is to review these existing approaches systematically, highlight research challenges and opportunities, and help guide future efforts. Firstly, the UMDO theory preliminaries are introduced to clarify the basic UMDO concepts and mathematical formulations, as well as provide a panoramic view of the general UMDO solving process. Then following the UMDO solving process, research progress of each key step is separately surveyed and discussed, specifically including uncertainty modeling, uncertainty propagation and analysis, optimization under uncertainty, and UMDO procedure. Finally some conclusions are given, and future research trends and prospects are discussed.

Wen Yao; Xiaoqian Chen; Wencai Luo; Michel van Tooren; Jian Guo

2011-01-01T23:59:59.000Z

177

Quantification of initial-data uncertainty on a shock-accelerated gas cylinder  

SciTech Connect (OSTI)

We quantify initial-data uncertainties on a shock accelerated heavy-gas cylinder by two-dimensional well-resolved direct numerical simulations. A high-resolution compressible multicomponent flow simulation model is coupled with a polynomial chaos expansion to propagate the initial-data uncertainties to the output quantities of interest. The initial flow configuration follows previous experimental and numerical works of the shock accelerated heavy-gas cylinder. We investigate three main initial-data uncertainties, (i) shock Mach number, (ii) contamination of SF{sub 6} with acetone, and (iii) initial deviations of the heavy-gas region from a perfect cylindrical shape. The impact of initial-data uncertainties on the mixing process is examined. The results suggest that the mixing process is highly sensitive to input variations of shock Mach number and acetone contamination. Additionally, our results indicate that the measured shock Mach number in the experiment of Tomkins et al. [“An experimental investigation of mixing mechanisms in shock-accelerated flow,” J. Fluid. Mech. 611, 131 (2008)] and the estimated contamination of the SF{sub 6} region with acetone [S. K. Shankar, S. Kawai, and S. K. Lele, “Two-dimensional viscous flow simulation of a shock accelerated heavy gas cylinder,” Phys. Fluids 23, 024102 (2011)] exhibit deviations from those that lead to best agreement between our simulations and the experiment in terms of overall flow evolution.

Tritschler, V. K., E-mail: volker.tritschler@aer.mw.tum.de; Avdonin, A.; Hickel, S.; Hu, X. Y.; Adams, N. A. [Institute of Aerodynamics and Fluid Mechanics, Technische Universität München, 85747 Garching (Germany)] [Institute of Aerodynamics and Fluid Mechanics, Technische Universität München, 85747 Garching (Germany)

2014-02-15T23:59:59.000Z

178

Beam Propagation Method Using a [(p -1)/p] Pade Approximant of the Propagator  

E-Print Network [OSTI]

propagation method (BPM) is developed based on a direct approximation to the propagator using the [(p - 1)/p of the BPM. 1 Introduction The beam propagation method (BPM)1­4 is widely used in numerical simulation, the governing equation is a scalar Helmholtz equation. The BPM relies on approximating the Helmholtz equation

Lu, Ya Yan

179

Propagating Belief Functions in AND-Trees  

E-Print Network [OSTI]

: . Open Access Version: . Propagating Belief Functions in AND-Trees† Rajendra P. Srivastava Professor of Accounting School of Business...'s Official Version: . Open Access Version: . 23 REFERENCES 1. Shenoy, P. P., and G. Shafer, Propagating Belief Functions using Local Computations, IEEE...

Srivastava, Rajendra P.; Shenoy, Prakash P.; Shafer, Glenn R.

1995-01-01T23:59:59.000Z

180

Initiation and propagation of coronal mass ejections  

E-Print Network [OSTI]

This paper reviews recent progress in the research on the initiation and propagation of CMEs. In the initiation part, several trigger mechanisms are discussed; In the propagation part, the observations and modelings of EIT waves/dimmings, as the EUV counterparts of CMEs, are described.

P. F. Chen

2007-12-21T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Crack propagation driven by crystal growth  

SciTech Connect (OSTI)

Crystals that grow in confinement may exert a force on their surroundings and thereby drive crack propagation in rocks and other materials. We describe a model of crystal growth in an idealized crack geometry in which the crystal growth and crack propagation are coupled through the stress in the surrounding bulk solid. Subcritical crack propagation takes place during a transient period, which may be very long, during which the crack velocity is limited by the kinetics of crack propagation. When the crack is sufficiently large, the crack velocity becomes limited by the kinetics of crystal growth. The duration of the subcritical regime is determined by two non-dimensional parameters, which relate the kinetics of crack propagation and crystal growth to the supersaturation of the fluid and the elastic properties of the surrounding material.

A. Royne; Paul Meaking; A. Malthe-Sorenssen; B. Jamtveit; D. K. Dysthe

2011-10-01T23:59:59.000Z

182

Propagation of an atmospheric pressure plasma plume  

SciTech Connect (OSTI)

The ''plasma bullet'' behavior of atmospheric pressure plasma plumes has recently attracted significant interest. In this paper, a specially designed plasma jet device is used to study this phenomenon. It is found that a helium primary plasma can propagate through the wall of a dielectric tube and keep propagating inside the dielectric tube (secondary plasma). High-speed photographs show that the primary plasma disappears before the secondary plasma starts to propagate. Both plumes propagate at a hypersonic speed. Detailed studies on the dynamics of the plasma plumes show that the local electric field induced by the charges on the surface of the dielectric tube plays an important role in the ignition of the secondary plasma. This indicates that the propagation of the plasma plumes may be attributed to the local electric field induced by the charges in the bulletlike plasma volume.

Lu, X.; Xiong, Q.; Xiong, Z.; Hu, J.; Zhou, F.; Gong, W.; Xian, Y.; Zou, C.; Tang, Z.; Jiang, Z.; Pan, Y. [College of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China)

2009-02-15T23:59:59.000Z

183

Random matrix theory for underwater sound propagation  

Science Journals Connector (OSTI)

Ocean acoustic propagation can be formulated as a wave guide with a weakly random medium generating multiple scattering. Twenty years ago, this was recognized as a quantum chaos problem, and yet random matrix theory, one pillar of quantum or wave chaos studies, has never been introduced into the subject. The modes of the wave guide provide a representation for the propagation, which in the parabolic approximation is unitary. Scattering induced by the ocean's internal waves leads to a power-law random banded unitary matrix ensemble for long-range deep-ocean acoustic propagation. The ensemble has similarities, but differs, from those introduced for studying the Anderson metal-insulator transition. The resulting long-range propagation ensemble statistics agree well with those of full wave propagation using the parabolic equation.

K. C. Hegewisch; S. Tomsovic

2012-01-01T23:59:59.000Z

184

Uncertainty and sampling issues in tank characterization  

SciTech Connect (OSTI)

A defensible characterization strategy must recognize that uncertainties are inherent in any measurement or estimate of interest and must employ statistical methods for quantifying and managing those uncertainties. Estimates of risk and therefore key decisions must incorporate knowledge about uncertainty. This report focuses statistical methods that should be employed to ensure confident decision making and appropriate management of uncertainty. Sampling is a major source of uncertainty that deserves special consideration in the tank characterization strategy. The question of whether sampling will ever provide the reliable information needed to resolve safety issues is explored. The issue of sample representativeness must be resolved before sample information is reliable. Representativeness is a relative term but can be defined in terms of bias and precision. Currently, precision can be quantified and managed through an effective sampling and statistical analysis program. Quantifying bias is more difficult and is not being addressed under the current sampling strategies. Bias could be bounded by (1) employing new sampling methods that can obtain samples from other areas in the tanks, (2) putting in new risers on some worst case tanks and comparing the results from existing risers with new risers, or (3) sampling tanks through risers under which no disturbance or activity has previously occurred. With some bound on bias and estimates of precision, various sampling strategies could be determined and shown to be either cost-effective or infeasible.

Liebetrau, A.M.; Pulsipher, B.A.; Kashporenko, D.M. [and others

1997-06-01T23:59:59.000Z

185

Report: Technical Uncertainty and Risk Reduction  

Broader source: Energy.gov (indexed) [DOE]

TECHNICAL UNCERTAINTY AND RISK REDUCTION TECHNICAL UNCERTAINTY AND RISK REDUCTION Background In FY 2007 EMAB was tasked to assess EM's ability to reduce risk and technical uncertainty. Board members explored this topic throughout the year as a component of their focus on the previously discussed topic of Discretionary Budgeting. Discussion Understanding the risks and variability associated with EM's projects is a challenging task that has the potential to significantly impact the program's established baselines. According to budget personnel, EM has established a database of baseline variables and possibilities; however, this tool is project-specific and does not apply to the greater complex. The Board believes that EM could benefit from incorporating an additional and more comprehensive data point into the baseline development process that budgets

186

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

Outlook Price Uncertainty-January 2010 Outlook Price Uncertainty-January 2010 1 January 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 January 12, 2010 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged $74.50 per barrel in December 2009, about $3.50 per barrel lower than the prior month's average. The WTI spot price fell from $78 to $70 during the first 2 weeks of December, but colder-than-normal weather and U.S. crude oil and product inventory draws that exceeded the December 5-year averages helped push it back up to $79 per barrel by the end of the month. EIA forecasts that WTI spot prices will weaken over

187

Mujeres Hombres Total Hombres Total 16 5 21 0 10  

E-Print Network [OSTI]

Julio de 2011 Tipo de Discapacidad Sexo CENTRO 5-Distribución del estudiantado con discapacidad por centro, tipo de discapacidad, sexo y totales. #12;

Autonoma de Madrid, Universidad

188

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... ment of the total energy and vice versa. From a measurement of spectral irradi- ance ... unit energy (for the wavelength region specified).

2000-01-02T23:59:59.000Z

189

Stochastic methods for uncertainty quantification in radiation transport  

SciTech Connect (OSTI)

The use of generalized polynomial chaos (gPC) expansions is investigated for uncertainty quantification in radiation transport. The gPC represents second-order random processes in terms of an expansion of orthogonal polynomials of random variables and is used to represent the uncertain input(s) and unknown(s). We assume a single uncertain input-the total macroscopic cross section-although this does not represent a limitation of the approaches considered here. Two solution methods are examined: The Stochastic Finite Element Method (SFEM) and the Stochastic Collocation Method (SCM). The SFEM entails taking Galerkin projections onto the orthogonal basis, which, for fixed source problems, yields a linear system of fully -coupled equations for the PC coefficients of the unknown. For k-eigenvalue calculations, the SFEM system is non-linear and a Newton-Krylov method is employed to solve it. The SCM utilizes a suitable quadrature rule to compute the moments or PC coefficients of the unknown(s), thus the SCM solution involves a series of independent deterministic transport solutions. The accuracy and efficiency of the two methods are compared and contrasted. The PC coefficients are used to compute the moments and probability density functions of the unknown(s), which are shown to be accurate by comparing with Monte Carlo results. Our work demonstrates that stochastic spectral expansions are a viable alternative to sampling-based uncertainty quantification techniques since both provide a complete characterization of the distribution of the flux and the k-eigenvalue. Furthermore, it is demonstrated that, unlike perturbation methods, SFEM and SCM can handle large parameter uncertainty.

Fichtl, Erin D [Los Alamos National Laboratory; Prinja, Anil K [Los Alamos National Laboratory; Warsa, James S [Los Alamos National Laboratory

2009-01-01T23:59:59.000Z

190

Sharp shock model for propagating detonation waves  

SciTech Connect (OSTI)

Recent analyses of the reactive Euler equations have led to an understanding of the effect of curvature on an underdriven detonation wave. This advance can be incorporated into an improved sharp shock model for propagating detonation waves in hydrodynamic calculations. We illustrate the model with two simple examples: time dependent propagation of a diverging detonation wave in 1-D, and the steady 2-D propagation of a detonation wave in a rate stick. Incorporating this model into a 2-D front tracking code is discussed. 20 refs., 3 figs.

Bukiet, B.; Menikoff, R.

1989-01-01T23:59:59.000Z

191

Total.................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

49.2 49.2 15.1 15.6 11.1 7.0 5.2 8.0 Have Cooling Equipment............................... 93.3 31.3 15.1 15.6 11.1 7.0 5.2 8.0 Use Cooling Equipment................................ 91.4 30.4 14.6 15.4 11.1 6.9 5.2 7.9 Have Equipment But Do Not Use it............... 1.9 1.0 0.5 Q Q Q Q Q Do Not Have Cooling Equipment................... 17.8 17.8 N N N N N N Air-Conditioning Equipment 1, 2 Central System............................................. 65.9 3.9 15.1 15.6 11.1 7.0 5.2 8.0 Without a Heat Pump................................ 53.5 3.5 12.9 12.7 8.6 5.5 4.2 6.2 With a Heat Pump..................................... 12.3 0.4 2.2 2.9 2.5 1.5 1.0 1.8 Window/Wall Units........................................ 28.9 27.5 0.5 Q 0.3 Q Q Q 1 Unit......................................................... 14.5 13.5 0.3 Q Q Q N Q 2 Units.......................................................

192

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

7.1 7.1 7.0 8.0 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.2 Have Main Space Heating Equipment.................. 109.8 7.1 6.8 7.9 11.9 Use Main Space Heating Equipment.................... 109.1 7.1 6.6 7.9 11.4 Have Equipment But Do Not Use It...................... 0.8 N Q N 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 3.8 0.4 3.8 8.4 Central Warm-Air Furnace................................ 44.7 1.8 Q 3.1 6.0 For One Housing Unit................................... 42.9 1.5 Q 3.1 6.0 For Two Housing Units................................. 1.8 Q N Q Q Steam or Hot Water System............................. 8.2 1.9 Q Q 0.2 For One Housing Unit................................... 5.1 0.8 Q N Q For Two Housing Units.................................

193

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

5.6 5.6 17.7 7.9 Do Not Have Space Heating Equipment............... 1.2 Q Q N Have Main Space Heating Equipment.................. 109.8 25.6 17.7 7.9 Use Main Space Heating Equipment.................... 109.1 25.6 17.7 7.9 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 18.4 13.1 5.3 Central Warm-Air Furnace................................ 44.7 16.2 11.6 4.7 For One Housing Unit................................... 42.9 15.5 11.0 4.5 For Two Housing Units................................. 1.8 0.7 0.6 Q Steam or Hot Water System............................. 8.2 1.6 1.2 0.4 For One Housing Unit................................... 5.1 1.1 0.9 Q For Two Housing Units.................................

194

Total...........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

4.2 4.2 7.6 16.6 Do Not Have Cooling Equipment............................. 17.8 10.3 3.1 7.3 Have Cooling Equipment.......................................... 93.3 13.9 4.5 9.4 Use Cooling Equipment........................................... 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it.......................... 1.9 1.0 Q 0.8 Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat Pump........................................... 53.5 8.7 3.2 5.5 With a Heat Pump............................................... 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit................................................................... 14.5 2.9 0.5 2.4 2 Units.................................................................

195

Total...........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Q Q Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005

196

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Personal Computers Personal Computers Do Not Use a Personal Computer.................................. 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer.............................................. 75.6 26.6 14.5 4.1 7.9 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 20.5 11.0 3.4 6.1 Laptop Model............................................................. 16.9 6.1 3.5 0.7 1.9 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 5.0 2.6 1.0 1.3 2 to 15 Hours............................................................. 29.1 10.3 5.9 1.6 2.9 16 to 40 Hours........................................................... 13.5 4.1 2.3 0.6 1.2 41 to 167 Hours.........................................................

197

Total..............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

,171 ,171 1,618 1,031 845 630 401 Census Region and Division Northeast................................................... 20.6 2,334 1,664 562 911 649 220 New England.......................................... 5.5 2,472 1,680 265 1,057 719 113 Middle Atlantic........................................ 15.1 2,284 1,658 670 864 627 254 Midwest...................................................... 25.6 2,421 1,927 1,360 981 781 551 East North Central.................................. 17.7 2,483 1,926 1,269 999 775 510 West North Central................................. 7.9 2,281 1,930 1,566 940 796 646 South.......................................................... 40.7 2,161 1,551 1,295 856 615 513 South Atlantic......................................... 21.7 2,243 1,607 1,359 896 642 543 East South Central.................................

198

Total.........................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

..... ..... 111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer...................................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer.................................................. 75.6 4.2 5.0 5.3 9.0 Most-Used Personal Computer Type of PC Desk-top Model............................................................. 58.6 3.2 3.9 4.0 6.7 Laptop Model................................................................. 16.9 1.0 1.1 1.3 2.4 Hours Turned on Per Week Less than 2 Hours......................................................... 13.6 0.7 0.9 0.9 1.4 2 to 15 Hours................................................................. 29.1 1.7 2.1 1.9 3.4 16 to 40 Hours............................................................... 13.5 0.9 0.9 0.9 1.8 41 to 167 Hours.............................................................

199

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 2.6 0.7 1.9 2 Times A Day...................................................... 24.6 6.6 2.0 4.6 Once a Day........................................................... 42.3 8.8 2.9 5.8 A Few Times Each Week...................................... 27.2 4.7 1.5 3.1 About Once a Week.............................................. 3.9 0.7 Q 0.6 Less Than Once a Week....................................... 4.1 0.7 0.3 0.4 No Hot Meals Cooked........................................... 0.9 0.2 Q Q Conventional Oven Use an Oven......................................................... 109.6 23.7 7.5 16.2 More Than Once a Day..................................... 8.9 1.7 0.4 1.3 Once a Day.......................................................

200

Total..............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

0.7 0.7 21.7 6.9 12.1 Do Not Have Cooling Equipment................................ 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................. 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment.............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................. 1.9 0.5 Q Q Q Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump.............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................... 12.3 9.0 6.7 1.4 0.9 Window/Wall Units..................................................... 28.9 8.0 3.4 1.7 2.9 1 Unit......................................................................

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Total....................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Household Size 1 Person.......................................................... 30.0 4.6 2.5 3.7 3.2 5.4 5.5 3.7 1.6 2 Persons......................................................... 34.8 4.3 1.9 4.4 4.1 5.9 5.3 5.5 3.4 3 Persons......................................................... 18.4 2.5 1.3 1.7 1.9 2.9 3.5 2.8 1.6 4 Persons......................................................... 15.9 1.9 0.8 1.5 1.6 3.0 2.5 3.1 1.4 5 Persons......................................................... 7.9 0.8 0.4 1.0 1.1 1.2 1.1 1.5 0.9 6 or More Persons........................................... 4.1 0.5 0.3 0.3 0.6 0.5 0.7 0.8 0.4 2005 Annual Household Income Category Less than $9,999............................................. 9.9 1.9 1.1 1.3 0.9 1.7 1.3 1.1 0.5 $10,000 to $14,999..........................................

202

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

25.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer.............................................. 75.6 13.7 17.5 26.6 17.8 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 10.4 14.1 20.5 13.7 Laptop Model............................................................. 16.9 3.3 3.4 6.1 4.1 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 2.4 3.4 5.0 2.9 2 to 15 Hours............................................................. 29.1 5.2 7.0 10.3 6.6 16 to 40 Hours........................................................... 13.5 3.1 2.8 4.1 3.4 41 to 167 Hours.........................................................

203

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

4.2 4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.4 2.2 4.2 Use a Personal Computer.............................................. 75.6 17.8 5.3 12.5 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 13.7 4.2 9.5 Laptop Model............................................................. 16.9 4.1 1.1 3.0 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 2.9 0.9 2.0 2 to 15 Hours............................................................. 29.1 6.6 2.0 4.6 16 to 40 Hours........................................................... 13.5 3.4 0.9 2.5 41 to 167 Hours......................................................... 6.3

204

Total..................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

33.0 33.0 8.0 3.4 5.9 14.4 1.2 Do Not Have Cooling Equipment..................... 17.8 6.5 1.6 0.9 1.3 2.4 0.2 Have Cooling Equipment................................. 93.3 26.5 6.5 2.5 4.6 12.0 1.0 Use Cooling Equipment.................................. 91.4 25.7 6.3 2.5 4.4 11.7 0.8 Have Equipment But Do Not Use it................. 1.9 0.8 Q Q 0.2 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 14.1 3.6 1.5 2.1 6.4 0.6 Without a Heat Pump.................................. 53.5 12.4 3.1 1.3 1.8 5.7 0.6 With a Heat Pump....................................... 12.3 1.7 0.6 Q 0.3 0.6 Q Window/Wall Units....................................... 28.9 12.4 2.9 1.0 2.5 5.6 0.4 1 Unit.......................................................... 14.5 7.3 1.2 0.5 1.4 3.9 0.2 2 Units.........................................................

205

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.7 1.6 1.4 1.5 2 Times A Day.............................................................. 24.6 10.8 4.1 4.3 5.5 Once a Day................................................................... 42.3 17.0 7.2 8.7 9.3 A Few Times Each Week............................................. 27.2 11.4 4.7 6.4 4.8 About Once a Week..................................................... 3.9 1.7 0.6 0.9 0.8 Less Than Once a Week.............................................. 4.1 2.2 0.6 0.8 0.5 No Hot Meals Cooked................................................... 0.9 0.4 Q Q Q Conventional Oven Use an Oven................................................................. 109.6 46.2 18.8

206

Total...................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Single-Family Units Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business

207

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 2.1 1.8 0.3 Have Cooling Equipment............................................ 93.3 23.5 16.0 7.5 Use Cooling Equipment............................................. 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it............................ 1.9 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat Pump............................................. 53.5 16.2 10.6 5.6 With a Heat Pump................................................. 12.3 1.1 0.8 0.4 Window/Wall Units.................................................. 28.9 6.6 4.9 1.7 1 Unit..................................................................... 14.5 4.1 2.9 1.2 2 Units...................................................................

208

Total..............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

20.6 20.6 25.6 40.7 24.2 Do Not Have Cooling Equipment................................ 17.8 4.0 2.1 1.4 10.3 Have Cooling Equipment............................................. 93.3 16.5 23.5 39.3 13.9 Use Cooling Equipment.............................................. 91.4 16.3 23.4 38.9 12.9 Have Equipment But Do Not Use it............................. 1.9 0.3 Q 0.5 1.0 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 6.0 17.3 32.1 10.5 Without a Heat Pump.............................................. 53.5 5.5 16.2 23.2 8.7 With a Heat Pump................................................... 12.3 0.5 1.1 9.0 1.7 Window/Wall Units..................................................... 28.9 10.7 6.6 8.0 3.6 1 Unit......................................................................

209

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

5.6 5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer.................................. 35.5 8.1 5.6 2.5 Use a Personal Computer.............................................. 75.6 17.5 12.1 5.4 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 14.1 10.0 4.0 Laptop Model............................................................. 16.9 3.4 2.1 1.3 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 3.4 2.5 0.9 2 to 15 Hours............................................................. 29.1 7.0 4.8 2.3 16 to 40 Hours........................................................... 13.5 2.8 2.1 0.7 41 to 167 Hours......................................................... 6.3

210

Total...................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

15.2 15.2 7.8 1.0 1.2 3.3 1.9 For Two Housing Units............................. 0.9 Q N Q 0.6 N Heat Pump.................................................. 9.2 7.4 0.3 Q 0.7 0.5 Portable Electric Heater............................... 1.6 0.8 Q Q Q 0.3 Other Equipment......................................... 1.9 0.7 Q Q 0.7 Q Fuel Oil........................................................... 7.7 5.5 0.4 0.8 0.9 0.2 Steam or Hot Water System........................ 4.7 2.9 Q 0.7 0.8 N For One Housing Unit.............................. 3.3 2.9 Q Q Q N For Two Housing Units............................. 1.4 Q Q 0.5 0.8 N Central Warm-Air Furnace........................... 2.8 2.4 Q Q Q 0.2 Other Equipment......................................... 0.3 0.2 Q N Q N Wood..............................................................

211

Total...............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment................. Do Not Have Cooling Equipment................. 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment.............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment............................... 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Air-Conditioning Equipment 1, 2 Central System............................................ 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units...................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit....................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units.....................................................

212

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.4 1.0 0.4 2 Times A Day...................................................... 24.6 5.8 3.5 2.3 Once a Day........................................................... 42.3 10.7 7.8 2.9 A Few Times Each Week...................................... 27.2 5.6 4.0 1.6 About Once a Week.............................................. 3.9 0.9 0.6 0.3 Less Than Once a Week....................................... 4.1 1.1 0.7 0.4 No Hot Meals Cooked........................................... 0.9 Q Q N Conventional Oven Use an Oven......................................................... 109.6 25.3 17.6 7.7 More Than Once a Day..................................... 8.9 1.3 0.8 0.5 Once a Day.......................................................

213

Total...............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer ........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer......................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Number of Desktop PCs 1.......................................................... 50.3 8.3 14.2 11.4 7.2 9.2 5.3 14.2 2.......................................................... 16.2 0.9 2.6 3.7 2.9 6.2 0.8 2.6 3 or More............................................. 9.0 0.4 1.2 1.3 1.2 5.0 0.3 1.1 Number of Laptop PCs 1.......................................................... 22.5 2.2 4.6 4.5 2.9 8.3 1.4 4.0 2.......................................................... 4.0 Q 0.4 0.6 0.4 2.4 Q 0.5 3 or More............................................. 0.7 Q Q Q Q 0.4 Q Q Type of Monitor Used on Most-Used PC Desk-top

214

Total...............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

20.6 20.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer ........... 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer......................... 75.6 13.7 17.5 26.6 17.8 Number of Desktop PCs 1.......................................................... 50.3 9.3 11.9 18.2 11.0 2.......................................................... 16.2 2.9 3.5 5.5 4.4 3 or More............................................. 9.0 1.5 2.1 2.9 2.5 Number of Laptop PCs 1.......................................................... 22.5 4.7 4.6 7.7 5.4 2.......................................................... 4.0 0.6 0.9 1.5 1.1 3 or More............................................. 0.7 Q Q Q 0.3 Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 7.9 11.4 15.4 10.2 Flat-panel LCD.................................

215

Total................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

111.1 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Do Not Have Space Heating Equipment....... 1.2 0.5 0.3 0.2 Q 0.2 0.3 0.6 Have Main Space Heating Equipment.......... 109.8 26.2 28.5 20.4 13.0 21.8 16.3 37.9 Use Main Space Heating Equipment............ 109.1 25.9 28.1 20.3 12.9 21.8 16.0 37.3 Have Equipment But Do Not Use It.............. 0.8 0.3 0.3 Q Q N 0.4 0.6 Main Heating Fuel and Equipment Natural Gas.................................................. 58.2 12.2 14.4 11.3 7.1 13.2 7.6 18.3 Central Warm-Air Furnace........................ 44.7 7.5 10.8 9.3 5.6 11.4 4.6 12.0 For One Housing Unit........................... 42.9 6.9 10.3 9.1 5.4 11.3 4.1 11.0 For Two Housing Units......................... 1.8 0.6 0.6 Q Q Q 0.4 0.9 Steam or Hot Water System..................... 8.2 2.4 2.5 1.0 1.0 1.3 1.5 3.6 For One Housing Unit...........................

216

Total...........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Q Q Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions)

217

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

25.6 25.6 40.7 24.2 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.7 Have Main Space Heating Equipment.................. 109.8 20.5 25.6 40.3 23.4 Use Main Space Heating Equipment.................... 109.1 20.5 25.6 40.1 22.9 Have Equipment But Do Not Use It...................... 0.8 N N Q 0.6 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 18.4 13.6 14.7 Central Warm-Air Furnace................................ 44.7 6.1 16.2 11.0 11.4 For One Housing Unit................................... 42.9 5.6 15.5 10.7 11.1 For Two Housing Units................................. 1.8 0.5 0.7 Q 0.3 Steam or Hot Water System............................. 8.2 4.9 1.6 1.0 0.6 For One Housing Unit................................... 5.1 3.2 1.1 0.4

218

Total...........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

0.6 0.6 15.1 5.5 Do Not Have Cooling Equipment............................. 17.8 4.0 2.4 1.7 Have Cooling Equipment.......................................... 93.3 16.5 12.8 3.8 Use Cooling Equipment........................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it.......................... 1.9 0.3 Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 5.2 0.8 Without a Heat Pump........................................... 53.5 5.5 4.8 0.7 With a Heat Pump............................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................. 28.9 10.7 7.6 3.1 1 Unit................................................................... 14.5 4.3 2.9 1.4 2 Units.................................................................

219

Total.......................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

4.2 4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.4 2.2 4.2 Use a Personal Computer................................ 75.6 17.8 5.3 12.5 Number of Desktop PCs 1.................................................................. 50.3 11.0 3.4 7.6 2.................................................................. 16.2 4.4 1.3 3.1 3 or More..................................................... 9.0 2.5 0.7 1.8 Number of Laptop PCs 1.................................................................. 22.5 5.4 1.5 3.9 2.................................................................. 4.0 1.1 0.3 0.8 3 or More..................................................... 0.7 0.3 Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)...........................

220

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

111.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer.................................. 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer.............................................. 75.6 30.3 12.5 18.1 14.7 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 22.9 9.8 14.1 11.9 Laptop Model............................................................. 16.9 7.4 2.7 4.0 2.9 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 5.7 1.8 2.9 3.2 2 to 15 Hours............................................................. 29.1 11.9 5.1 6.5 5.7 16 to 40 Hours........................................................... 13.5 5.5 2.5 3.3 2.2 41 to 167 Hours.........................................................

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

7.1 7.1 19.0 22.7 22.3 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.2 Q Have Main Space Heating Equipment.................. 109.8 46.3 18.9 22.5 22.1 Use Main Space Heating Equipment.................... 109.1 45.6 18.8 22.5 22.1 Have Equipment But Do Not Use It...................... 0.8 0.7 Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 27.0 11.9 14.9 4.3 Central Warm-Air Furnace................................ 44.7 19.8 8.6 12.8 3.6 For One Housing Unit................................... 42.9 18.8 8.3 12.3 3.5 For Two Housing Units................................. 1.8 1.0 0.3 0.4 Q Steam or Hot Water System............................. 8.2 4.4 2.1 1.4 0.3 For One Housing Unit................................... 5.1 2.1 1.6 1.0

222

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

15.1 15.1 5.5 Do Not Have Space Heating Equipment............... 1.2 Q Q Q Have Main Space Heating Equipment.................. 109.8 20.5 15.1 5.4 Use Main Space Heating Equipment.................... 109.1 20.5 15.1 5.4 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 9.1 2.3 Central Warm-Air Furnace................................ 44.7 6.1 5.3 0.8 For One Housing Unit................................... 42.9 5.6 4.9 0.7 For Two Housing Units................................. 1.8 0.5 0.4 Q Steam or Hot Water System............................. 8.2 4.9 3.6 1.3 For One Housing Unit................................... 5.1 3.2 2.2 1.0 For Two Housing Units.................................

223

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 2.8 0.7 0.5 0.2 Million U.S. Housing Units Home Electronics Usage Indicators Table HC12.12 Home Electronics Usage Indicators by Midwest Census Region,...

224

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 1.8 1.2 0.5 Table HC11.10 Home Appliances Usage Indicators by Northeast Census Region, 2005 Million U.S. Housing Units Home Appliances...

225

Total..........................................................  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

... 2.8 1.1 0.7 Q 0.4 Million U.S. Housing Units Home Electronics Usage Indicators Table HC13.12 Home Electronics Usage Indicators by South Census Region,...

226

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 3.1 1.0 2.2 Table HC14.10 Home Appliances Usage Indicators by West Census Region, 2005 Million U.S. Housing Units Home Appliances...

227

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

States New York Florida Texas California Million U.S. Housing Units Home Electronics Usage Indicators Table HC15.12 Home Electronics Usage Indicators by Four Most Populated...

228

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 2.7 3.5 2.2 1.3 3.5 1.3 3.8 Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line Eligible for Federal...

229

Total..........................................................  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

... 13.2 3.4 2.0 1.4 Table HC12.10 Home Appliances Usage Indicators by Midwest Census Region, 2005 Million U.S. Housing Units Home Appliances...

230

Total..........................................................  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Census Region Northeast Midwest South West Million U.S. Housing Units Home Electronics Usage Indicators Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005...

231

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

(as Self-Reported) City Town Suburbs Rural Million U.S. Housing Units Home Electronics Usage Indicators Table HC8.12 Home Electronics Usage Indicators by UrbanRural Location,...

232

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 13.2 4.4 2.5 3.0 3.4 Table HC8.10 Home Appliances Usage Indicators by UrbanRural Location, 2005 Million U.S. Housing Units UrbanRural...

233

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 2.8 0.6 Q 0.5 Million U.S. Housing Units Home Electronics Usage Indicators Table HC14.12 Home Electronics Usage Indicators by West Census Region, 2005...

234

Total..........................................................  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

... 13.2 4.9 2.3 1.1 1.5 Table HC13.10 Home Appliances Usage Indicators by South Census Region, 2005 Million U.S. Housing Units South Census Region...

235

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

... 51.9 7.0 4.8 2.2 Not Asked (Mobile Homes or Apartment in Buildings with 5 or More Units)... 23.7...

236

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

Housing Units Living Space Characteristics Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Single-Family Units Detached...

237

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

0.7 21.7 6.9 12.1 Do Not Have Space Heating Equipment... 1.2 Q Q N Q Have Main Space Heating Equipment... 109.8 40.3 21.4 6.9 12.0 Use Main Space Heating...

238

Total  

U.S. Energy Information Administration (EIA) Indexed Site

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

239

Total  

U.S. Energy Information Administration (EIA) Indexed Site

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

240

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.2 1.0 0.2 2 Times A Day...................................................... 24.6 4.0 2.7 1.2 Once a Day........................................................... 42.3 7.9 5.4 2.5 A Few Times Each Week...................................... 27.2 6.0 4.8 1.2 About Once a Week.............................................. 3.9 0.6 0.5 Q Less Than Once a Week....................................... 4.1 0.6 0.4 Q No Hot Meals Cooked........................................... 0.9 0.3 Q Q Conventional Oven Use an Oven......................................................... 109.6 20.3 14.9 5.4 More Than Once a Day..................................... 8.9 1.4 1.2 0.3 Once a Day.......................................................

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Total...............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

47.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer ........... 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer......................... 75.6 30.3 12.5 18.1 14.7 Number of Desktop PCs 1.......................................................... 50.3 21.1 8.3 10.7 10.1 2.......................................................... 16.2 6.2 2.8 4.1 3.0 3 or More............................................. 9.0 2.9 1.4 3.2 1.6 Number of Laptop PCs 1.......................................................... 22.5 9.1 3.6 6.0 3.8 2.......................................................... 4.0 1.5 0.6 1.3 0.7 3 or More............................................. 0.7 0.3 Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 17.7 7.5 10.2 9.6 Flat-panel LCD.................................

242

Total........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

111.1 24.5 1,090 902 341 872 780 441 Census Region and Division Northeast............................................. 20.6 6.7 1,247 1,032 Q 811 788 147 New England.................................... 5.5 1.9 1,365 1,127 Q 814 748 107 Middle Atlantic.................................. 15.1 4.8 1,182 978 Q 810 800 159 Midwest................................................ 25.6 4.6 1,349 1,133 506 895 810 346 East North Central............................ 17.7 3.2 1,483 1,239 560 968 842 351 West North Central........................... 7.9 1.4 913 789 329 751 745 337 South................................................... 40.7 7.8 881 752 572 942 873 797 South Atlantic................................... 21.7 4.9 875 707 522 1,035 934 926 East South Central........................... 6.9 0.7 Q Q Q 852 826 432 West South Central..........................

243

Total...............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

0.7 0.7 21.7 6.9 12.1 Personal Computers Do Not Use a Personal Computer ........... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer......................... 75.6 26.6 14.5 4.1 7.9 Number of Desktop PCs 1.......................................................... 50.3 18.2 10.0 2.9 5.3 2.......................................................... 16.2 5.5 3.0 0.7 1.8 3 or More............................................. 9.0 2.9 1.5 0.5 0.8 Number of Laptop PCs 1.......................................................... 22.5 7.7 4.3 1.1 2.4 2.......................................................... 4.0 1.5 0.9 Q 0.4 3 or More............................................. 0.7 Q Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 15.4 7.9 2.8 4.8 Flat-panel LCD.................................

244

Total.................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day.............................. 8.2 2.9 2.5 1.3 0.5 1.0 2.4 4.6 2 Times A Day........................................... 24.6 6.5 7.0 4.3 3.2 3.6 4.8 10.3 Once a Day................................................ 42.3 8.8 9.8 8.7 5.1 10.0 5.0 12.9 A Few Times Each Week........................... 27.2 5.6 7.2 4.7 3.3 6.3 3.2 7.5 About Once a Week................................... 3.9 1.1 1.1 0.6 0.5 0.6 0.4 1.4 Less Than Once a Week............................ 4.1 1.3 1.0 0.9 0.5 0.4 0.7 1.4 No Hot Meals Cooked................................ 0.9 0.5 Q Q Q Q 0.2 0.5 Conventional Oven Use an Oven.............................................. 109.6 26.1 28.5 20.2 12.9 21.8 16.3 37.8 More Than Once a Day..........................

245

Total..................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

. . 111.1 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Cooling Equipment..................... 17.8 3.9 1.8 2.2 2.1 3.1 2.6 1.7 0.4 Have Cooling Equipment................................. 93.3 10.8 5.6 10.3 10.4 15.8 16.0 15.6 8.8 Use Cooling Equipment.................................. 91.4 10.6 5.5 10.3 10.3 15.3 15.7 15.3 8.6 Have Equipment But Do Not Use it................. 1.9 Q Q Q Q 0.6 0.4 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 3.7 2.6 6.1 6.8 11.2 13.2 13.9 8.2 Without a Heat Pump.................................. 53.5 3.6 2.3 5.5 5.8 9.5 10.1 10.3 6.4 With a Heat Pump....................................... 12.3 Q 0.3 0.6 1.0 1.7 3.1 3.6 1.7 Window/Wall Units....................................... 28.9 7.3 3.2 4.5 3.7 4.8 3.0 1.9 0.7 1 Unit..........................................................

246

Total..............................................  

U.S. Energy Information Administration (EIA) Indexed Site

111.1 86.6 2,720 1,970 1,310 1,941 1,475 821 1,059 944 554 Census Region and Division Northeast.................................... 20.6 13.9 3,224 2,173 836 2,219 1,619 583 903 830 Q New England.......................... 5.5 3.6 3,365 2,154 313 2,634 1,826 Q 951 940 Q Middle Atlantic........................ 15.1 10.3 3,167 2,181 1,049 2,188 1,603 582 Q Q Q Midwest...................................... 25.6 21.0 2,823 2,239 1,624 2,356 1,669 1,336 1,081 961 778 East North Central.................. 17.7 14.5 2,864 2,217 1,490 2,514 1,715 1,408 907 839 553 West North Central................. 7.9 6.4 2,729 2,289 1,924 1,806 1,510 1,085 1,299 1,113 1,059 South.......................................... 40.7 33.0 2,707 1,849 1,563 1,605 1,350 954 1,064 970 685 South Atlantic......................... 21.7 16.8 2,945 1,996 1,695 1,573 1,359 909 1,044 955

247

Total.................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

... ... 111.1 20.6 15.1 5.5 Do Not Have Cooling Equipment................................. 17.8 4.0 2.4 1.7 Have Cooling Equipment............................................. 93.3 16.5 12.8 3.8 Use Cooling Equipment............................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it............................. 1.9 0.3 Q Q Type of Air-Conditioning Equipment 1, 2 Central System.......................................................... 65.9 6.0 5.2 0.8 Without a Heat Pump.............................................. 53.5 5.5 4.8 0.7 With a Heat Pump................................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................... 28.9 10.7 7.6 3.1 1 Unit.......................................................................

248

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 8.5 2.7 2.6 4.0 Have Cooling Equipment............................................ 93.3 38.6 16.2 20.1 18.4 Use Cooling Equipment............................................. 91.4 37.8 15.9 19.8 18.0 Have Equipment But Do Not Use it............................ 1.9 0.9 0.3 0.3 0.4 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 25.8 10.9 16.6 12.5 Without a Heat Pump............................................. 53.5 21.2 9.7 13.7 8.9 With a Heat Pump................................................. 12.3 4.6 1.2 2.8 3.6 Window/Wall Units.................................................. 28.9 13.4 5.6 3.9 6.1 1 Unit.....................................................................

249

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 10.3 3.1 7.3 Have Cooling Equipment............................................ 93.3 13.9 4.5 9.4 Use Cooling Equipment............................................. 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it............................ 1.9 1.0 Q 0.8 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat Pump............................................. 53.5 8.7 3.2 5.5 With a Heat Pump................................................. 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit..................................................................... 14.5 2.9 0.5 2.4 2 Units...................................................................

250

Total..................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

78.1 78.1 64.1 4.2 1.8 2.3 5.7 Do Not Have Cooling Equipment..................... 17.8 11.3 9.3 0.6 Q 0.4 0.9 Have Cooling Equipment................................. 93.3 66.8 54.7 3.6 1.7 1.9 4.8 Use Cooling Equipment.................................. 91.4 65.8 54.0 3.6 1.7 1.9 4.7 Have Equipment But Do Not Use it................. 1.9 1.1 0.8 Q N Q Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 51.7 43.9 2.5 0.7 1.6 3.1 Without a Heat Pump.................................. 53.5 41.1 34.8 2.1 0.5 1.2 2.6 With a Heat Pump....................................... 12.3 10.6 9.1 0.4 Q 0.3 0.6 Window/Wall Units....................................... 28.9 16.5 12.0 1.3 1.0 0.4 1.7 1 Unit.......................................................... 14.5 7.2 5.4 0.5 0.2 Q 0.9 2 Units.........................................................

251

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................ 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................ 1.9 0.5 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................. 12.3 9.0 6.7 1.4 0.9 Window/Wall Units.................................................. 28.9 8.0 3.4 1.7 2.9 1 Unit.....................................................................

252

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

4.2 4.2 7.6 16.6 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.7 Have Main Space Heating Equipment.................. 109.8 23.4 7.5 16.0 Use Main Space Heating Equipment.................... 109.1 22.9 7.4 15.4 Have Equipment But Do Not Use It...................... 0.8 0.6 Q 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 14.7 4.6 10.1 Central Warm-Air Furnace................................ 44.7 11.4 4.0 7.4 For One Housing Unit................................... 42.9 11.1 3.8 7.3 For Two Housing Units................................. 1.8 0.3 Q Q Steam or Hot Water System............................. 8.2 0.6 0.3 0.3 For One Housing Unit................................... 5.1 0.4 0.2 0.1 For Two Housing Units.................................

253

Total..............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment................ Do Not Have Cooling Equipment................ 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment.............................. 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System.......................................... 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit...................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units....................................................

254

An atomic clock with $1\\times 10^{-18}$ room-temperature blackbody Stark uncertainty  

E-Print Network [OSTI]

The Stark shift due to blackbody radiation (BBR) is the key factor limiting the performance of many atomic frequency standards, with the BBR environment inside the clock apparatus being difficult to characterize at a high level of precision. Here we demonstrate an in-vacuum radiation shield that furnishes a uniform, well-characterized BBR environment for the atoms in an ytterbium optical lattice clock. Operated at room temperature, this shield enables specification of the BBR environment to a corresponding fractional clock uncertainty contribution of $5.5 \\times 10^{-19}$. Combined with uncertainty in the atomic response, the total uncertainty of the BBR Stark shift is now $1\\times10^{-18}$. Further operation of the shield at elevated temperatures enables a direct measure of the BBR shift temperature dependence and demonstrates consistency between our evaluated BBR environment and the expected atomic response.

Beloy, K; Phillips, N B; Sherman, J A; Schioppo, M; Lehman, J; Feldman, A; Hanssen, L M; Oates, C W; Ludlow, A D

2014-01-01T23:59:59.000Z

255

Sampling-based Uncertainty Quantification in Deconvolution of X-ray Radiographs  

SciTech Connect (OSTI)

In imaging applications that focus on quantitative analysis{such as X-ray radiography in the security sciences--it is necessary to be able to reliably estimate the uncertainties in the processing algorithms applied to the image data, and deconvolving the system blur out of the image is usually an essential step. In this work we solve the deconvolution problem within a Bayesian framework for edge-enhancing reconstruction with uncertainty quantification. The likelihood is a normal approximation to the Poisson likelihood, and the prior is generated from a classical total variation regularized Poisson deconvolution. Samples from the corresponding posterior distribution are computed using a Markov chain Monte Carlo approach, giving a pointwise measure of uncertainty in the final, deconvolved signal. We demonstrate the results on real data used to calibrate a high-energy X-ray source and show that this approach gives reconstructions as good as classical regularization methods, while mitigating many of their drawbacks.

Howard, M. [NSTec; Luttman, A. [NSTec; Fowler, M. [NSTec

2014-11-01T23:59:59.000Z

256

Idle Operating Total Stream Day  

U.S. Energy Information Administration (EIA) Indexed Site

3 3 Idle Operating Total Stream Day Barrels per Idle Operating Total Calendar Day Barrels per Atmospheric Crude Oil Distillation Capacity Idle Operating Total Operable Refineries Number of State and PAD District a b b 11 10 1 1,293,200 1,265,200 28,000 1,361,700 1,329,700 32,000 ............................................................................................................................................... PAD District I 1 1 0 182,200 182,200 0 190,200 190,200 0 ................................................................................................................................................................................................................................................................................................ Delaware......................................

257

ACS calibration pipeline testing: error propagation  

E-Print Network [OSTI]

1 ACS calibration pipeline testing: error propagation Doug Van Orsow, Max Mutchler, Warren Hack files (see ISRs 99-03 "CALACS Operation and Implementation" by Hack and 99-04 "ACS calibra- tion

Sirianni, Marco

258

ULTRASHORT LASER PULSE PROPAGATION IN WATER  

E-Print Network [OSTI]

We simulate ultrashort pulse propagation through water by numerical methods, which is a kind of optical communication research. Ultrashort pulses have been known to have non Beer-Lambert behavior, whereas continuous waves (CW) obey the Beer...

Byeon, Joong-Hyeok

2010-01-16T23:59:59.000Z

259

Ultrashort Pulse Propagation in the Linear Regime  

E-Print Network [OSTI]

First, we investigate the Bouguer-Lambert-Beer (BLB) law as applied to the transmission of ultrashort pulses through water in the linear absorption regime. We present a linear theory for propagation of ultrashort laser pulses, and related...

Wang, Jieyu

2010-07-14T23:59:59.000Z

260

Finite Propagation Speeds in Spatially Extended Systems  

E-Print Network [OSTI]

. Normal and anoma- lous diffusive activity [MK00, KS05] is known to spread infinitely fast over space ultra-fast activity pulse propagation in solids and plasma [LW98, TC98, ML92]. To describe these effects

Hutt, Axel

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Accounting for Parameter Uncertainty in Reservoir Uncertainty Assessment: The Conditional Finite-Domain Approach  

SciTech Connect (OSTI)

An important aim of modern geostatistical modeling is to quantify uncertainty in geological systems. Geostatistical modeling requires many input parameters. The input univariate distribution or histogram is perhaps the most important. A new method for assessing uncertainty in the histogram, particularly uncertainty in the mean, is presented. This method, referred to as the conditional finite-domain (CFD) approach, accounts for the size of the domain and the local conditioning data. It is a stochastic approach based on a multivariate Gaussian distribution. The CFD approach is shown to be convergent, design independent, and parameterization invariant. The performance of the CFD approach is illustrated in a case study focusing on the impact of the number of data and the range of correlation on the limiting uncertainty in the parameters. The spatial bootstrap method and CFD approach are compared. As the number of data increases, uncertainty in the sample mean decreases in both the spatial bootstrap and the CFD. Contrary to spatial bootstrap, uncertainty in the sample mean in the CFD approach decreases as the range of correlation increases. This is a direct result of the conditioning data being more correlated to unsampled locations in the finite domain. The sensitivity of the limiting uncertainty relative to the variogram and the variable limits are also discussed.

Babak, Olena, E-mail: obabak@ualberta.ca; Deutsch, Clayton V. [University of Alberta, Centre for Computational Geostatistics, Department of Civil and Environmental Engineering (Canada)], E-mail: cdeutsch@ualberta.ca

2009-03-15T23:59:59.000Z

262

Assessing uncertainties in the relationship between inhaled particle  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Assessing uncertainties in the relationship between inhaled particle Assessing uncertainties in the relationship between inhaled particle concentration, internal deposition and health effects, Chapter 9 Title Assessing uncertainties in the relationship between inhaled particle concentration, internal deposition and health effects, Chapter 9 Publication Type Book Chapter Year of Publication 2005 Authors Price, Phillip N. Secondary Authors Ruzer, Lev S., and Naomi H. Harley Book Title Aerosols Handbook: Measurement, Dosimetry and Health Effects Chapter Chapter Pagination 157-188 Publisher CRC Press, Boca Raton, FL Abstract The question that ultimately motivates most aerosol inhalation research is: for a given inhaled atmosphere, what health effects will result in a specified population? To attempt to address this question, quantitative research on inhaled aerosols has been performed for at least fifty years (Landahl et al, 1951). The physical factors that determine particle deposition have been determined, lung morphology has been quantified (particularly for adults), models of total particle deposition have been created and validated, and a large variety of inhalation experiments have been performed. However many basic questions remain, some of which are identified by the U.S. Committee on Research Priorities for Airborne Particulate Matter (NRC 1998a) as high-priority research areas. Among these are: What are the quantitative relationships between outdoor concentrations measured at stationary monitoring stations, and actual personal exposures? What are the exposures to biologically important constituents of particulate matter that cause responses in potentially susceptible subpopulations and the general population? What is the role of physicochemical characteristics of particulate matter in causing adverse health effects? As these questions show, in spite of significant progress in all areas of aerosol research, many of the most important practical questions remain unanswered or inadequately answered.In this chapter, we discuss the sources and magnitudes of error that hinder the ability to answer basic questions concerning the health effects of inhaled aerosols. We first consider the phenomena that affect the epidemiological studies, starting with studies of residential radon and moving on to fine particle air pollution. Next we discuss the major uncertainties in physical and physiological modeling of the causal chain that leads from inhaled aerosol concentration, to deposition in the airway, to time-dependent dose (that is, the concentration of particles at a given point in the lungs as function of time), to physiological effects, and finally to health effect.

263

Uncertainty in local determination of anisotropy parameters  

E-Print Network [OSTI]

. For the walkaway line with the best data quality, the analysis clearly shows that the shale in which the VSP tool is placed is anisotropic and that the symmetry axis is inclined from vertical. Nevertheless, the uncertainty recorded by the VSP tool. The three VSP tool placements were in massive homogeneous shales. The geologic

Cerveny, Vlastislav

264

COMPARISON OF UNCERTAINTY PARAMETERISATIONS FOR H ROBUST  

E-Print Network [OSTI]

PROBLEM The plant to be controlled is a turbocharged pas- senger car diesel engine equipped with exhaust. Diesel engine setup. The second feedback path from the exhaust to the intake manifold is due to exhaustCOMPARISON OF UNCERTAINTY PARAMETERISATIONS FOR H ROBUST CONTROL OF TURBOCHARGED DIESEL ENGINES

Cambridge, University of

265

Nuclear power expansion: thinking about uncertainty  

SciTech Connect (OSTI)

Nuclear power is one of many options available to achieve reduced carbon dioxide emissions. The real-option value model can help explain the uncertainties facing prospective nuclear plant developers in developing mitigation strategies for the development, construction, and operation of new nuclear plants. (author)

Holt, Lynne; Sotkiewicz, Paul; Berg, Sanford

2010-06-15T23:59:59.000Z

266

Manfred Huber 2011 1 Reasoning with Uncertainty  

E-Print Network [OSTI]

Logic - Applications Many everyday applications use Fuzzy Logic control Microwaves ABS brakes Camera Huber 2011 6 Fuzzy Inference (Control) Fuzzy Logic uses logic inference rules and defuzzification© Manfred Huber 2011 1 Reasoning with Uncertainty Fuzzy Logic #12;© Manfred Huber 2011 2 Fuzzy

Huber, Manfred

267

Uncertainty in Quantitative Thin-Layer Chromatography  

Science Journals Connector (OSTI)

......and cross-border issues force analysts not only to standardize...uncertainty is developed for fundamental metrological research and is...New York, NY, 1987. 7. Handbook of Thin-Layer Chromatography...New York, NY, 1994. 9. Handbook of Thin-Layer Chromatography......

Mirko Prosek; Alenka Golc-Wondra; Irena Vovk

268

Senior Center Network Redesign Under Demand Uncertainty  

E-Print Network [OSTI]

Senior Center Network Redesign Under Demand Uncertainty Osman Y. ¨Ozaltin Department of Industrial of Massachusetts Boston, Boston, MA 02125-3393, USA, michael.johnson@umb.edu Andrew J. Schaefer Department. In response, we propose a two-echelon network of senior centers. We for- mulate a two-stage stochastic

Schaefer, Andrew

269

Modeling of Uncertainty in Wind Energy Forecast  

E-Print Network [OSTI]

regression and splines are combined to model the prediction error from Tunø Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg Møller Kongens Lyngby 2006 IMM-2006

270

Uncertainty Analysis for a Virtual Flow Meter Using an Air-Handling Unit Chilled Water Valve  

SciTech Connect (OSTI)

A virtual water flow meter is developed that uses the chilled water control valve on an air-handling unit as a measurement device. The flow rate of water through the valve is calculated using the differential pressure across the valve and its associated coil, the valve command, and an empirically determined valve characteristic curve. Thus, the probability of error in the measurements is significantly greater than for conventionally manufactured flow meters. In this paper, mathematical models are developed and used to conduct uncertainty analysis for the virtual flow meter, and the results from the virtual meter are compared to measurements made with an ultrasonic flow meter. Theoretical uncertainty analysis shows that the total uncertainty in flow rates from the virtual flow meter is 1.46% with 95% confidence; comparison of virtual flow meter results with measurements from an ultrasonic flow meter yielded anuncertainty of 1.46% with 99% confidence. The comparable results from the theoretical uncertainty analysis and empirical comparison with the ultrasonic flow meter corroborate each other, and tend to validate the approach to computationally estimating uncertainty for virtual sensors introduced in this study.

Song, Li; Wang, Gang; Brambley, Michael R.

2013-04-28T23:59:59.000Z

271

total energy | OpenEI  

Open Energy Info (EERE)

total energy total energy Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics Level of Review Peer Reviewed

272

A steady-state measurement system for total hemispherical emissivity  

Science Journals Connector (OSTI)

A steady-state calorimetric technique was developed for measuring the total hemispherical emissivity of a conductive material. The system uses a thin strip of the conductive sample electrically heated by alternating current to high temperatures in a vacuum chamber. The emissivity was measured in a central region of the sample with an approximately uniform temperature distribution. Considering the influences of the gray body assumption, wire heat losses, effects of residual gas and conductive heat loss from the region to the rest of the strip, the emissivity was accurately determined by solving the inverse one-dimension steady-state heat transfer problem. The emissivities of various metal samples (nickel and 45# steel) were measured to verify the system accuracy. And the results were then analyzed to estimate the relative errors of emissivity arising from the gray body assumption, wire heat losses, effects of residual gas, non-uniform temperature distribution and the measurement uncertainty of emissivity. In the temperature range from 700 to 1300 K, the accuracy is acceptable for practical applications within the total measurement uncertainties of 1.1%. To increase the system applicability, some issues related to sample specifications, heating power control and temperature uniformity of sample test section were discussed. Thus, this system can provide accurate measurements of the total hemispherical emissivity of conductive samples at high temperatures.

Tairan Fu; Peng Tan; Chuanhe Pang

2012-01-01T23:59:59.000Z

273

Supporting qualified database for uncertainty evaluation  

SciTech Connect (OSTI)

Uncertainty evaluation constitutes a key feature of BEPU (Best Estimate Plus Uncertainty) process. The uncertainty can be the result of a Monte Carlo type analysis involving input uncertainty parameters or the outcome of a process involving the use of experimental data and connected code calculations. Those uncertainty methods are discussed in several papers and guidelines (IAEA-SRS-52, OECD/NEA BEMUSE reports). The present paper aims at discussing the role and the depth of the analysis required for merging from one side suitable experimental data and on the other side qualified code calculation results. This aspect is mostly connected with the second approach for uncertainty mentioned above, but it can be used also in the framework of the first approach. Namely, the paper discusses the features and structure of the database that includes the following kinds of documents: 1. The' RDS-facility' (Reference Data Set for the selected facility): this includes the description of the facility, the geometrical characterization of any component of the facility, the instrumentations, the data acquisition system, the evaluation of pressure losses, the physical properties of the material and the characterization of pumps, valves and heat losses; 2. The 'RDS-test' (Reference Data Set for the selected test of the facility): this includes the description of the main phenomena investigated during the test, the configuration of the facility for the selected test (possible new evaluation of pressure and heat losses if needed) and the specific boundary and initial conditions; 3. The 'QR' (Qualification Report) of the code calculation results: this includes the description of the nodalization developed following a set of homogeneous techniques, the achievement of the steady state conditions and the qualitative and quantitative analysis of the transient with the characterization of the Relevant Thermal-Hydraulics Aspects (RTA); 4. The EH (Engineering Handbook) of the input nodalization: this includes the rationale adopted for each part of the nodalization, the user choices, and the systematic derivation and justification of any value present in the code input respect to the values as indicated in the RDS-facility and in the RDS-test. (authors)

Petruzzi, A.; Fiori, F.; Kovtonyuk, A.; D'Auria, F. [Nuclear Research Group of San Piero A Grado, Univ. of Pisa, Via Livornese 1291, 56122 Pisa (Italy)

2012-07-01T23:59:59.000Z

274

Direct Observations of Reaction Zone Structure in Propagating Detonations  

E-Print Network [OSTI]

of self-sustaining, cellular detonations propagating near the Chapman-Jouguet state in hydrogen- oxygen

Barr, Al

275

Total Sky Imager (TSI) Handbook  

SciTech Connect (OSTI)

The total sky imager (TSI) provides time series of hemispheric sky images during daylight hours and retrievals of fractional sky cover for periods when the solar elevation is greater than 10 degrees.

Morris, VR

2005-06-01T23:59:59.000Z

276

E-Print Network 3.0 - acoustic waves propagating Sample Search...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

propagating Search Powered by Explorit Topic List Advanced Search Sample search results for: acoustic waves propagating...

277

E-Print Network 3.0 - acoustic waves propagation Sample Search...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

propagation Search Powered by Explorit Topic List Advanced Search Sample search results for: acoustic waves propagation...

278

Interpolation Uncertainties Across the ARM SGP Area  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Interpolation Uncertainties Across the ARM SGP Area Interpolation Uncertainties Across the ARM SGP Area J. E. Christy, C. N. Long, and T. R. Shippert Pacific Northwest National Laboratory Richland, Washington Interpolation Grids Across the SGP Network Area The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program operates a network of surface radiation measurement sites across north central Oklahoma and south central Kansas. This Southern Great Plains (SGP) network consists of 21 sites unevenly spaced from 95.5 to 99.5 degrees west longitude, and from 34.5 to 38.5 degrees north latitude. We use the technique outlined by Long and Ackerman (2000) and Long et al. (1999) to infer continuous estimates of clear-sky downwelling shortwave (SW) irradiance, SW cloud effect, and daylight fractional sky cover for each

279

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 1 July 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 July 7, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $75.34 per barrel in June 2010 ($1.60 per barrel above the prior month's average), close to the $76 per barrel projected in the forecast in last month's Outlook. EIA projects WTI prices will average about $79 per barrel over the second half of this year and rise to $84 by the end of next year (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown (Energy Price Volatility and Forecast Uncertainty). WTI futures for September 2010 delivery for the

280

Uncertainty quantification for porous media flows  

SciTech Connect (OSTI)

Uncertainty quantification is an increasingly important aspect of many areas of computational science, where the challenge is to make reliable predictions about the performance of complex physical systems in the absence of complete or reliable data. Predicting flows of oil and water through oil reservoirs is an example of a complex system where accuracy in prediction is needed primarily for financial reasons. Simulation of fluid flow in oil reservoirs is usually carried out using large commercially written finite difference simulators solving conservation equations describing the multi-phase flow through the porous reservoir rocks. This paper examines a Bayesian Framework for uncertainty quantification in porous media flows that uses a stochastic sampling algorithm to generate models that match observed data. Machine learning algorithms are used to speed up the identification of regions in parameter space where good matches to observed data can be found.

Christie, Mike [Institute of Petroleum Engineering, Heriot-Watt University, Riccarton, Edinburgh EH14 4AS, Scotland (United Kingdom)]. E-mail: mike.christie@pet.hw.ac.uk; Demyanov, Vasily [Institute of Petroleum Engineering, Heriot-Watt University, Riccarton, Edinburgh EH14 4AS, Scotland (United Kingdom); Erbas, Demet [Institute of Petroleum Engineering, Heriot-Watt University, Riccarton, Edinburgh EH14 4AS, Scotland (United Kingdom)

2006-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Global Warming Mitigation Investments Optimized under Uncertainty  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Global Warming Mitigation Investments Optimized under Uncertainty Global Warming Mitigation Investments Optimized under Uncertainty Speaker(s): Hermann Held Date: July 9, 2010 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Thomas McKone The Copenhagen Accord (2009) recognizes that 'the increase in global temperature should be below 2 degrees Celsius' (compared to pre-industrial levels, '2° target'). In recent years, energy economics have derived welfare-optimal investment streams into low-emission energy mixes and associated costs. According to our analyses, auxiliary targets that are in line with the 2° target could be achieved at relatively low costs if energy investments were triggered rather swiftly. While such analyses assume 'perfect foresight' of a benevolent 'social planner', an accompanying suite of experiments explicitly

282

Challenges in the face of uncertainty  

SciTech Connect (OSTI)

Opinions of the Interim Director of the Global Environment Program of Cornell University are presented. The focus is on obstacles to the implementation by policymakers of actions needed to address climate change. A major obstacle preventing action is stated to be the uncertainties involved in climate predictions. It is proposed that rapid, comprehensive action is required to meet the challenges posed by climate predictions, regardless of the inherent uncertainties. Aspects of future climate which are relatively certain are discussed, including continued greenhouse effects for the next several decades, a greater warming effect at higher altitudes, more warming in the winter, and linkage of all other aspects of climate to temperature changes. Aspects of climatic change which pose particular problems regarding predictability are also discussed.

Oglesby, R.T. [Cornell Univ., Ithaca, NY (United States)

1992-12-31T23:59:59.000Z

283

Polynomial regression with derivative information in nuclear reactor uncertainty quantification*  

E-Print Network [OSTI]

, Argonne National Laboratory, Argonne, IL, USA b Nuclear Engineering Division, Argonne National Laboratory1 Polynomial regression with derivative information in nuclear reactor uncertainty quantification, Argonne, IL, USA Abstract. We introduce a novel technique of uncertainty quantification using polynomial

Anitescu, Mihai

284

Uncertainty analysis of climate change and policy response  

E-Print Network [OSTI]

To aid climate policy decisions, accurate quantitative descriptions of the uncertainty in climate outcomes under various possible policies are needed. Here, we apply an earth systems model to describe the uncertainty in ...

Webster, Mort David.; Forest, Chris Eliot.; Reilly, John M.; Babiker, Mustafa H.M.; Kicklighter, David W.; Mayer, Monika.; Prinn, Ronald G.; Sarofim, Marcus C.; Sokolov, Andrei P.; Stone, Peter H.; Wang, Chien.

285

A Framework for Modeling Uncertainty in Regional Climate Change  

E-Print Network [OSTI]

In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the US associated with four dimensions of uncertainty. The sources ...

Monier, Erwan

286

Adaptive control of hypersonic vehicles in presence of actuation uncertainties  

E-Print Network [OSTI]

The thesis develops a new class of adaptive controllers that guarantee global stability in presence of actuation uncertainties. Actuation uncertainties culminate to linear plants with a partially known input matrix B. ...

Somanath, Amith

2010-01-01T23:59:59.000Z

287

Uncertainties in Energy Consumption Introduced by Building Operations and  

E-Print Network [OSTI]

Uncertainties in Energy Consumption Introduced by Building Operations and Weather for a Medium between predicted and actual building energy consumption can be attributed to uncertainties introduced in energy consumption due to actual weather and building operational practices, using a simulation

288

Jet energy scale uncertainty correlations between ATLAS and CMS  

E-Print Network [OSTI]

The correlation of the jet energy scale uncertainties between the ATLAS and CMS experiments are presented in this note. The uncertainty components for both experiments are grouped into categories. For each of these categories, the detailed

CMS Collaboration

2014-01-01T23:59:59.000Z

289

Application Form Certificate Program in Risk, Uncertainty, and Decision Analysis  

E-Print Network [OSTI]

of Uncertainty Analysis (3 credits): Nuclear Engineering 602 Uncertainty Analysis for Engineers of Engineering University of Wisconsin-Madison Personal Information: Name: __________________________ Department of Engineering Physics, College of Engineering, UW-Madison, 147 Engineering Research Building, 1500 Engineering

Van Veen, Barry D.

290

Quantifying Sources of Uncertainty in Projections of Future Climate  

Science Journals Connector (OSTI)

A simple statistical model is used to partition uncertainty from different sources, in projections of future climate from multimodel ensembles. Three major sources of uncertainty are considered: the choice of climate model, the choice of emissions ...

Paul J. Northrop; Richard E. Chandler

2014-12-01T23:59:59.000Z

291

Information-Disturbance theorem and Uncertainty Relation  

E-Print Network [OSTI]

It has been shown that Information-Disturbance theorem can play an important role in security proof of quantum cryptography. The theorem is by itself interesting since it can be regarded as an information theoretic version of uncertainty principle. It, however, has been able to treat restricted situations. In this paper, the restriction on the source is abandoned, and a general information-disturbance theorem is obtained. The theorem relates information gain by Eve with information gain by Bob.

Takayuki Miyadera; Hideki Imai

2007-07-31T23:59:59.000Z

292

Entropic uncertainties for joint quantum measurements  

SciTech Connect (OSTI)

We investigate the uncertainty associated with a joint quantum measurement of two spin components of a spin-(1/2) particle and quantify this in terms of entropy. We consider two entropic quantities, the joint entropy and the sum of the marginal entropies, and obtain lower bounds for each of these quantities. For the case of joint measurements where we measure each spin observable equally well, these lower bounds are tight.

Brougham, Thomas [Department of Physics, FJFI, CVUT, Brehova 7, 115 19 Praha 1 (Czech Republic); SUPA, Department of Physics, University of Strathclyde, Glasgow G4 ONG (United Kingdom); Andersson, Erika [SUPA, Department of Physics, School of EPS, Heriot-Watt University, Edinburgh EH14 4As (United Kingdom); Barnett, Stephen M. [SUPA, Department of Physics, University of Strathclyde, Glasgow G4 ONG (United Kingdom)

2009-10-15T23:59:59.000Z

293

Uncertainties in risk assessment at USDOE facilities  

SciTech Connect (OSTI)

The United States Department of Energy (USDOE) has embarked on an ambitious program to remediate environmental contamination at its facilities. Decisions concerning cleanup goals, choices among cleanup technologies, and funding prioritization should be largely risk-based. Risk assessments will be used more extensively by the USDOE in the future. USDOE needs to develop and refine risk assessment methods and fund research to reduce major sources of uncertainty in risk assessments at USDOE facilities. The terms{open_quote} risk assessment{close_quote} and{open_quote} risk management{close_quote} are frequently confused. The National Research Council (1983) and the United States Environmental Protection Agency (USEPA, 1991a) described risk assessment as a scientific process that contributes to risk management. Risk assessment is the process of collecting, analyzing and integrating data and information to identify hazards, assess exposures and dose responses, and characterize risks. Risk characterization must include a clear presentation of {open_quotes}... the most significant data and uncertainties...{close_quotes} in an assessment. Significant data and uncertainties are {open_quotes}...those that define and explain the main risk conclusions{close_quotes}. Risk management integrates risk assessment information with other considerations, such as risk perceptions, socioeconomic and political factors, and statutes, to make and justify decisions. Risk assessments, as scientific processes, should be made independently of the other aspects of risk management (USEPA, 1991a), but current methods for assessing health risks are based on conservative regulatory principles, causing unnecessary public concern and misallocation of funds for remediation.

Hamilton, L.D.; Holtzman, S.; Meinhold, A.F.; Morris, S.C.; Rowe, M.D.

1994-01-01T23:59:59.000Z

294

Generalized Uncertainty Principle: Approaches and Applications  

E-Print Network [OSTI]

We review highlights from string theory, black hole physics and doubly special relativity and some "thought" experiments which were suggested to probe the shortest distance and/or the maximum momentum at the Planck scale. The models which are designed to implement the minimal length scale and/or the maximum momentum in different physical systems are analysed entered the literature as the Generalized Uncertainty Principle (GUP). We compare between them. The existence of a minimal length and a maximum momentum accuracy is preferred by various physical observations. Furthermore, assuming modified dispersion relation allows for a wide range of applications in estimating, for example, the inflationary parameters, Lorentz invariance violation, black hole thermodynamics, Saleker-Wigner inequalities, entropic nature of the gravitational laws, Friedmann equations, minimal time measurement and thermodynamics of the high-energy collisions. One of the higher-order GUP approaches gives predictions for the minimal length uncertainty. Another one predicts a maximum momentum and a minimal length uncertainty, simultaneously. An extensive comparison between the different GUP approaches is summarized. We also discuss the GUP impacts on the equivalence principles including the universality of the gravitational redshift and the free fall and law of reciprocal action and on the kinetic energy of composite system. The concern about the compatibility with the equivalence principles, the universality of gravitational redshift and the free fall and law of reciprocal action should be addressed. We conclude that the value of the GUP parameters remain a puzzle to be verified.

Abdel Nasser Tawfik; Abdel Magied Diab

2014-11-23T23:59:59.000Z

295

October 16, 2014 Webinar- Decisional Analysis under Uncertainty  

Broader source: Energy.gov [DOE]

Webinar October 16, 2014, 11 am – 12:40 pm EDT: Dr. Paul Black (Neptune, Inc), Decisional Analysis under Uncertainty

296

Validation and Uncertainty Quantification in the Consortium for...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

and Uncertainty Quantification Advanced Modeling Applications Materials Performance and Optimization Virtual Reactor Integration Radiation Transport & Thermal Hydraulics CASLVUQ...

297

Heat pulse propagation studies in TFTR  

SciTech Connect (OSTI)

The time scales for sawtooth repetition and heat pulse propagation are much longer (10's of msec) in the large tokamak TFTR than in previous, smaller tokamaks. This extended time scale coupled with more detailed diagnostics has led us to revisit the analysis of the heat pulse propagation as a method to determine the electron heat diffusivity, chi/sub e/, in the plasma. A combination of analytic and computer solutions of the electron heat diffusion equation are used to clarify previous work and develop new methods for determining chi/sub e/. Direct comparison of the predicted heat pulses with soft x-ray and ECE data indicates that the space-time evolution is diffusive. However, the chi/sub e/ determined from heat pulse propagation usually exceeds that determined from background plasma power balance considerations by a factor ranging from 2 to 10. Some hypotheses for resolving this discrepancy are discussed. 11 refs., 19 figs., 1 tab.

Fredrickson, E.D.; Callen, J.D.; Colchin, R.J.; Efthimion, P.C.; Hill, K.W.; Izzo, R.; Mikkelsen, D.R.; Monticello, D.A.; McGuire, K.; Bell, J.D.

1986-02-01T23:59:59.000Z

298

The various manifestations of collisionless dissipation in wave propagation  

SciTech Connect (OSTI)

The propagation of an electrostatic wave packet inside a collisionless and initially Maxwellian plasma is always dissipative because of the irreversible acceleration of the electrons by the wave. Then, in the linear regime, the wave packet is Landau damped, so that in the reference frame moving at the group velocity, the wave amplitude decays exponentially with time. In the nonlinear regime, once phase mixing has occurred and when the electron motion is nearly adiabatic, the damping rate is strongly reduced compared to the Landau one, so that the wave amplitude remains nearly constant along the characteristics. Yet, we show here that the electrons are still globally accelerated by the wave packet, and in one dimension, this leads to a non local amplitude dependence of the group velocity. As a result, a freely propagating wave packet would shrink, and therefore, so would its total energy. In more than one dimension, not only does the magnitude of the group velocity nonlinearly vary, but also its direction. In the weakly nonlinear regime, when the collisionless damping rate is still significant compared to its linear value, the group velocity is directed towards the outside of the wave packet and tends to increase its transverse extent, while the opposite is true once the wave is essentially undamped. The impact of the nonlinear variation of the group velocity on the transverse size of the wave packet is quantified, and compared to that induced by the self-focussing due to wave front bowing.

Benisti, Didier; Morice, Olivier; Gremillet, Laurent [CEA, DAM, DIF, F-91297 Arpajon (France)

2012-06-15T23:59:59.000Z

299

Propagation of sound waves through a spatially homogeneous but smoothly time-dependent medium  

SciTech Connect (OSTI)

The propagation of sound through a spatially homogeneous but non-stationary medium is investigated within the framework of fluid dynamics. For a non-vortical fluid, especially, a generalized wave equation is derived for the (scalar) potential of the fluid velocity distribution in dependence of the equilibrium mass density of the fluid and the sound wave velocity. A solution of this equation for a finite transition period ? is determined in terms of the hypergeometric function for a phenomenologically realistic, sigmoidal change of the mass density and sound wave velocity. Using this solution, it is shown that the energy flux of the sound wave is not conserved but increases always for the propagation through a non-stationary medium, independent of whether the equilibrium mass density is increased or decreased. It is found, moreover, that this amplification of the transmitted wave arises from an energy exchange with the medium and that its flux is equal to the (total) flux of the incident and the reflected wave. An interpretation of the reflected wave as a propagation of sound backward in time is given in close analogy to Feynman and Stueckelberg for the propagation of anti-particles. The reflection and transmission coefficients of sound propagating through a non-stationary medium is analyzed in more detail for hypersonic waves with transition periods ? between 15 and 200 ps as well as the transformation of infrasound waves in non-stationary oceans. -- Highlights: •Analytically exact study of sound propagation through a non-stationary medium. •Energy exchange between the non-stationary medium and the sound wave. •Transformation of hypersonic and ultrasound frequencies in non-stationary media. •Propagation of sound backward in time in close analogy to anti-particles. •Prediction of tsunamis both in spatially and temporally inhomogeneous oceans.

Hayrapetyan, A.G., E-mail: armen@physi.uni-heidelberg.de [Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, D-69120 Heidelberg (Germany); Max-Planck-Institut für Kernphysik, Saupfercheckweg 1, D-69117 Heidelberg (Germany); Grigoryan, K.K.; Petrosyan, R.G. [Yerevan State University, 1 Alex Manoogian Str., 0025 Yerevan (Armenia)] [Yerevan State University, 1 Alex Manoogian Str., 0025 Yerevan (Armenia); Fritzsche, S. [Helmholtz-Institut Jena, Fröbelstieg 3, D-07743 Jena (Germany) [Helmholtz-Institut Jena, Fröbelstieg 3, D-07743 Jena (Germany); Theoretisch-Physikalisches Institut, Friedrich-Schiller-Universität Jena, Max-Wien-Platz 1, D-07743 Jena (Germany)

2013-06-15T23:59:59.000Z

300

H. Douville D. Salas-Me lia S. Tyteca On the tropical origin of uncertainties in the global land precipitation  

E-Print Network [OSTI]

. 2005). Global warming also leads to a systematic increase in total precipitable water, soH. Douville � D. Salas-Me´ lia � S. Tyteca On the tropical origin of uncertainties in the global land precipitation response to global warming Received: 17 August 2005 / Accepted: 25 October 2005

Ribes, Aurélien

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 1: Main report  

SciTech Connect (OSTI)

This volume is the first of a two-volume document that summarizes a joint project conducted by the US Nuclear Regulatory Commission and the European Commission to assess uncertainties in the MACCS and COSYMA probabilistic accident consequence codes. These codes were developed primarily for estimating the risks presented by nuclear reactors based on postulated frequencies and magnitudes of potential accidents. This document reports on an ongoing project to assess uncertainty in the MACCS and COSYMA calculations for the offsite consequences of radionuclide releases by hypothetical nuclear power plant accidents. A panel of sixteen experts was formed to compile credible and traceable uncertainty distributions for food chain variables that affect calculations of offsite consequences. The expert judgment elicitation procedure and its outcomes are described in these volumes. Other panels were formed to consider uncertainty in other aspects of the codes. Their results are described in companion reports. Volume 1 contains background information and a complete description of the joint consequence uncertainty study. Volume 2 contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures for both panels, (3) the rationales and results for the panels on soil and plant transfer and animal transfer, (4) short biographies of the experts, and (5) the aggregated results of their responses.

Brown, J. [National Radiological Protection Board (United Kingdom); Goossens, L.H.J.; Kraan, B.C.P. [Delft Univ. of Technology (Netherlands)] [and others

1997-06-01T23:59:59.000Z

302

Reactor Neutrino Flux Uncertainty Suppression on Multiple Detector Experiments  

E-Print Network [OSTI]

This publication provides a coherent treatment for the reactor neutrino flux uncertainties suppression, specially focussed on the latest $\\theta_{13}$ measurement. The treatment starts with single detector in single reactor site, most relevant for all reactor experiments beyond $\\theta_{13}$. We demonstrate there is no trivial error cancellation, thus the flux systematic error can remain dominant even after the adoption of multi-detector configurations. However, three mechanisms for flux error suppression have been identified and calculated in the context of Double Chooz, Daya Bay and RENO sites. Our analysis computes the error {\\it suppression fraction} using simplified scenarios to maximise relative comparison among experiments. We have validated the only mechanism exploited so far by experiments to improve the precision of the published $\\theta_{13}$. The other two newly identified mechanisms could lead to total error flux cancellation under specific conditions and are expected to have major implications on the global $\\theta_{13}$ knowledge today. First, Double Chooz, in its final configuration, is the only experiment benefiting from a negligible reactor flux error due to a $\\sim$90\\% geometrical suppression. Second, Daya Bay and RENO could benefit from their partial geometrical cancellation, yielding a potential $\\sim$50\\% error suppression, thus significantly improving the global $\\theta_{13}$ precision today. And third, we illustrate the rationale behind further error suppression upon the exploitation of the inter-reactor error correlations, so far neglected. So, our publication is a key step forward in the context of high precision neutrino reactor experiments providing insight on the suppression of their intrinsic flux error uncertainty, thus affecting past and current experimental results, as well as the design of future experiments.

Andi Cucoanes; Pau Novella; Anatael Cabrera; Muriel Fallot; Anthony Onillon; Michel Obolensky; Frederic Yermia

2015-01-02T23:59:59.000Z

303

Linear elastic fracture mechanics predicts the propagation distance of frictional slip  

E-Print Network [OSTI]

When a frictional interface is subject to a localized shear load, it is often (experimentally) observed that local slip events initiate at the stress concentration and propagate over parts of the interface by arresting naturally before reaching the edge. We develop a theoretical model based on linear elastic fracture mechanics to describe the propagation of such precursory slip. The model's prediction of precursor lengths as a function of external load is in good quantitative agreement with laboratory experiments as well as with dynamic simulations, and provides thereby evidence to recognize frictional slip as a fracture phenomenon. We show that predicted precursor lengths depend, within given uncertainty ranges, mainly on the kinetic friction coefficient, and only weakly on other interface and material parameters. By simplifying the fracture mechanics model we also reveal sources for the observed non-linearity in the growth of precursor lengths as a function of the applied force. The discrete nature of precursors as well as the shear tractions caused by frustrated Poisson's expansion are found to be the dominant factors. Finally, we apply our model to a different, symmetric set-up and provide a prediction of the propagation distance of frictional slip for future experiments.

David S. Kammer; Mathilde Radiguet; Jean-Paul Ampuero; Jean-François Molinari

2014-08-18T23:59:59.000Z

304

Constraining uncertainties about the sources and magnitude of polycyclic  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Constraining uncertainties about the sources and magnitude of polycyclic Constraining uncertainties about the sources and magnitude of polycyclic aromatic hydrocarbon (PAH)levels in ambient air: the State of Minnesota as a case study Title Constraining uncertainties about the sources and magnitude of polycyclic aromatic hydrocarbon (PAH)levels in ambient air: the State of Minnesota as a case study Publication Type Journal Article LBNL Report Number LBNL-54473 Year of Publication 2004 Authors Lobscheid, Agnes B., and Thomas E. McKone Journal Atmospheric Environment Volume 38 Start Page Chapter Pagination 5501-5515 Abstract Emissions data are often lacking or uncertain for many airborne contaminants. Chemicals, such as polycyclic aromatic hydrocarbons (PAHs), emitted from combustion sources, fall into this category. Currently available ambient-air emission inventories of PAHs either fail to account for population-based activities (such as residential wood combustion and motor vehicle activity) and/or report 'total PAH' or particulate organic matter emissions instead of individual compounds. We measure the degree of overlap between predicted concentrations from estimated emissions with measured concentrations. Our analysis is, based on probabilistic analysis of measured outdoor air concentrations with those predicted from mass-balance models. . Based on available information, we estimate the relative magnitude of emissions from four major sources ofPAHs to outdoor air- (1) on-road motor vehicles, including light-duty gasoline vehicles and diesel-powered buses and medium and heavy duty trucks; (2) residential wood combustion; and (3) power generation from external combustion boilers. We use the CalTOX regional multimedia mass-balance model to evaluate our emissions estimates in rural and urban regions of the state of Minnesota, USA. We compare model estimatesof outdoor PAH airborne concentrations with those reported by the Minnesota Children's Pesticide Exposure Study (MNCPES). With these measured concentrations we probabilistically evaluate our emissions and interpret the reliability of our emissions estimates for specific PAHs. The median estimates of our predicted outdoor air concentrations agree within an order of magnitude of measured concentrations. For fourrepresentative PAHs, we were able to obtain a reasonable degree of overlap between empirical and predicted distributions of outdoor air concentrations. Our combination of models, emissions estimates, and empirical concentration data estimate exposure in a manner that is more reliable than any of these tools alone. Thereby, we increase our confidence about our plausible ranges of emissions and predicted concentrations

305

A Bayesian approach to simultaneously quantify assignments and linguistic uncertainty  

SciTech Connect (OSTI)

Subject matter expert assessments can include both assignment and linguistic uncertainty. This paper examines assessments containing linguistic uncertainty associated with a qualitative description of a specific state of interest and the assignment uncertainty associated with assigning a qualitative value to that state. A Bayesian approach is examined to simultaneously quantify both assignment and linguistic uncertainty in the posterior probability. The approach is applied to a simplified damage assessment model involving both assignment and linguistic uncertainty. The utility of the approach and the conditions under which the approach is feasible are examined and identified.

Chavez, Gregory M [Los Alamos National Laboratory; Booker, Jane M [BOOKER SCIENTIFIC FREDERICKSBURG; Ross, Timothy J [UNM

2010-10-07T23:59:59.000Z

306

Explosion propagation in inert porous media  

Science Journals Connector (OSTI)

...the density, c the heat capacity and k the thermal...important in porous media combustion because it represents...voids and the rate of heat loss to the porous medium...velocities for a propagating combustion wave: the planar laminar...detonation velocity. For hydrocarbon fuel-air mixtures...

2012-01-01T23:59:59.000Z

307

Analysis of Microwave Propagation In Plasma  

E-Print Network [OSTI]

Analysis of Microwave Propagation In Plasma Elaine Chung Advisor: Dr. John Rodgers #12;Plasma OverviewPlasma Overview · Plasma ­ ionized gas htt[p://www.noaa.gov http://www.photoeverywhere.co.uk http://sohowww.nascom.nasa.gov/ #12;Experimental Plasma · Formed by collisional excitation of gas in an electric field Electrode Non

Anlage, Steven

308

Information Propagation in the Bitcoin Network  

E-Print Network [OSTI]

Information Propagation in the Bitcoin Network Christian Decker ETH Zurich ­ Distributed Computing Group ­ www.disco.ethz.ch #12;What is Bitcoin? #12;What is Bitcoin? + #12;What is Bitcoin? + = #12;What 250 300 Price[USD] USD / Bitcoin exchange price 150$/BTC #12;What's it worth? Oct 2010 Feb 2011 Jun

309

Wave propagation in the magnetic sun  

E-Print Network [OSTI]

This paper reports on efforts to simulate wave propagation in the solar interior. Presented is work on extending a numerical code for constant entropy acoustic waves in the absence of magnetic fields to the case where magnetic fields are present. A set of linearized magnetohydrodynamic (MHD) perturbation equations has been derived and implemented.

T. Hartlep; M. S. Miesch; N. N. Mansour

2008-05-03T23:59:59.000Z

310

Modified Photon Propagator in the -Dominance Model  

Science Journals Connector (OSTI)

......by the insertion of a single p0 propa- gator, second graph of Fig. 1, and the first...term" inserted between photon propa- gators. Using the vector meson propagator given...peating this insertion process of p0 propa- gators and "photon mass terms" to con- struct......

R. A. Buchl; B. P. Nigam

1970-09-01T23:59:59.000Z

311

Detonation propagation in a high loss configuration  

SciTech Connect (OSTI)

This work presents an experimental study of detonation wave propagation in tubes with inner diameters (ID) comparable to the mixture cell size. Propane-oxygen mixtures were used in two test section tubes with inner diameters of 1.27 mm and 6.35 mm. For both test sections, the initial pressure of stoichiometric mixtures was varied to determine the effect on detonation propagation. For the 6.35 mm tube, the equivalence ratio {phi} (where the mixture was {phi} C{sub 3}H{sub 8} + 50{sub 2}) was also varied. Detonations were found to propagate in mixtures with cell sizes as large as five times the diameter of the tube. However, under these conditions, significant losses were observed, resulting in wave propagation velocities as slow as 40% of the CJ velocity U{sub CJ}. A review of relevant literature is presented, followed by experimental details and data. Observed velocity deficits are predicted using models that account for boundary layer growth inside detonation waves.

Jackson, Scott I [Los Alamos National Laboratory; Shepherd, Joseph E [CALTECH

2009-01-01T23:59:59.000Z

312

Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for internal dosimetry. Volume 1: Main report  

SciTech Connect (OSTI)

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA internal dosimetry models.

Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Harrison, J.D. [National Radiological Protection Board (United Kingdom); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

1998-04-01T23:59:59.000Z

313

Probabilistic accident consequence uncertainty analysis -- Late health effects uncertainty assessment. Volume 1: Main report  

SciTech Connect (OSTI)

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA late health effects models.

Little, M.P.; Muirhead, C.R. [National Radiological Protection Board (United Kingdom); Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

1997-12-01T23:59:59.000Z

314

Probabilistic accident consequence uncertainty analysis -- Early health effects uncertainty assessment. Volume 1: Main report  

SciTech Connect (OSTI)

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA early health effects models.

Haskin, F.E. [Univ. of New Mexico, Albuquerque, NM (United States); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Goossens, L.H.J.; Kraan, B.C.P. [Delft Univ. of Technology (Netherlands); Grupa, J.B. [Netherlands Energy Research Foundation (Netherlands)

1997-12-01T23:59:59.000Z

315

Uncertainty Budget Analysis for Dimensional Inspection Processes (U)  

SciTech Connect (OSTI)

This paper is intended to provide guidance and describe how to prepare an uncertainty analysis of a dimensional inspection process through the utilization of an uncertainty budget analysis. The uncertainty analysis is stated in the same methodology as that of the ISO GUM standard for calibration and testing. There is a specific distinction between how Type A and Type B uncertainty analysis is used in a general and specific process. All theory and applications are utilized to represent both a generalized approach to estimating measurement uncertainty and how to report and present these estimations for dimensional measurements in a dimensional inspection process. The analysis of this uncertainty budget shows that a well-controlled dimensional inspection process produces a conservative process uncertainty, which can be attributed to the necessary assumptions in place for best possible results.

Valdez, Lucas M. [Los Alamos National Laboratory

2012-07-26T23:59:59.000Z

316

Uncertainty assessment for accelerator-driven systems.  

SciTech Connect (OSTI)

The concept of a subcritical system driven by an external source of neutrons provided by an accelerator ADS (Accelerator Driver System) has been recently revived and is becoming more popular in the world technical community with active programs in Europe, Russia, Japan, and the U.S. A general consensus has been reached in adopting for the subcritical component a fast spectrum liquid metal cooled configuration. Both a lead-bismuth eutectic, sodium and gas are being considered as a coolant; each has advantages and disadvantages. The major expected advantage is that subcriticality avoids reactivity induced transients. The potentially large subcriticality margin also should allow for the introduction of very significant quantities of waste products (minor Actinides and Fission Products) which negatively impact the safety characteristics of standard cores. In the U.S. these arguments are the basis for the development of the Accelerator Transmutation of Waste (ATW), which has significant potential in reducing nuclear waste levels. Up to now, neutronic calculations have not attached uncertainties on the values of the main nuclear integral parameters that characterize the system. Many of these parameters (e.g., degree of subcriticality) are crucial to demonstrate the validity and feasibility of this concept. In this paper we will consider uncertainties related to nuclear data only. The present knowledge of the cross sections of many isotopes that are not usually utilized in existing reactors (like Bi, Pb-207, Pb-208, and also Minor Actinides and Fission Products) suggests that uncertainties in the integral parameters will be significantly larger than for conventional reactor systems, and this raises concerns on the neutronic performance of those systems.

Finck, P. J.; Gomes, I.; Micklich, B.; Palmiotti, G.

1999-06-10T23:59:59.000Z

317

Uncertainty and sensitivity analysis of chronic exposure results with the MACCS reactor accident consequence model  

SciTech Connect (OSTI)

Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the chronic exposure pathways associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 75 imprecisely known input variables on the following reactor accident consequences are studied: crop growing season dose, crop long-term dose, water ingestion dose, milk growing season dose, long-term groundshine dose, long-term inhalation dose, total food pathways dose, total ingestion pathways dose, total long-term pathways dose, total latent cancer fatalities, area-dependent cost, crop disposal cost, milk disposal cost, population-dependent cost, total economic cost, condemnation area, condemnation population, crop disposal area and milk disposal area. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: dry deposition velocity, transfer of cesium from animal feed to milk, transfer of cesium from animal feed to meat, ground concentration of Cs-134 at which the disposal of milk products will be initiated, transfer of Sr-90 from soil to legumes, maximum allowable ground concentration of Sr-90 for production of crops, fraction of cesium entering surface water that is consumed in drinking water, groundshine shielding factor, scale factor defining resuspension, dose reduction associated with decontamination, and ground concentration of 1-131 at which disposal of crops will be initiated due to accidents that occur during the growing season.

Helton, J.C. [Arizona State Univ., Tempe, AZ (United States); Johnson, J.D.; Rollstin, J.A. [Gram, Inc., Albuquerque, NM (United States); Shiver, A.W.; Sprung, J.L. [Sandia National Labs., Albuquerque, NM (United States)

1995-01-01T23:59:59.000Z

318

Online Sensor Calibration Monitoring Uncertainty Estimation  

SciTech Connect (OSTI)

Empirical modeling techniques have been applied to online process monitoring to detect equipment and instrumentation degradations. However, few applications provide prediction uncertainty estimates, which can provide a measure of confidence in decisions. This paper presents the development of analytical prediction interval estimation methods for three common nonlinear empirical modeling strategies: artificial neural networks, neural network partial least squares, and local polynomial regression. The techniques are applied to nuclear power plant operational data for sensor calibration monitoring, and the prediction intervals are verified via bootstrap simulation studies.

Hines, J. Wesley; Rasmussen, Brandon [University of Tennessee (United States)

2005-09-15T23:59:59.000Z

319

Gravitational tests of the Generalized Uncertainty Principle  

E-Print Network [OSTI]

We compute the corrections to the Schwarzschild metric necessary to reproduce the Hawking temperature derived from a Generalized Uncertainty Principle (GUP), so that the GUP deformation parameter is directly linked to the deformation of the metric. Using this modified Schwarzschild metric, we compute corrections to the standard General Relativistic predictions for the light deflection and perihelion precession, both for planets in the solar system and for binary pulsars. This analysis allows us to set bounds for the GUP deformation parameter from well-known astronomical measurements.

Scardigli, Fabio

2014-01-01T23:59:59.000Z

320

Gravitational tests of the Generalized Uncertainty Principle  

E-Print Network [OSTI]

We compute the corrections to the Schwarzschild metric necessary to reproduce the Hawking temperature derived from a Generalized Uncertainty Principle (GUP), so that the GUP deformation parameter is directly linked to the deformation of the metric. Using this modified Schwarzschild metric, we compute corrections to the standard General Relativistic predictions for the light deflection and perihelion precession, both for planets in the solar system and for binary pulsars. This analysis allows us to set bounds for the GUP deformation parameter from well-known astronomical measurements.

Fabio Scardigli; Roberto Casadio

2014-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
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321

EPR Steering Inequalities from Entropic Uncertainty Relations  

E-Print Network [OSTI]

We use entropic uncertainty relations to formulate inequalities that witness Einstein-Podolsky-Rosen (EPR) steering correlations in diverse quantum systems. We then use these inequalities to formulate symmetric EPR-steering inequalities using the mutual information. We explore the differing natures of the correlations captured by one-way and symmetric steering inequalities, and examine the possibility of exclusive one-way steerability in two-qubit states. Furthermore, we show that steering inequalities can be extended to generalized positive operator valued measures (POVMs), and we also derive hybrid-steering inequalities between alternate degrees of freedom.

James Schneeloch; Curtis J. Broadbent; Stephen P. Walborn; Eric G. Cavalcanti; John C. Howell

2013-03-29T23:59:59.000Z

322

SWEPP PAN assay system uncertainty analysis: Active mode measurements of solidified aqueous sludge waste  

SciTech Connect (OSTI)

The Idaho National Engineering and Environmental Laboratory is being used as a temporary storage facility for transuranic waste generated by the US Nuclear Weapons program at the Rocky Flats Plant (RFP) in Golden, Colorado. Currently, there is a large effort in progress to prepare to ship this waste to the Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico. In order to meet the TRU Waste Characterization Quality Assurance Program Plan nondestructive assay compliance requirements and quality assurance objectives, it is necessary to determine the total uncertainty of the radioassay results produced by the Stored Waste Examination Pilot Plant (SWEPP) Passive Active Neutron (PAN) radioassay system. This paper is one of a series of reports quantifying the results of the uncertainty analysis of the PAN system measurements for specific waste types and measurement modes. In particular this report covers active mode measurements of weapons grade plutonium-contaminated aqueous sludge waste contained in 208 liter drums (item description codes 1, 2, 7, 800, 803, and 807). Results of the uncertainty analysis for PAN active mode measurements of aqueous sludge indicate that a bias correction multiplier of 1.55 should be applied to the PAN aqueous sludge measurements. With the bias correction, the uncertainty bounds on the expected bias are 0 {+-} 27%. These bounds meet the Quality Assurance Program Plan requirements for radioassay systems.

Blackwood, L.G.; Harker, Y.D.; Meachum, T.R.

1997-12-01T23:59:59.000Z

323

Performance Period Total Fee Paid  

Broader source: Energy.gov (indexed) [DOE]

Period Period Total Fee Paid 4/29/2012 - 9/30/2012 $418,348 10/1/2012 - 9/30/2013 $0 10/1/2013 - 9/30/2014 $0 10/1/2014 - 9/30/2015 $0 10/1/2015 - 9/30/2016 $0 Cumulative Fee Paid $418,348 Contract Type: Cost Plus Award Fee Contract Period: $116,769,139 November 2011 - September 2016 $475,395 $0 Fee Information Total Estimated Contract Cost $1,141,623 $1,140,948 $1,140,948 $5,039,862 $1,140,948 Maximum Fee $5,039,862 Minimum Fee Fee Available Portage, Inc. DE-DT0002936 EM Contractor Fee Site: MOAB Uranium Mill Tailings - MOAB, UT Contract Name: MOAB Uranium Mill Tailings Remedial Action Contract September 2013 Contractor: Contract Number:

324

Buildings","Total  

U.S. Energy Information Administration (EIA) Indexed Site

L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings*",54068,51570,45773,6746,34910,1161,3725,779 "Building Floorspace" "(Square Feet)" "1,001 to 5,000",6272,5718,4824,986,3767,50,22,54 "5,001 to 10,000",7299,6667,5728,1240,4341,61,169,45 "10,001 to 25,000",10829,10350,8544,1495,6442,154,553,"Q"

325

ARM - Measurement - Total cloud water  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

cloud water cloud water ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total cloud water The total concentration (mass/vol) of ice and liquid water particles in a cloud; this includes condensed water content (CWC). Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including those recorded for diagnostic or quality assurance purposes. External Instruments NCEPGFS : National Centers for Environment Prediction Global Forecast System Field Campaign Instruments CSI : Cloud Spectrometer and Impactor PDI : Phase Doppler Interferometer

326

Buildings","Total  

U.S. Energy Information Administration (EIA) Indexed Site

L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",61707,58693,49779,6496,37150,3058,5343,1913 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6750,5836,4878,757,3838,231,109,162 "5,001 to 10,000 ..............",7940,7166,5369,1044,4073,288,160,109 "10,001 to 25,000 .............",10534,9773,7783,1312,5712,358,633,232

327

Buildings","Total  

U.S. Energy Information Administration (EIA) Indexed Site

L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",64783,62060,51342,5556,37918,4004,4950,2403 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6789,6038,4826,678,3932,206,76,124 "5,001 to 10,000 ..............",6585,6090,4974,739,3829,192,238,248 "10,001 to 25,000 .............",11535,11229,8618,1197,6525,454,506,289

328

Comparison of Rigid and Adaptive Methods of Propagating Gross Tumor Volume Through Respiratory Phases of Four-Dimensional Computed Tomography Image Data Set  

SciTech Connect (OSTI)

Purpose: To compare three different methods of propagating the gross tumor volume (GTV) through the respiratory phases that constitute a four-dimensional computed tomography image data set. Methods and Materials: Four-dimensional computed tomography data sets of 20 patients who had undergone definitive hypofractionated radiotherapy to the lung were acquired. The GTV regions of interest (ROIs) were manually delineated on each phase of the four-dimensional computed tomography data set. The ROI from the end-expiration phase was propagated to the remaining nine phases of respiration using the following three techniques: (1) rigid-image registration using in-house software, (2) rigid image registration using research software from a commercial radiotherapy planning system vendor, and (3) rigid-image registration followed by deformable adaptation originally intended for organ-at-risk delineation using the same software. The internal GTVs generated from the various propagation methods were compared with the manual internal GTV using the normalized Dice similarity coefficient (DSC) index. Results: The normalized DSC index of 1.01 {+-} 0.06 (SD) for rigid propagation using the in-house software program was identical to the normalized DSC index of 1.01 {+-} 0.06 for rigid propagation achieved with the vendor's research software. Adaptive propagation yielded poorer results, with a normalized DSC index of 0.89 {+-} 0.10 (paired t test, p <0.001). Conclusion: Propagation of the GTV ROIs through the respiratory phases using rigid- body registration is an acceptable method within a 1-mm margin of uncertainty. The adaptive organ-at-risk propagation method was not applicable to propagating GTV ROIs, resulting in an unacceptable reduction of the volume and distortion of the ROIs.

Ezhil, Muthuveni [Department of Radiation Physics, University of Texas M. D. Anderson Cancer Center, Houston, TX (United States); Department of Radiation Oncology, University of Texas M. D. Anderson Cancer Center, Houston, TX (United States)], E-mail: veniezhil@hotmail.com; Choi, Bum; Starkschall, George [Department of Radiation Physics, University of Texas M. D. Anderson Cancer Center, Houston, TX (United States); Bucci, M. Kara [Department of Radiation Oncology, University of Texas M. D. Anderson Cancer Center, Houston, TX (United States); Vedam, Sastry; Balter, Peter [Department of Radiation Physics, University of Texas M. D. Anderson Cancer Center, Houston, TX (United States)

2008-05-01T23:59:59.000Z

329

Uncertainty Analysis Technique for OMEGA Dante Measurements  

SciTech Connect (OSTI)

The Dante is an 18 channel X-ray filtered diode array which records the spectrally and temporally resolved radiation flux from various targets (e.g. hohlraums, etc.) at X-ray energies between 50 eV to 10 keV. It is a main diagnostics installed on the OMEGA laser facility at the Laboratory for Laser Energetics, University of Rochester. The absolute flux is determined from the photometric calibration of the X-ray diodes, filters and mirrors and an unfold algorithm. Understanding the errors on this absolute measurement is critical for understanding hohlraum energetic physics. We present a new method for quantifying the uncertainties on the determined flux using a Monte-Carlo parameter variation technique. This technique combines the uncertainties in both the unfold algorithm and the error from the absolute calibration of each channel into a one sigma Gaussian error function. One thousand test voltage sets are created using these error functions and processed by the unfold algorithm to produce individual spectra and fluxes. Statistical methods are applied to the resultant set of fluxes to estimate error bars on the measurements.

May, M J; Widmann, K; Sorce, C; Park, H; Schneider, M

2010-05-07T23:59:59.000Z

330

From Interval Methods of Representing Uncertainty To A General Description of Uncertainty  

E-Print Network [OSTI]

hunguyen@nmsu.edu Abstract Measurements do not result in an exact value of the measured quantity; even of the measured quantity. Traditionally, in science and engineering, this uncertainty is character­ ized measurements. Some of this knowl­ edge comes not from measurements but from the ex­ pertise of scientists

Kreinovich, Vladik

331

Modeling TechnologyModeling Technology Innovation:Innovation: Uncertainties inUncertainties in  

E-Print Network [OSTI]

environmental technologies (e.g., advanced power plants with carbon capture and storage) in energy- economic control systems used at coal-fired power plants · No "natural" markets for these technologies; major models used for climate/energy policy analysis? · What are the uncertainties associated with use

332

Discrete Propagation in Numerically Simulated Nocturnal Squall Lines  

Science Journals Connector (OSTI)

Simulations of a typical midlatitude squall line were used to investigate a mechanism for discrete propagation, defined as convective initiation ahead of an existing squall line leading to a faster propagation speed for the storm complex. Radar ...

Robert G. Fovell; Gretchen L. Mullendore; Seung-Hee Kim

2006-12-01T23:59:59.000Z

333

PROPAGATION OF SINGULARITIES FOR ROUGH METRICS HART F. SMITH  

E-Print Network [OSTI]

PROPAGATION OF SINGULARITIES FOR ROUGH METRICS HART F. SMITH Abstract. We use a wave packet the Simons Foundation (# 266371 to Hart Smith). 1 #12;2 HART F. SMITH H¨ormander's theorem [9] on propagation

Smith, Hart F.

334

Method and apparatus for charged particle propagation  

DOE Patents [OSTI]

A method and apparatus are provided for propagating charged particles from a vacuum to a higher pressure region. A generator includes an evacuated chamber having a gun for discharging a beam of charged particles such as an electron beam or ion beam. The beam is discharged through a beam exit in the chamber into a higher pressure region. A plasma interface is disposed at the beam exit and includes a plasma channel for bounding a plasma maintainable between a cathode and an anode disposed at opposite ends thereof. The plasma channel is coaxially aligned with the beam exit for propagating the beam from the chamber, through the plasma, and into the higher pressure region. The plasma is effective for pumping down the beam exit for preventing pressure increase in the chamber and provides magnetic focusing of the beam discharged into the higher pressure region 24. 7 figs.

Hershcovitch, A.

1996-11-26T23:59:59.000Z

335

Observation of propagating edge spin waves modes  

SciTech Connect (OSTI)

Broadband magnetization response of equilateral triangular 1000 nm Permalloy dots has been studied under an in-plane magnetic field, applied parallel (buckle state), and perpendicular (Y state) to the triangles base. Micromagnetic simulations identify edge spin waves (E-SWs) in the buckle state as SWs propagating along the two adjacent edges. These quasi one-dimensional spin waves emitted by the vertex magnetic charges gradually transform from propagating to standing due to interference and are weakly affected by dipolar interdot interaction and variation of the aspect ratio. Spin waves in the Y state have a two dimensional character. These findings open perspectives for implementation of the E-SWs in magnonic crystals and thin films.

Lara, A.; Aliev, F. G., E-mail: farkhad.aliev@uam.es [Dpto. Física de la Materia Condensada C-III, Instituto Nicolas Cabrera (INC) and Condensed Matter Physics Institute (IFIMAC), Universidad Autónoma de Madrid, Madrid 28049 (Spain); Metlushko, V. [Department of Electrical and Computer Engineering, University of Illinois, Chicago, Illinois 60607 (United States)

2013-12-07T23:59:59.000Z

336

Characterization of penetration induced thermal runaway propagation process within a large format lithium ion battery module  

Science Journals Connector (OSTI)

Abstract This paper investigates the mechanisms of penetration induced thermal runaway (TR) propagation process within a large format lithium ion battery pack. A 6-battery module is built with 47 thermocouples installed at critical positions to record the temperature profiles. The first battery of the module is penetrated to trigger a TR propagation process. The temperature responses, the voltage responses and the heat transfer through different paths are analyzed and discussed to characterize the underlying physical behavior. The temperature responses show that: 1) Compared with the results of TR tests using accelerating rate calorimetry (ARC) with uniform heating, a lower onset temperature and a shorter TR triggering time are observed in a penetration induced TR propagation test due to side heating. 2) The maximum temperature difference within a battery can be as high as 791.8 °C in a penetration induced TR propagation test. The voltage responses have a 5-stage feature, indicating that the TR happens in sequence for the two pouch cells packed inside a battery. The heat transfer analysis shows that: 1) 12% of the total heat released in TR of a battery is enough to trigger the adjacent battery to TR. 2) The heat transferred through the pole connector is only about 1/10 of that through the battery shell. 3) The fire has little influence on the TR propagation, but may cause significant damage on the accessories located above the battery. The results can enhance our understandings of the mechanisms of TR propagation, and provide important guidelines in pack design for large format lithium ion battery.

Xuning Feng; Jing Sun; Minggao Ouyang; Fang Wang; Xiangming He; Languang Lu; Huei Peng

2015-01-01T23:59:59.000Z

337

High energy bosons do not propagate  

E-Print Network [OSTI]

We discuss the propagation of bosons (scalars, gauge fields and gravitons) at high energy in the context of the spectral action. Using heat kernel techniques, we find that in the high-momentum limit the quadratic part of the action does not contain positive powers of the derivatives. We interpret this as the fact that the two point Green functions vanish for nearby points, where the proximity scale is given by the inverse of the cutoff.

M. A. Kurkov; Fedele Lizzi; Dmitri Vassilevich

2013-12-08T23:59:59.000Z

338

Survey and Evaluate Uncertainty Quantification Methodologies  

SciTech Connect (OSTI)

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that will develop and deploy state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models with uncertainty quantification, optimization, risk analysis and decision making capabilities. The CCSI Toolset will incorporate commercial and open-source software currently in use by industry and will also develop new software tools as necessary to fill technology gaps identified during execution of the project. The CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. The goal of CCSI is to deliver a toolset that can simulate the scale-up of a broad set of new carbon capture technologies from laboratory scale to full commercial scale. To provide a framework around which the toolset can be developed and demonstrated, we will focus on three Industrial Challenge Problems (ICPs) related to carbon capture technologies relevant to U.S. pulverized coal (PC) power plants. Post combustion capture by solid sorbents is the technology focus of the initial ICP (referred to as ICP A). The goal of the uncertainty quantification (UQ) task (Task 6) is to provide a set of capabilities to the user community for the quantification of uncertainties associated with the carbon capture processes. As such, we will develop, as needed and beyond existing capabilities, a suite of robust and efficient computational tools for UQ to be integrated into a CCSI UQ software framework.

Lin, Guang; Engel, David W.; Eslinger, Paul W.

2012-02-01T23:59:59.000Z

339

Quantum Graphical Models and Belief Propagation  

SciTech Connect (OSTI)

Belief Propagation algorithms acting on Graphical Models of classical probability distributions, such as Markov Networks, Factor Graphs and Bayesian Networks, are amongst the most powerful known methods for deriving probabilistic inferences amongst large numbers of random variables. This paper presents a generalization of these concepts and methods to the quantum case, based on the idea that quantum theory can be thought of as a noncommutative, operator-valued, generalization of classical probability theory. Some novel characterizations of quantum conditional independence are derived, and definitions of Quantum n-Bifactor Networks, Markov Networks, Factor Graphs and Bayesian Networks are proposed. The structure of Quantum Markov Networks is investigated and some partial characterization results are obtained, along the lines of the Hammersley-Clifford theorem. A Quantum Belief Propagation algorithm is presented and is shown to converge on 1-Bifactor Networks and Markov Networks when the underlying graph is a tree. The use of Quantum Belief Propagation as a heuristic algorithm in cases where it is not known to converge is discussed. Applications to decoding quantum error correcting codes and to the simulation of many-body quantum systems are described.

Leifer, M.S. [Institute for Quantum Computing, University of Waterloo, 200 University Avenue West, Waterloo Ont., N2L 3G1 (Canada); Perimeter Institute for Theoretical Physics, 31 Caroline Street North, Waterloo Ont., N2L 2Y5 (Canada)], E-mail: matt@mattleifer.info; Poulin, D. [Center for the Physics of Information, California Institute of Technology, 1200 E. California Boulevard, 107-81, Pasadena, CA 91125 (United States)], E-mail: dpoulin@ist.caltech.edu

2008-08-15T23:59:59.000Z

340

Optimal investment and scheduling of distributed energy resources with uncertainty in electric vehicles driving schedules  

SciTech Connect (OSTI)

The large scale penetration of electric vehicles (EVs) will introduce technical challenges to the distribution grid, but also carries the potential for vehicle-to-grid services. Namely, if available in large enough numbers, EVs can be used as a distributed energy resource (DER) and their presence can influence optimal DER investment and scheduling decisions in microgrids. In this work, a novel EV fleet aggregator model is introduced in a stochastic formulation of DER-CAM [1], an optimization tool used to address DER investment and scheduling problems. This is used to assess the impact of EV interconnections on optimal DER solutions considering uncertainty in EV driving schedules. Optimization results indicate that EVs can have a significant impact on DER investments, particularly if considering short payback periods. Furthermore, results suggest that uncertainty in driving schedules carries little significance to total energy costs, which is corroborated by results obtained using the stochastic formulation of the problem.

Center for Energy and Innovative Technologies; NEC Laboratories America Inc.; Cardoso, Goncalo; Stadler, Michael; Bozchalui, Mohammed C.; Sharma, Ratnesh; Marnay, Chris; Barbosa-Povoa, Ana; Ferrao, Paulo

2013-10-27T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Benefits of dealing with uncertainty in greenhouse gas inventories: introduction  

SciTech Connect (OSTI)

The assessment of greenhouse gases emitted to and removed from the atmosphere is high on the international political and scientific agendas. Growing international concern and cooperation regarding the climate change problem have increased the need for policy-oriented solutions to the issue of uncertainty in, and related to, inventories of greenhouse gas (GHG) emissions. The approaches to addressing uncertainty discussed in this Special Issue reflect attempts to improve national inventories, not only for their own sake but also from a wider, systems analytical perspective-a perspective that seeks to strengthen the usefulness of national inventories under a compliance and/or global monitoring and reporting framework. These approaches demonstrate the benefits of including inventory uncertainty in policy analyses. The authors of the contributed papers show that considering uncertainty helps avoid situations that can, for example, create a false sense of certainty or lead to invalid views of subsystems. This may eventually prevent related errors from showing up in analyses. However, considering uncertainty does not come for free. Proper treatment of uncertainty is costly and demanding because it forces us to make the step from 'simple to complex' and only then to discuss potential simplifications. Finally, comprehensive treatment of uncertainty does not offer policymakers quick and easy solutions. The authors of the papers in this Special Issue do, however, agree that uncertainty analysis must be a key component of national GHG inventory analysis. Uncertainty analysis helps to provide a greater understanding and better science helps us to reduce and deal with uncertainty. By recognizing the importance of identifying and quantifying uncertainties, great strides can be made in ongoing discussions regarding GHG inventories and accounting for climate change. The 17 papers in this Special Issue deal with many aspects of analyzing and dealing with uncertainty in emissions estimates.

Jonas, Matthias [IIASA, Laxenburg, Austria; Winiwarter, Wilfried [AIT Austrian Institute of Technology, Vienna, Austria; Marland, Gregg [ORNL; White, Thomas [Canadian Forest Service; Nahorski, Zbigniew [Systems Research Institute, Polish Academy of Science, Warsaw, Poland; Bun, Rostyslav [Lviv Polytech National University, Lviv, Ukraine

2010-01-01T23:59:59.000Z

342

Jet energy scale uncertainty correlations between ATLAS and CMS  

E-Print Network [OSTI]

The correlation of the jet energy scale uncertainties between the ATLAS and CMS experiments are presented in this note. The uncertainty components for both experiments are grouped in categories. For each of these categories, the detailed comparison of the procedures to determine the jet calibration and its uncertainties allows to estimate a range for the correlation coefficient between the two experiments, ranging from 0 (uncorrelated) to 100\\% (fully correlated). This information can be used for the combination of ATLAS and CMS precision measurements.

The ATLAS collaboration

2014-01-01T23:59:59.000Z

343

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 1 September 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 September 8, 2010 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged about $77 per barrel in August 2010, very close to the July average, but $3 per barrel lower than projected in last month's Outlook. WTI spot prices averaged almost $82 per barrel over the first 10 days of August but then fell by $9 per barrel over the next 2 weeks as the market reacted to a series of reports of a stumbling economic recovery. EIA has lowered its average fourth quarter 2010 WTI spot price forecast to $77 per barrel, compared with $81 in last month's Outlook. WTI spot prices are projected to

344

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

October 2010 October 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 October 13, 2010 Release Crude Oil Prices. WTI oil prices averaged $75 per barrel in September but rose above $80 at the end of the month and into early October. EIA has raised the average fourth- quarter 2010 forecasted WTI spot price to $79 per barrel compared with $77 per barrel in last monthʹs Outlook. WTI spot prices are projected to rise to $85 per barrel by the fourth quarter of next year. As has been the case for most of 2010, WTI futures traded with a notable lack of volatility during the third quarter of 2010 (Figure 1). However, prices did bounce in

345

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

March 2010 March 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 March 9, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $76.39 per barrel in February 2010, almost $2 per barrel lower than the prior month's average and very near the $76 per barrel forecast in last month's Outlook. Last month, the WTI spot price reached a low of $71.15 on February 5 and peaked at $80.04 on February 22. EIA expects WTI prices to average above $80 per barrel this spring, rising to an average of about $82 per barrel by the end of the year and to $85 per barrel by the end of 2011 (West Texas Intermediate Crude Oil Price Chart).

346

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

November 2010 November 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 November 9, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged almost $82 per barrel in October, about $7 per barrel higher than the September average, as expectations of higher oil demand pushed up prices. EIA has raised the average fourth quarter 2010 WTI spot price forecast to about $83 per barrel compared with $79 per barrel in last monthʹs Outlook. WTI spot prices rise to $87 per barrel by the fourth quarter of next year. Projected WTI prices average $79 per barrel in 2010 and $85 per barrel in 2011. WTI futures for January 2011 delivery (for the 5-day period ending November 4)

347

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

May 2010 May 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 May 11, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $84 per barrel in April 2010, about $3 per barrel above the prior month's average and $2 per barrel higher than forecast in last month's Outlook. EIA projects WTI prices will average about $84 per barrel over the second half of this year and rise to $87 by the end of next year, an increase of about $2 per barrel from the previous Outlook (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown. Prices for near-term futures options contracts suggest that the market attaches

348

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

December 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 December 7, 2010 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged over $84 per barrel in November, more than $2 per barrel higher than the October average. EIA has raised the average winter 2010-2011 period WTI spot price forecast by $1 per barrel from the last monthʹs Outlook to $84 per barrel. WTI spot prices rise to $89 per barrel by the end of next year, $2 per barrel higher than in the last Outlook. Projected WTI prices average $79 per barrel in 2010 and $86 per barrel in 2011. WTI futures for February 2011 delivery during the 5-day period ending December 2

349

Microsoft Word - Price Uncertainty Supplement .docx  

Gasoline and Diesel Fuel Update (EIA)

1 1 1 January 2011 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 January 11, 2011 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged over $89 per barrel in December, about $5 per barrel higher than the November average. Expectations of higher oil demand, combined with unusually cold weather in both Europe and the U.S. Northeast, contributed to prices. EIA has raised the first quarter 2011 WTI spot price forecast by $8 per barrel from last monthʹs Outlook to $92 per barrel with a continuing rise to an average $99 per barrel in the fourth quarter of 2012. The projected annual average WTI price is $93 per barrel in 2011 and $98 per barrel in

350

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 1 June 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 June 8, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged less than $74 per barrel in May 2010, almost $11 per barrel below the prior month's average and $7 per barrel lower than forecast in last month's Outlook. EIA projects WTI prices will average about $79 per barrel over the second half of this year and rise to $84 by the end of next year, a decrease of about $3 per barrel from the previous Outlook (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown. Prices for near-term futures options contracts suggest that the market attaches

351

Uncertainty in climate science and climate policy  

E-Print Network [OSTI]

This essay, written by a statistician and a climate scientist, describes our view of the gap that exists between current practice in mainstream climate science, and the practical needs of policymakers charged with exploring possible interventions in the context of climate change. By `mainstream' we mean the type of climate science that dominates in universities and research centres, which we will term `academic' climate science, in contrast to `policy' climate science; aspects of this distinction will become clearer in what follows. In a nutshell, we do not think that academic climate science equips climate scientists to be as helpful as they might be, when involved in climate policy assessment. Partly, we attribute this to an over-investment in high resolution climate simulators, and partly to a culture that is uncomfortable with the inherently subjective nature of climate uncertainty.

Rougier, Jonathan

2014-01-01T23:59:59.000Z

352

Diffusion of irreversible energy technologies under uncertainty  

SciTech Connect (OSTI)

This paper presents a model of technology diffusion is consistent with characteristics of participants in most energy markets. Whereas the models used most widely for empirical research are based on the assumption that the extended delays in adoption of cost-saving innovations are the result of either lack of knowledge about the new processes or heterogeneity across potential adopters, the model presented in this paper is based on the strategic behavior by firms. The strategic interdependence of the firms` decisions is rooted in spillover effects associated with an inability to exclude others from the learning-by-doing acquired when a firm implements a new technology. The model makes extensive use of recent developments in investment theory as it relates irreversible investments under uncertainty.

Cacallo, J.D.; Sutherland, R.J.

1993-09-01T23:59:59.000Z

353

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

April 2010 April 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 April 6, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $81 per barrel in March 2010, almost $5 per barrel above the prior month's average and $3 per barrel higher than forecast in last month's Outlook. Oil prices rose from a low this year of $71.15 per barrel on February 5 to $80 per barrel by the end of February, generally on news of robust economic and energy demand growth in non-OECD Asia and the Middle East, and held near $81 until rising to $85 at the start of April. EIA expects WTI prices to average above $81 per barrel this summer, slightly less that $81 for 2010 as a whole,

354

Intrinsic Uncertainties in Modeling Complex Systems.  

SciTech Connect (OSTI)

Models are built to understand and predict the behaviors of both natural and artificial systems. Because it is always necessary to abstract away aspects of any non-trivial system being modeled, we know models can potentially leave out important, even critical elements. This reality of the modeling enterprise forces us to consider the prospective impacts of those effects completely left out of a model - either intentionally or unconsidered. Insensitivity to new structure is an indication of diminishing returns. In this work, we represent a hypothetical unknown effect on a validated model as a finite perturba- tion whose amplitude is constrained within a control region. We find robustly that without further constraints, no meaningful bounds can be placed on the amplitude of a perturbation outside of the control region. Thus, forecasting into unsampled regions is a very risky proposition. We also present inherent difficulties with proper time discretization of models and representing in- herently discrete quantities. We point out potentially worrisome uncertainties, arising from math- ematical formulation alone, which modelers can inadvertently introduce into models of complex systems. Acknowledgements This work has been funded under early-career LDRD project %23170979, entitled %22Quantify- ing Confidence in Complex Systems Models Having Structural Uncertainties%22, which ran from 04/2013 to 09/2014. We wish to express our gratitude to the many researchers at Sandia who con- tributed ideas to this work, as well as feedback on the manuscript. In particular, we would like to mention George Barr, Alexander Outkin, Walt Beyeler, Eric Vugrin, and Laura Swiler for provid- ing invaluable advice and guidance through the course of the project. We would also like to thank Steven Kleban, Amanda Gonzales, Trevor Manzanares, and Sarah Burwell for their assistance in managing project tasks and resources.

Cooper, Curtis S; Bramson, Aaron L.; Ames, Arlo L.

2014-09-01T23:59:59.000Z

355

Total Adjusted Sales of Kerosene  

U.S. Energy Information Administration (EIA) Indexed Site

End Use: Total Residential Commercial Industrial Farm All Other Period: End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

356

Solar total energy project Shenandoah  

SciTech Connect (OSTI)

This document presents the description of the final design for the Solar Total Energy System (STES) to be installed at the Shenandoah, Georgia, site for utilization by the Bleyle knitwear plant. The system is a fully cascaded total energy system design featuring high temperature paraboloidal dish solar collectors with a 235 concentration ratio, a steam Rankine cycle power conversion system capable of supplying 100 to 400 kW(e) output with an intermediate process steam take-off point, and a back pressure condenser for heating and cooling. The design also includes an integrated control system employing the supervisory control concept to allow maximum experimental flexibility. The system design criteria and requirements are presented including the performance criteria and operating requirements, environmental conditions of operation; interface requirements with the Bleyle plant and the Georgia Power Company lines; maintenance, reliability, and testing requirements; health and safety requirements; and other applicable ordinances and codes. The major subsystems of the STES are described including the Solar Collection Subysystem (SCS), the Power Conversion Subsystem (PCS), the Thermal Utilization Subsystem (TUS), the Control and Instrumentation Subsystem (CAIS), and the Electrical Subsystem (ES). Each of these sections include design criteria and operational requirements specific to the subsystem, including interface requirements with the other subsystems, maintenance and reliability requirements, and testing and acceptance criteria. (WHK)

None

1980-01-10T23:59:59.000Z

357

Grantee Total Number of Homes  

Broader source: Energy.gov (indexed) [DOE]

Grantee Grantee Total Number of Homes Weatherized through November 2011 [Recovery Act] Total Number of Homes Weatherized through November 2011 (Calendar Year 2009 - November 2011) [Recovery Act + Annual Program Funding] Alabama 6,704 7,867 1 Alaska 443 2,363 American Samoa 304 410 Arizona 6,354 7,518 Arkansas 5,231 6,949 California 41,649 50,002 Colorado 12,782 19,210 Connecticut 8,940 10,009 2 Delaware** 54 54 District of Columbia 962 1,399 Florida 18,953 20,075 Georgia 13,449 14,739 Guam 574 589 Hawaii 604 1,083 Idaho** 4,470 6,614 Illinois 35,530 44,493 Indiana** 18,768 21,689 Iowa 8,794 10,202 Kansas 6,339 7,638 Kentucky 7,639 10,902 Louisiana 4,698 6,946 Maine 5,130 6,664 Maryland 8,108 9,015 Massachusetts 17,687 21,645 Michigan 29,293 37,137 Minnesota 18,224 22,711 Mississippi 5,937 6,888 Missouri 17,334 20,319 Montana 3,310 6,860 Navajo Nation

358

Uncertainty relation for non-Hamiltonian quantum systems  

SciTech Connect (OSTI)

General forms of uncertainty relations for quantum observables of non-Hamiltonian quantum systems are considered. Special cases of uncertainty relations are discussed. The uncertainty relations for non-Hamiltonian quantum systems are considered in the Schroedinger-Robertson form since it allows us to take into account Lie-Jordan algebra of quantum observables. In uncertainty relations, the time dependence of quantum observables and the properties of this dependence are discussed. We take into account that a time evolution of observables of a non-Hamiltonian quantum system is not an endomorphism with respect to Lie, Jordan, and associative multiplications.

Tarasov, Vasily E. [Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow 119991 (Russian Federation)] [Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow 119991 (Russian Federation)

2013-01-15T23:59:59.000Z

359

Neutron reactions and climate uncertainties earn Los Alamos scientists...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

DOE Early Career awards Neutron reactions and climate uncertainties earn Los Alamos scientists DOE Early Career awards Marian Jandel and Nathan Urban are among the 61 national...

360

Uncertainties of coherent states for a generalized supersymmetric annihilation operator  

SciTech Connect (OSTI)

This study presents supersymmetric coherent states that are eigenstates of a general four-parameter family of annihilation operators. The elements of this family are defined as operators in Fock space that transform a subspace of a definite number of particles into a subspace with one particle removed. The emphasis is on classifying parameter space in various regions according to the uncertainty bounds of the corresponding coherent states. Specifically, the uncertainty in position-momentum is analyzed, with specific focus on characterizing regions of minimum uncertainty states, regions where the uncertainties are bounded from above, and where they grow unbound.

Kornbluth, Mordechai; Zypman, Fredy [Physics Department, Yeshiva University, 500 W 185th Street, New York, New York 10033 (United States)] [Physics Department, Yeshiva University, 500 W 185th Street, New York, New York 10033 (United States)

2013-01-15T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Variable Grid Method for Visualizing Uncertainty Associated with...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

This Return to Search Variable Grid Method for Visualizing Uncertainty Associated with Spatial Data A decision-making tool for industry,government, academia, and scientists...

362

Investment and Upgrade in Distributed Generation under Uncertainty  

E-Print Network [OSTI]

S. Irreversible investment in alternative projects. Economice Dixit, AK, Pindyck, RS. Investment under uncertainty.Maribu, KM, Wangensteen, I. Optimal investment strategies in

Siddiqui, Afzal

2008-01-01T23:59:59.000Z

363

Distributed Generation Investment by a Microgrid under Uncertainty  

E-Print Network [OSTI]

KM. Distributed generation investment and upgrade underin gas fired power plant investments. Review of Financial13] Dixit AK, Pindyck RS. Investment under uncertainty.

Siddiqui, Afzal

2008-01-01T23:59:59.000Z

364

Investment and Upgrade in Distributed Generation under Uncertainty  

E-Print Network [OSTI]

tax on microgrid combined heat and power adoption. JournalDG) and combined heat and power (CHP) applications via heatUncertainty Keywords: Combined heat and power applications,

Siddiqui, Afzal

2008-01-01T23:59:59.000Z

365

Substantive and Procedural Rationality in Decisions under Uncertainty  

E-Print Network [OSTI]

Income Inequality and Decision Theory Resolving the Allaisthe classical theory of decision making under uncertainty.1979) “Prospect Theory: An Analysis of Decision under Risk,”

Choi, Syngjoo; Fisman, Raymond; Gale, Douglass; Kariv, Sachar

2006-01-01T23:59:59.000Z

366

Characterizing Uncertainty for Regional Climate Change Mitigation and Adaptation Decisions  

SciTech Connect (OSTI)

This white paper describes the results of new research to develop an uncertainty characterization process to help address the challenges of regional climate change mitigation and adaptation decisions.

Unwin, Stephen D.; Moss, Richard H.; Rice, Jennie S.; Scott, Michael J.

2011-09-30T23:59:59.000Z

367

Optimization Online - The impact of wind uncertainty on the strategic ...  

E-Print Network [OSTI]

Jan 14, 2015 ... Abstract: The intermittent nature of wind energy generation has introduced a new degree of uncertainty to the tactical planning of energy ...

Pedro Crespo Del Granado

2015-01-14T23:59:59.000Z

368

Uncertainty Quantification for Nano-Scale Integrated Circuits...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Uncertainty Quantification for Nano-Scale Integrated Circuits and MEMS Design Event Sponsor: Mathematics and Computing Science Seminar Start Date: Jan 20 2015 - 10:30am Building...

369

Robust Optimization under Multi-band Uncertainty Part I: Theory ?  

E-Print Network [OSTI]

rithms for the design of robust and survivable networks, in collaboration with ... problems), where the uncertainty set has been defined in collaboration with our.

2013-03-14T23:59:59.000Z

370

Diffusive Propagation of Ultra-High-Energy Cosmic Rays and the Propagation Theorem  

Science Journals Connector (OSTI)

We present a detailed analytical study of the propagation of ultra-high-energy (UHE) particles in extragalactic magnetic fields. The crucial parameter that affects the diffuse spectrum is the separation between sources. In the case of a uniform distribution of sources with a separation between them much smaller than all characteristic propagation lengths, the diffuse spectrum of UHE particles has a universal form, independent of the mode of propagation. This statement has the status of theorem. The proof is obtained using the particle number conservation during propagation and also using the kinetic equation for the propagation of UHE particles. This theorem can be also proved with the help of the diffusion equation. In particular, it is shown numerically how the diffuse fluxes converge to this universal spectrum, when the separation between sources diminishes. We study also the analytic solution of the diffusion equation in weak and strong magnetic fields with energy losses taken into account. In the case of strong magnetic fields and for a separation between sources large enough, the GZK cutoff can practically disappear, as it has been found early in numerical simulations. In practice, however, the source luminosities required are too large for this possibility.

R. Aloisio; V. Berezinsky

2004-01-01T23:59:59.000Z

371

Total Number of Operable Refineries  

U.S. Energy Information Administration (EIA) Indexed Site

Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge Capacity (B/SD) Thermal Cracking Downstream Charge Capacity (B/SD) Thermal Cracking Total Coking Downstream Charge Capacity (B/SD) Thermal Cracking Delayed Coking Downstream Charge Capacity (B/SD Thermal Cracking Fluid Coking Downstream Charge Capacity (B/SD) Thermal Cracking Visbreaking Downstream Charge Capacity (B/SD) Thermal Cracking Other/Gas Oil Charge Capacity (B/SD) Catalytic Cracking Fresh Feed Charge Capacity (B/SD) Catalytic Cracking Recycle Charge Capacity (B/SD) Catalytic Hydro-Cracking Charge Capacity (B/SD) Catalytic Hydro-Cracking Distillate Charge Capacity (B/SD) Catalytic Hydro-Cracking Gas Oil Charge Capacity (B/SD) Catalytic Hydro-Cracking Residual Charge Capacity (B/SD) Catalytic Reforming Charge Capacity (B/SD) Catalytic Reforming Low Pressure Charge Capacity (B/SD) Catalytic Reforming High Pressure Charge Capacity (B/SD) Catalytic Hydrotreating/Desulfurization Charge Capacity (B/SD) Catalytic Hydrotreating Naphtha/Reformer Feed Charge Cap (B/SD) Catalytic Hydrotreating Gasoline Charge Capacity (B/SD) Catalytic Hydrotreating Heavy Gas Oil Charge Capacity (B/SD) Catalytic Hydrotreating Distillate Charge Capacity (B/SD) Catalytic Hydrotreating Kerosene/Jet Fuel Charge Capacity (B/SD) Catalytic Hydrotreating Diesel Fuel Charge Capacity (B/SD) Catalytic Hydrotreating Other Distillate Charge Capacity (B/SD) Catalytic Hydrotreating Residual/Other Charge Capacity (B/SD) Catalytic Hydrotreating Residual Charge Capacity (B/SD) Catalytic Hydrotreating Other Oils Charge Capacity (B/SD) Fuels Solvent Deasphalting Charge Capacity (B/SD) Catalytic Reforming Downstream Charge Capacity (B/CD) Total Coking Downstream Charge Capacity (B/CD) Catalytic Cracking Fresh Feed Downstream Charge Capacity (B/CD) Catalytic Hydro-Cracking Downstream Charge Capacity (B/CD) Period:

372

Observations of the Li, Be, and B isotopes and Constraints on Cosmic-ray Propagation  

SciTech Connect (OSTI)

The abundance of Li, Be, and B isotopes in galactic cosmic rays (GCR) between E=50-200 MeV/nucleon has been observed by the Cosmic Ray Isotope Spectrometer (CRIS) on NASA's ACE mission since 1997 with high statistical accuracy. Precise observations of Li, Be, B can be used to constrain GCR propagation models. We find that a diffusive reacceleration model with parameters that best match CRIS results (e.g. B/C, Li/C, etc) are also consistent with other GCR observations. A {approx}15-20% overproduction of Li and Be in the model predictions is attributed to uncertainties in the production cross-section data. The latter becomes a significant limitation to the study of rare GCR species that are generated predominantly via spallation.

de Nolfo, Georgia A.; Moskalenko, I.V.; Binns, W.R.; Christian, E.R.; Cummings, A.C.; Davis, A.J.; George, J.S.; Hink, P.L.; Israel, M.H.; Leske, R.A.; Lijowski, M.; Mewaldt, R.A.; Stone, E.C.; Strong, A.W.; von Rosenvinge, T.T.; Wiedenbeck, M.E.; Yanasak, N.E.; /NASA, Goddard /Stanford U., HEPL /Washington U., St. Louis /NASA, Headquarters/Caltech, SRL /Aerospace Corp. /Garching, Max Planck Inst., MPE /Caltech, JPL; ,

2006-11-15T23:59:59.000Z

373

Total quality management implementation guidelines  

SciTech Connect (OSTI)

These Guidelines were designed by the Energy Quality Council to help managers and supervisors in the Department of Energy Complex bring Total Quality Management to their organizations. Because the Department is composed of a rich mixture of diverse organizations, each with its own distinctive culture and quality history, these Guidelines are intended to be adapted by users to meet the particular needs of their organizations. For example, for organizations that are well along on their quality journeys and may already have achieved quality results, these Guidelines will provide a consistent methodology and terminology reference to foster their alignment with the overall Energy quality initiative. For organizations that are just beginning their quality journeys, these Guidelines will serve as a startup manual on quality principles applied in the Energy context.

Not Available

1993-12-01T23:59:59.000Z

374

Extension of EU Emissions Trading Scheme to Other Sectors and Gases: Consequences for Uncertainty of Total Tradable Amount  

Science Journals Connector (OSTI)

Emissions trading in the European Union (EU), covering...2...from combustion and selected industrial processes in large installations), began in 2005. During the first commitment period of the Kyoto Protocol (200...

S. Monni; S. Syri; R. Pipatti; I. Savolainen

2007-01-01T23:59:59.000Z

375

Extension of EU Emissions Trading Scheme to Other Sectors and Gases: Consequences for Uncertainty of Total Tradable Amount  

Science Journals Connector (OSTI)

Emissions trading in the European Union (EU), covering...2...from combustion and selected industrial processes in large installations), began in 2005. During the first commitment period of the Kyoto Protocol (200...

S. Monni; S. Syri; R. Pipatti; I. Savolainen

2007-09-01T23:59:59.000Z

376

Probabilistic accident consequence uncertainty analysis -- Early health effects uncertainty assessment. Volume 2: Appendices  

SciTech Connect (OSTI)

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA early health effects models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on early health effects, (4) short biographies of the experts, and (5) the aggregated results of their responses.

Haskin, F.E. [Univ. of New Mexico, Albuquerque, NM (United States); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Goossens, L.H.J.; Kraan, B.C.P. [Delft Univ. of Technology (Netherlands)

1997-12-01T23:59:59.000Z

377

Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for internal dosimetry. Volume 2: Appendices  

SciTech Connect (OSTI)

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA internal dosimetry models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on internal dosimetry, (4) short biographies of the experts, and (5) the aggregated results of their responses.

Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Harrison, J.D. [National Radiological Protection Board (United Kingdom); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

1998-04-01T23:59:59.000Z

378

COMPARING FRACTURE PROPAGATION TESTS AND RELATING TEST RESULTS TO SNOWPACK CHARACTERISTICS  

E-Print Network [OSTI]

COMPARING FRACTURE PROPAGATION TESTS AND RELATING TEST RESULTS TO SNOWPACK CHARACTERISTICS Cameron for a slab and weak layer combination to propagate a fracture. University of Calgary researchers performed propensity. KEYWORDS: fracture propagation, snowpack stability test, extended column test, propagation saw

Jamieson, Bruce

379

Total Heart Transplant: A Modern Overview  

E-Print Network [OSTI]

use of the total artificial heart. New England Journal ofJ. (1997). Artificial heart transplants. British medicala total artificial heart as a bridge to transplantation. New

Lingampalli, Nithya

2014-01-01T23:59:59.000Z

380

Uncertainty in projected impacts of climate change on water  

E-Print Network [OSTI]

Global Carbon Project · Scenarios trends are averages across all models available for each scenario class1928 2000 Uncertainty in projected impacts of climate change on water Uncertainty in projected-2004Observed Changes: 1970-2004 · High confidence changes in: ­ rainfall intensity ­ extreme temperatures

Maurer,. Edwin P.

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Climate Change Uncertainty and Skepticism: A Cross-Country Analysis  

E-Print Network [OSTI]

Climate Change Uncertainty and Skepticism: A Cross-Country Analysis Skepticism about climate change for other countries. · Skepticism and uncertainty are related but different aspects of climate change perceptions. In the literature, skepticism often relates to whether people believe climate change is happening

Hall, Sharon J.

382

Bayesian System Identification and Response Predictions Robust to Modeling Uncertainty  

E-Print Network [OSTI]

uncertainties, both prior (e.g. design based on reliability or life-cycle cost optimization), & posterior (e reliability of treating excitation uncertainty under wind and earthquakes (random vibrations, stochastic in the development and use of Bayesian methods in the last decade or so · Allows analysis that is robust to modeling

Beck, James L.

383

Examining Uncertainty in Demand Response Baseline Models and  

E-Print Network [OSTI]

LBNL-5096E Examining Uncertainty in Demand Response Baseline Models and Variability in Automated of California. #12;Examining Uncertainty in Demand Response Baseline Models and Variability in Automated.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR

384

Policy Uncertainty and Cross-Border Flows of BRANDON JULIO  

E-Print Network [OSTI]

Policy Uncertainty and Cross-Border Flows of Capital BRANDON JULIO London Business School YOUNGSUK YOOK Sungkyunkwan University September 2011 ABSTRACT We find that policy uncertainty is an important determinant of fluctuations in cross- border flows of capital. Spefically, we find that fluctuations in policy

University of Technology, Sydney

385

Offshore Oilfield Development Planning under Uncertainty and Fiscal Considerations  

E-Print Network [OSTI]

1 Offshore Oilfield Development Planning under Uncertainty and Fiscal Considerations Vijay Gupta1 of uncertainty and complex fiscal rules in the development planning of offshore oil and gas fields which involve, Offshore Oil and Gas, Multistage Stochastic, Endogenous, Production Sharing Agreements (PSAs) 1

Grossmann, Ignacio E.

386

Uncertainties in the Anti-neutrino Production at Nuclear Reactors  

E-Print Network [OSTI]

Anti-neutrino emission rates from nuclear reactors are determined from thermal power measurements and fission rate calculations. The uncertainties in these quantities for commercial power plants and their impact on the calculated interaction rates in electron anti-neutrino detectors is examined. We discuss reactor-to-reactor correlations between the leading uncertainties and their relevance to reactor anti-neutrino experiments.

Z. Djurcic; J. A. Detwiler; A. Piepke; V. R. Foster Jr.; L. Miller; G. Gratta

2008-08-06T23:59:59.000Z

387

Investment under uncertainty, competition and regulation Adrien Nguyen Huu1  

E-Print Network [OSTI]

Investment under uncertainty, competition and regulation Adrien Nguyen Huu1 1 IMPA, Estrada Dona of preemptive investment. We recall the rigorous framework of M. Grasselli, V. Lecl`ere and M. Ludkovsky investment valuation. The latter uses recent methods from stochastic finance to price uncertainty

Paris-Sud XI, Université de

388

Evolution of Schrodinger Uncertainty Relation in Quantum Mechanics  

E-Print Network [OSTI]

In the present article, we discuss one of the basic relations of Quantum Mechanics - the Uncertainty Relation (UR). In 1930, few years after Heisenberg, Erwin Schrodinger generalized the famous Uncertainty Relation in Quantum Mechanics, making it more precise than the original. The present study discusses recent generalizations of Schrodinger's work and explains why his paper remains almost forgotten in the last century.

A Angelow

2008-06-07T23:59:59.000Z

389

Total and spontaneous fission half-lives of the americium and curium nuclides  

SciTech Connect (OSTI)

The total half-life and the half-life for spontaneous fission are evaluated for the various long-lived nuclides of interest. Recommended values are presented for /sup 241/Am, /sup 242m/Am, /sup 243/Am, /sup 242/Cm, /sup 243/Cm, /sup 244/Cm, /sup 245/Cm, /sup 246/Cm, /sup 247/Cm, /sup 248/Cm, and /sup 250/Cm. The uncertainties are provided at the 95% confidence limit for each of the recommended values.

Holden, N.E.

1984-01-01T23:59:59.000Z

390

Design Feasibility Analysis and Optimization under Uncertainty - A Bayesian  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Design Feasibility Analysis and Optimization under Uncertainty - A Bayesian Design Feasibility Analysis and Optimization under Uncertainty - A Bayesian Optimal Decision Framework Speaker(s): Jose M. Ortega Date: October 7, 2003 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Michael Sohn A new approach to the problem of identifying design feasibility and optimality under uncertainty is introduced. Based on the Bayesian concepts of predictive probability and expected utility, the method can quantify the feasibility of a process design and identify the optimal operation conditions when there are uncertainties in the process parameters. The use of Bayesian statistics enables the treatment of a very wide class of parameter uncertainties, including simple bounds, analytic probability density functions, correlation structures and empirical distributions.

391

Avoiding climate change uncertainties in Strategic Environmental Assessment  

SciTech Connect (OSTI)

This article is concerned with how Strategic Environmental Assessment (SEA) practice handles climate change uncertainties within the Danish planning system. First, a hypothetical model is set up for how uncertainty is handled and not handled in decision-making. The model incorporates the strategies ‘reduction’ and ‘resilience’, ‘denying’, ‘ignoring’ and ‘postponing’. Second, 151 Danish SEAs are analysed with a focus on the extent to which climate change uncertainties are acknowledged and presented, and the empirical findings are discussed in relation to the model. The findings indicate that despite incentives to do so, climate change uncertainties were systematically avoided or downplayed in all but 5 of the 151 SEAs that were reviewed. Finally, two possible explanatory mechanisms are proposed to explain this: conflict avoidance and a need to quantify uncertainty.

Larsen, Sanne Vammen, E-mail: sannevl@plan.aau.dk [The Danish Centre for Environmental Assessment, Aalborg University-Copenhagen, A.C. Meyers Vænge 15, 2450 København SV (Denmark); Kørnøv, Lone, E-mail: lonek@plan.aau.dk [The Danish Centre for Environmental Assessment, Aalborg University, Skibbrogade 5, 1. Sal, 9000 Aalborg (Denmark)] [The Danish Centre for Environmental Assessment, Aalborg University, Skibbrogade 5, 1. Sal, 9000 Aalborg (Denmark); Driscoll, Patrick, E-mail: patrick@plan.aau.dk [The Danish Centre for Environmental Assessment, Aalborg University-Copenhagen, A.C. Meyers Vænge 15, 2450 København SV (Denmark)] [The Danish Centre for Environmental Assessment, Aalborg University-Copenhagen, A.C. Meyers Vænge 15, 2450 København SV (Denmark)

2013-11-15T23:59:59.000Z

392

Total Imports of Residual Fuel  

Gasoline and Diesel Fuel Update (EIA)

May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 View May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 View History U.S. Total 5,752 5,180 7,707 9,056 6,880 6,008 1936-2013 PAD District 1 1,677 1,689 2,008 3,074 2,135 2,814 1981-2013 Connecticut 1995-2009 Delaware 1995-2012 Florida 359 410 439 392 704 824 1995-2013 Georgia 324 354 434 364 298 391 1995-2013 Maine 65 1995-2013 Maryland 1995-2013 Massachusetts 1995-2012 New Hampshire 1995-2010 New Jersey 903 756 948 1,148 1,008 1,206 1995-2013 New York 21 15 14 771 8 180 1995-2013 North Carolina 1995-2011 Pennsylvania 1995-2013 Rhode Island 1995-2013 South Carolina 150 137 194 209 1995-2013 Vermont 5 4 4 5 4 4 1995-2013 Virginia 32 200 113 1995-2013 PAD District 2 217 183 235 207 247 179 1981-2013 Illinois 1995-2013

393

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Noyes, MN Warroad, MN Babb, MT Port of Del Bonita, MT Port of Morgan, MT Sweetgrass, MT Whitlash, MT Portal, ND Sherwood, ND Pittsburg, NH Champlain, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Highgate Springs, VT U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Galvan Ranch, TX LNG Imports from Algeria LNG Imports from Australia LNG Imports from Brunei LNG Imports from Canada Highgate Springs, VT LNG Imports from Egypt Cameron, LA Elba Island, GA Freeport, TX Gulf LNG, MS LNG Imports from Equatorial Guinea LNG Imports from Indonesia LNG Imports from Malaysia LNG Imports from Nigeria Cove Point, MD LNG Imports from Norway Cove Point, MD Freeport, TX Sabine Pass, LA LNG Imports from Oman LNG Imports from Peru Cameron, LA Freeport, TX LNG Imports from Qatar Elba Island, GA Golden Pass, TX Sabine Pass, LA LNG Imports from Trinidad/Tobago Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf LNG, MS Lake Charles, LA Sabine Pass, LA LNG Imports from United Arab Emirates LNG Imports from Yemen Everett, MA Freeport, TX Sabine Pass, LA LNG Imports from Other Countries Period: Monthly Annual

394

Natural Gas Total Liquids Extracted  

U.S. Energy Information Administration (EIA) Indexed Site

Thousand Barrels) Thousand Barrels) Data Series: Natural Gas Processed Total Liquids Extracted NGPL Production, Gaseous Equivalent Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2007 2008 2009 2010 2011 2012 View History U.S. 658,291 673,677 720,612 749,095 792,481 873,563 1983-2012 Alabama 13,381 11,753 11,667 13,065 1983-2010 Alaska 22,419 20,779 19,542 17,798 18,314 18,339 1983-2012 Arkansas 126 103 125 160 212 336 1983-2012 California 11,388 11,179 11,042 10,400 9,831 9,923 1983-2012 Colorado 27,447 37,804 47,705 57,924 1983-2010 Florida 103 16 1983-2008 Illinois 38 33 24 231 705 0 1983-2012

395

Accounting for Global Climate Model Projection Uncertainty in Modern Statistical Downscaling  

SciTech Connect (OSTI)

Future climate change has emerged as a national and a global security threat. To carry out the needed adaptation and mitigation steps, a quantification of the expected level of climate change is needed, both at the global and the regional scale; in the end, the impact of climate change is felt at the local/regional level. An important part of such climate change assessment is uncertainty quantification. Decision and policy makers are not only interested in 'best guesses' of expected climate change, but rather probabilistic quantification (e.g., Rougier, 2007). For example, consider the following question: What is the probability that the average summer temperature will increase by at least 4 C in region R if global CO{sub 2} emission increases by P% from current levels by time T? It is a simple question, but one that remains very difficult to answer. It is answering these kind of questions that is the focus of this effort. The uncertainty associated with future climate change can be attributed to three major factors: (1) Uncertainty about future emission of green house gasses (GHG). (2) Given a future GHG emission scenario, what is its impact on the global climate? (3) Given a particular evolution of the global climate, what does it mean for a particular location/region? In what follows, we assume a particular GHG emission scenario has been selected. Given the GHG emission scenario, the current batch of the state-of-the-art global climate models (GCMs) is used to simulate future climate under this scenario, yielding an ensemble of future climate projections (which reflect, to some degree our uncertainty of being able to simulate future climate give a particular GHG scenario). Due to the coarse-resolution nature of the GCM projections, they need to be spatially downscaled for regional impact assessments. To downscale a given GCM projection, two methods have emerged: dynamical downscaling and statistical (empirical) downscaling (SDS). Dynamic downscaling involves configuring and running a regional climate model (RCM) nested within a given GCM projection (i.e., the GCM provides bounder conditions for the RCM). On the other hand, statistical downscaling aims at establishing a statistical relationship between observed local/regional climate variables of interest and synoptic (GCM-scale) climate predictors. The resulting empirical relationship is then applied to future GCM projections. A comparison of the pros and cons of dynamical versus statistical downscaling is outside the scope of this effort, but has been extensively studied and the reader is referred to Wilby et al. (1998); Murphy (1999); Wood et al. (2004); Benestad et al. (2007); Fowler et al. (2007), and references within those. The scope of this effort is to study methodology, a statistical framework, to propagate and account for GCM uncertainty in regional statistical downscaling assessment. In particular, we will explore how to leverage an ensemble of GCM projections to quantify the impact of the GCM uncertainty in such an assessment. There are three main component to this effort: (1) gather the necessary climate-related data for a regional SDS study, including multiple GCM projections, (2) carry out SDS, and (3) assess the uncertainty. The first step is carried out using tools written in the Python programming language, while analysis tools were developed in the statistical programming language R; see Figure 1.

Johannesson, G

2010-03-17T23:59:59.000Z

396

Dark Energy from Quantum Uncertainty of Simultaneity  

E-Print Network [OSTI]

The observed acceleration expansion of the universe was thought attribute to a mysterious dark energy in the framework of the classical general relativity. The dark energy behaves very similar with a vacuum energy in quantum mechanics. However, once the quantum effects are seriously taken into account, it predicts a wrong order of the vacuum energy and leads to a severe fine-tuning, known as the cosmological constant problem. We abandon the standard interpretation that time is a global parameter in quantum mechanics, replace it by a quantum dynamical variable playing the role of an operational quantum clock system. In the framework of reinterpretation of time, we find that the synchronization of two quantum clocks distance apart can not be realized in all rigor at quantum level. Thus leading to an intrinsic quantum uncertainty of simultaneity between spatial interval, which implies a visional vacuum energy fluctuation and gives an observed dark energy density $\\rho_{de}=\\frac{6}{\\pi}L_{P}^{-2}L_{H}^{-2}$, whe...

Luo, M J

2014-01-01T23:59:59.000Z

397

Clustering and Uncertainty in Perfect Chaos Systems  

E-Print Network [OSTI]

The goal of this investigation was to derive strictly new properties of chaotic systems and their mutual relations. The generalized Fokker-Planck equation with a non stationary diffusion has been derived and used for chaos analysis. An anomalous transport turned out to be natural property of this equation. A nonlinear dispersion of the considered motion allowed to find a principal consequence: a chaotic system with uniform dynamic properties tends to unstable clustering. Small fluctuations of particles density increase by time and form attractors and stochastic islands even if the initial transport properties have uniform distribution. It was shown that an instability of phase trajectories leads to the nonlinear dispersion law and consequently to a space instability. A fixed boundary system was considered, using a standard Fokker-Planck equation. We have derived that such a type of dynamic systems has a discrete diffusive and energy spectra. It was shown that phase space diffusion is the only parameter that defines a dynamic accuracy in this case. The uncertainty relations have been obtained for conjugate phase space variables with account of transport properties. Given results can be used in the area of chaotic systems modelling and turbulence investigation.

Sergey A. Kamenshchikov

2014-07-27T23:59:59.000Z

398

Method and apparatus for charged particle propagation  

DOE Patents [OSTI]

A method and apparatus are provided for propagating charged particles from a vacuum to a higher pressure region. A generator 14,14b includes an evacuated chamber 16a,b having a gun 18,18b for discharging a beam of charged particles such as an electron beam 12 or ion beam 12b. The beam 12,12b is discharged through a beam exit 22 in the chamber 16a,b into a higher pressure region 24. A plasma interface 34 is disposed at the beam exit 22 and includes a plasma channel 38 for bounding a plasma 40 maintainable between a cathode 42 and an anode 44 disposed at opposite ends thereof. The plasma channel 38 is coaxially aligned with the beam exit 22 for propagating the beam 12,12b from the chamber 16a,b, through the plasma 40, and into the higher pressure region 24. The plasma 40 is effective for pumping down the beam exit 22 for preventing pressure increase in the chamber 16a,b, and provides magnetic focusing of the beam 12,12b discharged into the higher pressure region 24.

Hershcovitch, Ady (Mount Sinai, NY)

1996-11-26T23:59:59.000Z

399

Total Petroleum Systems and Assessment Units (AU)  

E-Print Network [OSTI]

Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Surface water Groundwater X X X X X X X X AU 00000003 Oil/ Gas X X X X X X X X Total X X X X X X X Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Total undiscovered petroleum (MMBO or BCFG) Water per oil

Torgersen, Christian

400

Locating and total dominating sets in trees  

Science Journals Connector (OSTI)

A set S of vertices in a graph G = ( V , E ) is a total dominating set of G if every vertex of V is adjacent to a vertex in S. We consider total dominating sets of minimum cardinality which have the additional property that distinct vertices of V are totally dominated by distinct subsets of the total dominating set.

Teresa W. Haynes; Michael A. Henning; Jamie Howard

2006-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Propagation and structure of planar streamer fronts  

Science Journals Connector (OSTI)

Streamers are a mode of dielectric breakdown of a gas in a strong electric field: A sharp nonlinear ionization wave propagates into a nonionized gas, leaving a nonequilibrium plasma behind. The ionization avalanche in the tip of the wave is due to free electrons being accelerated in the strong field and ionizing the gas by impact. This chain reaction deeper in the wave is suppressed by the generated free charges screening the field. Simulations of streamers show two widely separated spatial scales: the width of the charged layer where the electron density gradients and the ionization rate are very large [O(?m)], and the width of the electrically screened, finger-shaped, and ionized region [O(mm)]. We thus recently have suggested analyzing first the properties of the charge-ionization layer on the inner scale on which it is almost planar, and then understanding the streamer shape on the outer scale as the motion of an effective interface, as is done in other examples of nonequilibrium pattern formation. The first step thus is the analysis of the inner dynamics of planar streamer fronts. For these, we resolve the long-standing question about what determines the front speed, by applying the modern insights of pattern formation to the streamer equations used in the recent simulations. These include field-driven impact ionization, electron drift and diffusion, and the Poisson equation for the electric field. First, in appropriately chosen dimensionless units only one parameter remains to characterize the gas, the dimensionless electron diffusion constant D; for typical gases under normal conditions D?0.1–0.3. Then we determine essentially all relevant properties of planar streamer fronts. Technically, we identify the propagation of streamer fronts as an example of front propagation into unstable states. In terms of the marginal stability scenario we then find that the front approached asymptotically starting from any sufficiently localized initial condition (the ``selected front'') is the steepest uniformly translating front solution, which is physical and stable. Negatively charged fronts are selected by linear marginal stability, which allows us to derive their velocity analytically. Positively charged fronts can only propagate due to electron diffusion against the electric field; as a result their behavior is singular in the limit of D?0. For D?1, these fronts are selected by nonlinear marginal stability and we have to apply numerical methods for predicting the selected front velocity. For larger D, linear marginal stability applies and the velocity can be determined analytically. Numerical integrations of the temporal evolution of planar fronts out of localized initial conditions confirm all our analytical and numerical predictions for the selection. Finally, our general predictions for the selected front velocity and for the degree of ionization of the plasma are in semiquantitative agreement with recent numerical solutions of three-dimensional streamer propagation. This gives credence to our suggestion that the front analysis on the inner (?m) scale yields the moving boundary conditions for a moving ``streamer interface,'' whose pattern formation is governed by the evolution of the fields on the outer (mm) scale.

Ute Ebert, Wim van Saarloos, and Christiane Caroli

1997-02-01T23:59:59.000Z

402

Shallow Water Model which Admit a Propagation of Shocks over a Dry Bed  

Science Journals Connector (OSTI)

A method for modeling the propagation of hydraulic bores over a dry bed using the first approximation of shallow water theory is proposed. The method is based on a modified conservation law of total momentum that takes into account the concentrated momentum losses due to the formation of local turbulent vortex structures in the fluid surface layer at a hydraulic bore front. A quantitative estimate of these losses is obtained by deriving the shallow water equations from the Navier?Stokes equations with allowance for viscosity which has a rapidly increasing effect in the turbulent flow regions described in theory as shocks. A comparative analysis is performed for the modeling of the dam?break problem experimentally and theoretically by the help of the classical and modified shallow water equations. Numerical results are presented for the propagation over a dry bed of a two?dimensional shock arising in a partial dam break in a channel with sloping bottom in the lower pool.

2010-01-01T23:59:59.000Z

403

Locating-total domination in graphs  

Science Journals Connector (OSTI)

In this paper, we continue the study of locating-total domination in graphs. A set S of vertices in a graph G is a total dominating set in G if every vertex of G is adjacent to a vertex in S . We consider total dominating sets S which have the additional property that distinct vertices in V ( G ) ? S are totally dominated by distinct subsets of the total dominating set. Such a set S is called a locating-total dominating set in G , and the locating-total domination number of G is the minimum cardinality of a locating-total dominating set in G . We obtain new lower and upper bounds on the locating-total domination number of a graph. Interpolation results are established, and the locating-total domination number in special families of graphs, including cubic graphs and grid graphs, is investigated.

Michael A. Henning; Nader Jafari Rad

2012-01-01T23:59:59.000Z

404

Grid and basis adaptive polynomial chaos techniques for sensitivity and uncertainty analysis  

SciTech Connect (OSTI)

The demand for accurate and computationally affordable sensitivity and uncertainty techniques is constantly on the rise and has become especially pressing in the nuclear field with the shift to Best Estimate Plus Uncertainty methodologies in the licensing of nuclear installations. Besides traditional, already well developed methods – such as first order perturbation theory or Monte Carlo sampling – Polynomial Chaos Expansion (PCE) has been given a growing emphasis in recent years due to its simple application and good performance. This paper presents new developments of the research done at TU Delft on such Polynomial Chaos (PC) techniques. Our work is focused on the Non-Intrusive Spectral Projection (NISP) approach and adaptive methods for building the PCE of responses of interest. Recent efforts resulted in a new adaptive sparse grid algorithm designed for estimating the PC coefficients. The algorithm is based on Gerstner's procedure for calculating multi-dimensional integrals but proves to be computationally significantly cheaper, while at the same it retains a similar accuracy as the original method. More importantly the issue of basis adaptivity has been investigated and two techniques have been implemented for constructing the sparse PCE of quantities of interest. Not using the traditional full PC basis set leads to further reduction in computational time since the high order grids necessary for accurately estimating the near zero expansion coefficients of polynomial basis vectors not needed in the PCE can be excluded from the calculation. Moreover the sparse PC representation of the response is easier to handle when used for sensitivity analysis or uncertainty propagation due to the smaller number of basis vectors. The developed grid and basis adaptive methods have been implemented in Matlab as the Fully Adaptive Non-Intrusive Spectral Projection (FANISP) algorithm and were tested on four analytical problems. These show consistent good performance both in terms of the accuracy of the resulting PC representation of quantities and the computational costs associated with constructing the sparse PCE. Basis adaptivity also seems to make the employment of PC techniques possible for problems with a higher number of input parameters (15–20), alleviating a well known limitation of the traditional approach. The prospect of larger scale applicability and the simplicity of implementation makes such adaptive PC algorithms particularly appealing for the sensitivity and uncertainty analysis of complex systems and legacy codes.

Perkó, Zoltán, E-mail: Z.Perko@tudelft.nl; Gilli, Luca, E-mail: Gilli@nrg.eu; Lathouwers, Danny, E-mail: D.Lathouwers@tudelft.nl; Kloosterman, Jan Leen, E-mail: J.L.Kloosterman@tudelft.nl

2014-03-01T23:59:59.000Z

405

Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 2: Appendices  

SciTech Connect (OSTI)

This volume is the second of a two-volume document that summarizes a joint project by the US Nuclear Regulatory and the Commission of European Communities to assess uncertainties in the MACCS and COSYMA probabilistic accident consequence codes. These codes were developed primarily for estimating the risks presented by nuclear reactors based on postulated frequencies and magnitudes of potential accidents. This two-volume report, which examines mechanisms and uncertainties of transfer through the food chain, is the first in a series of five such reports. A panel of sixteen experts was formed to compile credible and traceable uncertainty distributions for food chain transfer that affect calculations of offsite radiological consequences. Seven of the experts reported on transfer into the food chain through soil and plants, nine reported on transfer via food products from animals, and two reported on both. The expert judgment elicitation procedure and its outcomes are described in these volumes. This volume contains seven appendices. Appendix A presents a brief discussion of the MAACS and COSYMA model codes. Appendix B is the structure document and elicitation questionnaire for the expert panel on soils and plants. Appendix C presents the rationales and responses of each of the members of the soils and plants expert panel. Appendix D is the structure document and elicitation questionnaire for the expert panel on animal transfer. The rationales and responses of each of the experts on animal transfer are given in Appendix E. Brief biographies of the food chain expert panel members are provided in Appendix F. Aggregated results of expert responses are presented in graph format in Appendix G.

Brown, J. [National Radiological Protection Board (United Kingdom); Goossens, L.H.J.; Kraan, B.C.P. [Delft Univ. of Technology (Netherlands)] [and others

1997-06-01T23:59:59.000Z

406

U.S. Total Exports  

U.S. Energy Information Administration (EIA) Indexed Site

International Falls, MN Noyes, MN Warroad, MN Babb, MT Havre, MT Port of Del Bonita, MT Port of Morgan, MT Sweetgrass, MT Whitlash, MT Portal, ND Sherwood, ND Pittsburg, NH Champlain, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Highgate Springs, VT North Troy, VT LNG Imports into Cameron, LA LNG Imports into Cove Point, MD LNG Imports into Elba Island, GA LNG Imports into Everett, MA LNG Imports into Freeport, TX LNG Imports into Golden Pass, TX LNG Imports into Gulf Gateway, LA LNG Imports into Gulf LNG, MS LNG Imports into Lake Charles, LA LNG Imports into Neptune Deepwater Port LNG Imports into Northeast Gateway LNG Imports into Sabine Pass, LA U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Alamo, TX El Paso, TX Galvan Ranch, TX Hidalgo, TX McAllen, TX Penitas, TX LNG Imports from Algeria Cove Point, MD Everett, MA Lake Charles, LA LNG Imports from Australia Everett, MA Lake Charles, LA LNG Imports from Brunei Lake Charles, LA LNG Imports from Canada Highgate Springs, VT LNG Imports from Egypt Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf LNG, MS Lake Charles, LA Northeast Gateway Sabine Pass, LA LNG Imports from Equatorial Guinea Elba Island, GA Lake Charles, LA LNG Imports from Indonesia Lake Charles, LA LNG Imports from Malaysia Gulf Gateway, LA Lake Charles, LA LNG Imports from Nigeria Cove Point, MD Elba Island, GA Freeport, TX Gulf Gateway, LA Lake Charles, LA Sabine Pass, LA LNG Imports from Norway Cove Point, MD Sabine Pass, LA LNG Imports from Oman Lake Charles, LA LNG Imports from Peru Cameron, LA Freeport, TX Sabine Pass, LA LNG Imports from Qatar Cameron, LA Elba Island, GA Golden Pass, TX Gulf Gateway, LA Lake Charles, LA Northeast Gateway Sabine Pass, LA LNG Imports from Trinidad/Tobago Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf Gateway, LA Gulf LNG, MS Lake Charles, LA Neptune Deepwater Port Northeast Gateway Sabine Pass, LA LNG Imports from United Arab Emirates Lake Charles, LA LNG Imports from Yemen Everett, MA Freeport, TX Neptune Deepwater Port Sabine Pass, LA LNG Imports from Other Countries Lake Charles, LA Period: Monthly Annual

407

Shelf?break tidally induced environmental influences on acoustic propagation  

Science Journals Connector (OSTI)

Continuous wave propagation in the 100–500 Hz band in littoral regions depends upon both time?dependent oceanography and bathymetry. The environmental influences interact nonlinearly in the acoustical time variation especially since the diurnal tidesurface height changes creates time?dependent total water depth. A submesoscale hydrodynamic model developed by Shen and Evans is used with tidal forcing and a simple shelf?break bathymetry to produce surface height variation and internal wave activity due to internal tide in a stratified ocean environment. A three?dimensional parabolic equation acoustic model is used to acoustically probe this environment at various bearings relative to the shelf break and the resulting internal tidal dynamics. In particular the acoustical results are examined for three?dimensional effects such as horizontal refraction. First the influence of bathymetry alone is shown and then compared to the full environment due to hydrodynamic action. The relative influences will then be compared by various measures such as modal decomposition acoustic energy summed over depth and signal gain degradation. [This research is sponsored by the ONR.

2004-01-01T23:59:59.000Z

408

Measurement uncertainty in the performance verification of indicating measuring instruments  

Science Journals Connector (OSTI)

This paper is concerned with measurement uncertainty in the performance verification of the metrological characteristics of indicating measuring instruments to specified tolerances, often called maximum permissible errors (MPE). Performance verification differs from other types of calibrations in that the measurement does not necessarily result in an assigned quantity value. When a measurement involves assigning a quantity value, as is typical with the calibration of material measures or inspection of features on commercial workpieces, the measurand is different than in performance verification. The research literature and published standards and practice for measurement uncertainty typically only address the measurement uncertainty associated with assigned quantity values. When these general approaches to measurement uncertainty are applied to performance verification as well, the measurement uncertainty is not properly estimated and therefore incorrect practice is wide spread in the calibration industry. The purpose of this paper is to clarify the measurand in performance verification and to develop an associated general measurement uncertainty model. Examples are presented that highlight some cases where a measurand associated with performance verification results in a very different measurement uncertainty than when the measurand is associated with the assignment of a quantity value. Some issues for future work are also identified, particularly for consideration in the standardization of specifications for indicating measuring instruments.

James G. Salsbury; Edward P. Morse

2012-01-01T23:59:59.000Z

409

Joint measurability, steering and entropic uncertainty  

E-Print Network [OSTI]

The notion of incompatibility of measurements in quantum theory is in stark contrast with the corresponding classical perspective, where all physical observables are jointly measurable. It is of interest to examine if the results of two or more measurements in the quantum scenario can be perceived from a classical point of view or they still exhibit non-classical features. Clearly, commuting observables can be measured jointly using projective measurements and their statistical outcomes can be discerned classically. However, such simple minded association of compatibility of measurements with commutativity turns out to be limited in an extended framework, where the usual notion of sharp projective valued measurements of self adjoint observables gets broadened to include unsharp measurements of generalized observables constituting positive operator valued measures (POVM). There is a surge of research activity recently towards gaining new physical insights on the emergence of classical behavior via joint measurability of unsharp observables. Here, we explore the entropic uncertainty relation for a pair of discrete observables (of Alice's system) when an entangled quantum memory of Bob is restricted to record outcomes of jointly measurable POVMs only. Within the joint measurability regime, the sum of entropies associated with Alice's measurement outcomes - conditioned by the results registered at Bob's end - are constrained to obey an entropic steering inequality. In this case, Bob's non-steerability reflects itself as his inability in predicting the outcomes of Alice's pair of non-commuting observables with better precision, even when they share an entangled state. As a further consequence, the quantum advantage envisaged for the construction of security proofs in key distribution is lost, when Bob's measurements are restricted to the joint measurability regime.

H. S. Karthik; A. R. Usha Devi; A. K. Rajagopal

2014-10-05T23:59:59.000Z

410

Sound propagation in the nonhomogeneous ocean with currents  

Science Journals Connector (OSTI)

One considers the problem of sound propagation in the nonhomogeneous ocean with currents, where the characteristics of the medium vary...oco?1, ...

N. S. Grigor'eva

1985-09-10T23:59:59.000Z

411

Light propagation in chiral media with large pitch  

Science Journals Connector (OSTI)

Light propagation in uniaxial chiral media with large pitch is studied. In these systems there are forbidden zones for extraordinary beams, which lead to effective reflection on zone...

Aksenova, Elena V; Karetnikov, Aleksandr A; Kovshik, Aleksandr P; Kryukov, Evgeny V; Romanov, Vadim P

2008-01-01T23:59:59.000Z

412

Transitions from Oscillatory to Smooth Fracture Propagation in...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Transitions from Oscillatory to Smooth Fracture Propagation in Viscoelastic Materials Jan 29 2015 10:30 AM - 11:30 AM Yehuda Braiman, Division Staff Computer Science and...

413

Nonstationary doppler effect for waves propagating in nonhomogeneous media  

Science Journals Connector (OSTI)

The theory of the frequency shift of continuous waves propagating in a medium whose properties depend on the coordinates and time is presented.

V. I. Krylovich

1982-10-01T23:59:59.000Z

414

Propagation-invariant wave fields with finite energy  

Science Journals Connector (OSTI)

Propagation invariance is extended in the paraxial regime, leading to a generalized self-imaging effect. These wave fields are characterized by a finite number of transverse...

Piestun, Rafael; Schechner, Yoav Y; Shamir, Joseph

2000-01-01T23:59:59.000Z

415

Generation of multi-photon entanglement by propagation and detection  

E-Print Network [OSTI]

We investigate the change of entanglement of photons due to propagation. We find that post-selected entanglement in general varies by propagation and, as a consequence, states with maximum bi- and tri-partite entanglement can be generated from propagation of unentangled photons. We generalize the results to n photons and show that entangled states with permutation symmetry can be generated from propagation of unentangled states. Generation of n-photon GHZ states is discussed as an example of a class of states with the desired symmetry.

H. Hossein-Nejad; R. Stock; D. F. V. James

2009-03-02T23:59:59.000Z

416

Evaluation of expanded uncertainties in luminous intensity and illuminance calibrations  

SciTech Connect (OSTI)

Detector-based calibrating methods and expressions for calculation of photometric uncertainties related to uncertainties in the calibrations of luminous intensity of a light source, illuminance responsivity of a photometer head, and calibration factors of an illuminance meter are discussed. These methods permit luminous intensity calibrations of incandescent light sources, luminous responsivity calibrations of photometer heads, and calibration factors of illuminance meters to be carried out with relative expanded uncertainties (with a level of confidence of 95.45%) of 0.4%, 0.4%, and 0.6%, respectively.

Sametoglu, Ferhat

2008-11-01T23:59:59.000Z

417

Calibration and Measurement Uncertainty Estimation of Radiometric Data: Preprint  

SciTech Connect (OSTI)

Evaluating the performance of photovoltaic cells, modules, and arrays that form large solar deployments relies on accurate measurements of the available solar resource. Therefore, determining the accuracy of these solar radiation measurements provides a better understanding of investment risks. This paper provides guidelines and recommended procedures for estimating the uncertainty in calibrations and measurements by radiometers using methods that follow the International Bureau of Weights and Measures Guide to the Expression of Uncertainty (GUM). Standardized analysis based on these procedures ensures that the uncertainty quoted is well documented.

Habte, A.; Sengupta, M.; Reda, I.; Andreas, A.; Konings, J.

2014-11-01T23:59:59.000Z

418

Lattice Boltzmann model for wave propagation  

Science Journals Connector (OSTI)

A lattice Boltzmann model for two-dimensional wave equation is proposed by using the higher-order moment method. The higher-order moment method is based on the solution of a series of partial differential equations obtained by using multiscale technique and Chapman-Enskog expansion. In order to obtain the lattice Boltzmann model for the wave equation with higher-order accuracy of truncation errors, we removed the second-order dissipation term and the third-order dispersion term by employing the moments up to fourth order. The reversibility in time appears owing to the absence of the second-order dissipation term and the third-order dispersion term. As numerical examples, some classical examples, such as interference, diffraction, and wave passing through a convex lens, are simulated. The numerical results show that this model can be used to simulate wave propagation.

Jianying Zhang; Guangwu Yan; Xiubo Shi

2009-08-27T23:59:59.000Z

419

Comparison of Homogeneous and Heterogeneous CFD Fuel Models for Phase I of the IAEA CRP on HTR Uncertainties Benchmark  

SciTech Connect (OSTI)

Computational Fluid Dynamics (CFD) evaluation of homogeneous and heterogeneous fuel models was performed as part of the Phase I calculations of the International Atomic Energy Agency (IAEA) Coordinate Research Program (CRP) on High Temperature Reactor (HTR) Uncertainties in Modeling (UAM). This study was focused on the nominal localized stand-alone fuel thermal response, as defined in Ex. I-3 and I-4 of the HTR UAM. The aim of the stand-alone thermal unit-cell simulation is to isolate the effect of material and boundary input uncertainties on a very simplified problem, before propagation of these uncertainties are performed in subsequent coupled neutronics/thermal fluids phases on the benchmark. In many of the previous studies for high temperature gas cooled reactors, the volume-averaged homogeneous mixture model of a single fuel compact has been applied. In the homogeneous model, the Tristructural Isotropic (TRISO) fuel particles in the fuel compact were not modeled directly and an effective thermal conductivity was employed for the thermo-physical properties of the fuel compact. On the contrary, in the heterogeneous model, the uranium carbide (UCO), inner and outer pyrolytic carbon (IPyC/OPyC) and silicon carbide (SiC) layers of the TRISO fuel particles are explicitly modeled. The fuel compact is modeled as a heterogeneous mixture of TRISO fuel kernels embedded in H-451 matrix graphite. In this study, a steady-state and transient CFD simulations were performed with both homogeneous and heterogeneous models to compare the thermal characteristics. The nominal values of the input parameters are used for this CFD analysis. In a future study, the effects of input uncertainties in the material properties and boundary parameters will be investigated and reported.

Gerhard Strydom; Su-Jong Yoon

2014-04-01T23:59:59.000Z

420

Study on Total Instantaneous Blockage Accident for CEFR  

SciTech Connect (OSTI)

Chinese Experimental Fast Reactor (CEFR) is under construction in China. It is essential to investigate core disruptive accidents (CDAs) for the evaluation of CEFR's safety characteristic. Accident of total instantaneous blockage in single assembly scale had already been modeled and analyzed. The degradation scenario had been calculated by a fluid-dynamics analysis code for liquid-metal fast reactors (LMFRs). For further investigation of accident process and influence to the near bundles, the seven assembly scale were then simulated and calculated. Total instantaneous blockage was assumed to occur in the center assembly under normal operating conditions and consequences to neighboring assemblies were studied. The result shows that the key events such as sodium boiling, clad melting, fuel particles relocation, hexcan failure and melt discharge into neighboring six assemblies symmetrically were adequately simulated. All the key events appeared in the same sequence as the single assembly simulation, while hexcan failure occurred later than that of single assembly simulation. The reason for the different timing may be the boundary condition assumption can influence the heat removal from the blocked assembly. The seven-assembly scale model can reduce the boundary condition's uncertainties and help to give a better understanding and prediction of hypothetical accident scenario in subassembly blockage accidents for CEFR. (authors)

Zhe Wang; Xuewu Cao [Shanghai Jiaotong University, Shanghai (China)

2006-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

State Residential Commercial Industrial Transportation Total  

Gasoline and Diesel Fuel Update (EIA)

schedules 4A-D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total 2012 Total Electric Industry- Average Retail Price (centskWh) (Data from...

422

Total cost model for making sourcing decisions  

E-Print Network [OSTI]

This thesis develops a total cost model based on the work done during a six month internship with ABB. In order to help ABB better focus on low cost country sourcing, a total cost model was developed for sourcing decisions. ...

Morita, Mark, M.B.A. Massachusetts Institute of Technology

2007-01-01T23:59:59.000Z

423

Uncertainty Quantification Tools for Multiphase Flow Simulations using MFIX  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Uncertainty Uncertainty Quantification Tools for Multiphase Flow Simulations using MFIX X. Hu 1 , A. Passalacqua 2 , R. O. Fox 1 1 Iowa State University, Department of Chemical and Biological Engineering, Ames, IA 2 Iowa State University, Department of Mechanical Engineering, Ames, IA Project Manager: Steve Seachman University Coal Research and Historically Black Colleges and Universities and Other Minority Institutions Contractors Review Conference Pittsburgh, June 11 th - 13 th 2013 X. Hu, A. Passalacqua, R. O. Fox (ISU) Uncertainty quantification DOE-UCR Review Meeting 2013 1 / 44 Outline 1 Introduction and background 2 Project objectives and milestones 3 Technical progress Univariate case Multivariate case Code structure 4 Future work X. Hu, A. Passalacqua, R. O. Fox (ISU) Uncertainty quantification DOE-UCR Review Meeting 2013 2 / 44 Introduction and background Outline 1 Introduction

424

Modeling aviation's global emissions, uncertainty analysis, and applications to policy  

E-Print Network [OSTI]

(cont.) fuel burn results below 3000 ft. For emissions, the emissions indices were the most influential uncertainties for the variance in model outputs. By employing the model, this thesis examined three policy options for ...

Lee, Joosung Joseph, 1974-

2005-01-01T23:59:59.000Z

425

A robust optimization model for a supply chain under uncertainty  

Science Journals Connector (OSTI)

......2010). Although handling uncertainty is an...interesting framework for handling stochastic logistics...In N numbers) Material Flow Material Flow Fig. 1. A schematic diagram of the logistics...which is capable of handling demand and transportation......

Sara Hosseini; Reza Zanjirani Farahani; Wout Dullaert; Birger Raa; Mohsen Rajabi; Alireza Bolhari

2014-10-01T23:59:59.000Z

426

Uncertainty in science and its role in climate policy  

Science Journals Connector (OSTI)

...about risk management. Thus, climate science supports...as climate science provides a basis for risk management much deeper...practice approaches for characterizing...in climate science and policy...uncertainty management in model-based...

2011-01-01T23:59:59.000Z

427

The Uncertainty Principle Determines the Nonlocality of Quantum Mechanics  

Science Journals Connector (OSTI)

...Wehner S. , Relaxed uncertainty relations and information processing . QIC 9 , 801 ( 2009 ). Abstract 5 Paw?owski M. ., Information causality as a physical principle . Nature 461 , 1101 ( 2009 ). 10.1038/nature08400 19847260 6 W. van Dam...

Jonathan Oppenheim; Stephanie Wehner

2010-11-19T23:59:59.000Z

428

Distributed Generation Investment by a Microgrid under Uncertainty++++ Afzal Siddiqui  

E-Print Network [OSTI]

1 Distributed Generation Investment by a Microgrid under Uncertainty++++ Afzal Siddiqui University's decision to invest in a distributed generation (DG) unit fuelled by natural gas. While the long. KEYWORDS. OR in Energy; Distributed Generation; Real Options; Optimal Investment. 1. INTRODUCTION

Guillas, Serge

429

Analysis and reduction of chemical models under uncertainty.  

SciTech Connect (OSTI)

While models of combustion processes have been successful in developing engines with improved fuel economy, more costly simulations are required to accurately model pollution chemistry. These simulations will also involve significant parametric uncertainties. Computational singular perturbation (CSP) and polynomial chaos-uncertainty quantification (PC-UQ) can be used to mitigate the additional computational cost of modeling combustion with uncertain parameters. PC-UQ was used to interrogate and analyze the Davis-Skodje model, where the deterministic parameter in the model was replaced with an uncertain parameter. In addition, PC-UQ was combined with CSP to explore how model reduction could be combined with uncertainty quantification to understand how reduced models are affected by parametric uncertainty.

Oxberry, Geoff; Debusschere, Bert J.; Najm, Habib N.

2008-08-01T23:59:59.000Z

430

An efficient Bayesian approach to history matching and uncertainty assessment  

E-Print Network [OSTI]

Conditioning reservoir models to production data and assessment of uncertainty can be done by Bayesian theorem. This inverse problem can be computationally intensive, generally requiring orders of magnitude more computation time compared...

Yuan, Chengwu

2007-04-25T23:59:59.000Z

431

The Decision Rule Approach to Optimisation under Uncertainty ...  

E-Print Network [OSTI]

Robust Optimisation, Decision Rules, Optimisation under Uncertainty. ... in turn lead to the underperformance or complete breakdown of production processes. Yet,. 1 ...... 5: Energy Systems Engineering, M. Georgiadis, E. Kikkinides, and E.

2011-12-21T23:59:59.000Z

432

How does fuel price uncertainty affect strategic airline planning?  

Science Journals Connector (OSTI)

Today, jet fuel costs are a growing part in airlines’ ... fluctuations. Therefore, airlines think about minimizing jet fuel costs and counteracting fuel price uncertainty. The strategic flight planning highly det...

Marc Naumann; Leena Suhl

2013-10-01T23:59:59.000Z

433

Model sensitivity and uncertainty analysis using roadside air quality measurements  

E-Print Network [OSTI]

Model sensitivity and uncertainty analysis using roadside air quality measurements Sotiris, a probabilistic methodology for assessing urban air quality was proposed. Keywords: Air pollution; Model 535265 1. Introduction Mathematical modelling has been widely used for assessing ambient air quality

Paris-Sud XI, Université de

434

On the Predictive Uncertainty of a Distributed Hydrologic Model  

E-Print Network [OSTI]

We use models to simulate the real world mainly for prediction purposes. However, since any model is a simplification of reality, there remains a great deal of uncertainty even after the calibration of model parameters. The model’s identifiability...

Cho, Huidae

2009-05-15T23:59:59.000Z

435

Managing uncertainty: information and insurance under the risk of starvation  

Science Journals Connector (OSTI)

...In an uncertain world, animals face...and insurance (energy reserves) under starvation...programming|energy reserves| Managing uncertainty...In an uncertain world, animals face...and insurance (energy reserves) under starvation...

2002-01-01T23:59:59.000Z

436

Optimum maintenance strategy under uncertainty in the lifetime distribution  

Science Journals Connector (OSTI)

Abstract The problem of determining the optimal maintenance strategy for a machine given its lifetime distribution has been studied extensively. Solutions to this problem are outlined in the academic literature, prescribed in professional handbooks, implemented in reliability engineering software systems and widely used in practice. These solutions typically assume that the lifetime distribution and its parameter values are known with certainty, although this is usually not the case in practice. In this paper we study the effect of parameter uncertainty on the optimum age-based maintenance strategy. The effect of uncertainty is evaluated by considering both a theoretical uniform lifetime distribution and a more realistic Weibull lifetime distribution. The results show that admitting to the uncertainty does influence the optimal maintenance age and also provides a quantifiable cost benefit. The results can help maintenance managers in making maintenance decisions under uncertainty, and also in deciding when it is worthwhile to invest in advanced data improvement procedures.

Bram de Jonge; Warse Klingenberg; Ruud Teunter; Tiedo Tinga

2015-01-01T23:59:59.000Z

437

Uncertainty in future carbon emissions : a preliminary exploration  

E-Print Network [OSTI]

In order to analyze competing policy approaches for addressing global climate change, a wide variety of economic-energy models are used to project future carbon emissions under various policy scenarios. Due to uncertainties ...

Webster, Mort David.

438

Team Total Points Beta Theta Pi 2271  

E-Print Network [OSTI]

Bubbles 40 Upset City 30 Team Success 30 #12;Team Total Points Sly Tye 16 Barringer 15 Fire Stinespring 15

Buehrer, R. Michael

439

Computer-aided-design of agricultural drains under uncertainty  

E-Print Network [OSTI]

COMPUTER-AIDED-DESIGN OF AGRICULTURAL DRAINS UNDER UNCERTAINTY A Thesis LUIS ALFREDO GARCIA Submitted to the Graduate College of Texas A&N University in partial fulfillment of the requirements for the degree of RASTER OF SCIENCE December... 1985 Major Subject: Civil Engineering COMPUTER-AIDED-DESIGN OP AGRICULTURAL DRAINS UNDER UNCERTAINTY A Thesis by LUIS ALFREDO GARCIA Approved as to style and content by: Kenne M rzepek Wc (Member) Donald McDonald (Head of Department...

Garcia, Luis Alfredo

2012-06-07T23:59:59.000Z

440

Environmental uncertainty and social value orientation in resource dilemmas  

E-Print Network [OSTI]

research has shown that both environmental uncertainty and social value orientation (cooperators vs. noncooperators) will affect harvest sizes from a common resource pool. However, these two variables have not been simultaneously explored.... In the present experiment, 172 subjects harvested units from a common resource pool over 20 twenty trials. It was predicted that noncooperators would harvest more than cooperators (Hypothesis 1), an interaction between social value orientation and uncertainty...

Roch, Sylvia Gabriele

1994-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Calculation and Verification of Blood Ethanol Measurement Uncertainty for Headspace Gas Chromatography  

Science Journals Connector (OSTI)

......Calculation and Verification of Blood Ethanol Measurement Uncertainty for...Calculation and verification of blood ethanol measurement uncertainty for...2% of the BAC measurement. Verification of the estimate......

Jason H. Sklerov; Fiona J. Couper

2011-09-01T23:59:59.000Z

442

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network [OSTI]

Energy Resources and Demand Response under Uncertainty AfzalEnergy Resources and Demand Response under Uncertainty ?DER in conjunction with demand response (DR): the expected

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

443

SciTech Connect: Improvements of Nuclear Data and Its Uncertainties...  

Office of Scientific and Technical Information (OSTI)

Improvements of Nuclear Data and Its Uncertainties by Theoretical Modeling Citation Details In-Document Search Title: Improvements of Nuclear Data and Its Uncertainties by...

444

E-Print Network 3.0 - assessing spatial uncertainty Sample Search...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Uncertainty analysis assesses... in evaluating alternatives. Concern about uncertainty in spatial data and analyses is not new, but systematic... A thorough understanding of...

445

Assessing the Role of Operating, Passenger, and Infrastructure Costs in Fleet Planning under Fuel Price Uncertainty  

E-Print Network [OSTI]

ICKET . Aircraft Category Fuel Price (FP) Coefficient SL*FPin Fleet Planning under Fuel Price Uncertainty Megan Smirti,in Fleet Planning under Fuel Price Uncertainty Megan Smirti,

Smirti, Megan; Hansen, Mark

2009-01-01T23:59:59.000Z

446

Uncertainty estimation improves energy measurement and verification procedures  

Science Journals Connector (OSTI)

Abstract Implementing energy conservation measures in buildings can reduce energy costs and environmental impacts, but such measures cost money to implement so intelligent investment strategies require the ability to quantify the energy savings by comparing actual energy used to how much energy would have been used in absence of the conservation measures (known as the “baseline” energy use). Methods exist for predicting baseline energy use, but a limitation of most statistical methods reported in the literature is inadequate quantification of the uncertainty in baseline energy use predictions. However, estimation of uncertainty is essential for weighing the risks of investing in retrofits. Most commercial buildings have, or soon will have, electricity meters capable of providing data at short time intervals. These data provide new opportunities to quantify uncertainty in baseline predictions, and to do so after shorter measurement durations than are traditionally used. In this paper, we show that uncertainty estimation provides greater measurement and verification (M&V) information and helps to overcome some of the difficulties with deciding how much data is needed to develop baseline models and to confirm energy savings. We also show that cross-validation is an effective method for computing uncertainty. In so doing, we extend a simple regression-based method of predicting energy use using short-interval meter data. We demonstrate the methods by predicting energy use in 17 real commercial buildings. We discuss the benefits of uncertainty estimates which can provide actionable decision making information for investing in energy conservation measures.

Travis Walter; Phillip N. Price; Michael D. Sohn

2014-01-01T23:59:59.000Z

447

How incorporating more data reduces uncertainty in recovery predictions  

SciTech Connect (OSTI)

From the discovery to the abandonment of a petroleum reservoir, there are many decisions that involve economic risks because of uncertainty in the production forecast. This uncertainty may be quantified by performing stochastic reservoir modeling (SRM); however, it is not practical to apply SRM every time the model is updated to account for new data. This paper suggests a novel procedure to estimate reservoir uncertainty (and its reduction) as a function of the amount and type of data used in the reservoir modeling. Two types of data are analyzed: conditioning data and well-test data. However, the same procedure can be applied to any other data type. Three performance parameters are suggested to quantify uncertainty. SRM is performed for the following typical stages: discovery, primary production, secondary production, and infill drilling. From those results, a set of curves is generated that can be used to estimate (1) the uncertainty for any other situation and (2) the uncertainty reduction caused by the introduction of new wells (with and without well-test data) into the description.

Campozana, F.P.; Lake, L.W.; Sepehrnoori, K. [Univ. of Texas, Austin, TX (United States)

1997-08-01T23:59:59.000Z

448

Uncertainty Estimation Improves Energy Measurement and Verification Procedures  

SciTech Connect (OSTI)

Implementing energy conservation measures in buildings can reduce energy costs and environmental impacts, but such measures cost money to implement so intelligent investment strategies require the ability to quantify the energy savings by comparing actual energy used to how much energy would have been used in absence of the conservation measures (known as the baseline energy use). Methods exist for predicting baseline energy use, but a limitation of most statistical methods reported in the literature is inadequate quantification of the uncertainty in baseline energy use predictions. However, estimation of uncertainty is essential for weighing the risks of investing in retrofits. Most commercial buildings have, or soon will have, electricity meters capable of providing data at short time intervals. These data provide new opportunities to quantify uncertainty in baseline predictions, and to do so after shorter measurement durations than are traditionally used. In this paper, we show that uncertainty estimation provides greater measurement and verification (M&V) information and helps to overcome some of the difficulties with deciding how much data is needed to develop baseline models and to confirm energy savings. We also show that cross-validation is an effective method for computing uncertainty. In so doing, we extend a simple regression-based method of predicting energy use using short-interval meter data. We demonstrate the methods by predicting energy use in 17 real commercial buildings. We discuss the benefits of uncertainty estimates which can provide actionable decision making information for investing in energy conservation measures.

Walter, Travis; Price, Phillip N.; Sohn, Michael D.

2014-05-14T23:59:59.000Z

449

Heuristically Driven Front Propagation for Fast Geodesic Extraction  

E-Print Network [OSTI]

Heuristically Driven Front Propagation for Fast Geodesic Extraction Gabriel Peyr´e Laurent D. Cohen to quickly extract geodesic paths on images and 3D meshes. We use a heuristic to drive the front propagation that is similar to the A algorithm used in artificial intelli- gence. In order to find very quickly geodesic paths

Paris-Sud XI, Université de

450

Viscous attenuation of a detonation wave propagating in a channel  

E-Print Network [OSTI]

Viscous attenuation of a detonation wave propagating in a channel P. Ravindran1 , R. Bellini1 , T of a detonation wave in a two-dimensional channel is simulated by an Euler and a Navier-Stokes solver. Transport arising from viscous drag. 1 Introduction The propagation of a detonation wave remains one

Texas at Arlington, University of

451

EFFECT OF REACTION RATE PERIODICITY ON DETONATION PROPAGATION  

E-Print Network [OSTI]

EFFECT OF REACTION RATE PERIODICITY ON DETONATION PROPAGATION Eric O. Morano and Joseph E. Shepherd through numerical simulations how the detonation propagation is affected by the heterogeneous rate but there is no accepted and accurate repre- sentation of all thermodynamic states significant to the detonation process

Barr, Al

452

LevelSet Techniques Applied to Unsteady Detonation Propagation  

E-Print Network [OSTI]

## Level­Set Techniques Applied to Unsteady Detonation Propagation D. Scott Stewart 1 Tariq Aslam 1­propagating surface. The detonation shock surface has been shown under certain circumstances to be governed, we discuss the specific example from detonation theory, which summarizes our recent work in [2

Aslam, Tariq

453

Fast DOA estimation of incoherently distributed sources by novel propagator  

Science Journals Connector (OSTI)

A low-complexity algorithm is presented for the estimation of the nominal direction-of-arrivals (DOAs) of incoherently distributed (ID) sources. The presented algorithm estimates the nominal DOAs of ID sources by a novel propagator method which makes ... Keywords: DOA estimation, Incoherently distributed sources, Novel propagator, Uniform linear array (ULA)

Zhi Zheng; Guangjun Li

2013-09-01T23:59:59.000Z

454

Radiative transport theory for light propagation in luminescent media  

E-Print Network [OSTI]

the radiative transport equation (RTE) [1,2]. It has been applied successfully to many prob- lemsRadiative transport theory for light propagation in luminescent media Derya ahin* and Boaz Ilan of radiative transport theory to account for light propagation in luminescent random media. This theory

Ilan, Boaz

455

Variational Structure of Inverse Problems in Wave Propagation and Vibration  

E-Print Network [OSTI]

Variational Structure of Inverse Problems in Wave Propagation and Vibration James G. Berryman in wave propagation (traveltime tomography) and two examples in vibration (the plucked string and free.'' For vibrating systems, the apparently very complex behavior of an excited string, drumhead, or the Earth can

456

Bootstrapping the statistical uncertainties of NN scattering data  

E-Print Network [OSTI]

We use the Monte Carlo bootstrap as a method to simulate pp and np scattering data below pion production threshold from an initial set of over 6700 experimental mutually $3\\sigma$ consistent data. We compare the results of the bootstrap, with 1020 statistically generated samples of the full database, with the standard covariance matrix method of error propagation. No significant differences in scattering observables and phase shifts are found. This suggests alternative strategies for propagating errors of nuclear forces in nuclear structure calculations.

R. Navarro Perez; J. E. Amaro; E. Ruiz Arriola

2014-07-15T23:59:59.000Z

457

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

38 38 Nevada - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S30. Summary statistics for natural gas - Nevada, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 4 4 4 3 4 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 4 4 4 3 4

458

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Idaho - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S14. Summary statistics for natural gas - Idaho, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

459

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Washington - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S49. Summary statistics for natural gas - Washington, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

460

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

0 0 Maine - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S21. Summary statistics for natural gas - Maine, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

8 8 Minnesota - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S25. Summary statistics for natural gas - Minnesota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

462

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

2 2 South Carolina - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S42. Summary statistics for natural gas - South Carolina, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

463

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 North Carolina - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. Summary statistics for natural gas - North Carolina, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

464

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Iowa - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S17. Summary statistics for natural gas - Iowa, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0

465

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

4 4 Massachusetts - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

466

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Minnesota - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S25. Summary statistics for natural gas - Minnesota, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

467

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 New Jersey - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. Summary statistics for natural gas - New Jersey, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

468

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Vermont - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S47. Summary statistics for natural gas - Vermont, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

469

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Wisconsin - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S51. Summary statistics for natural gas - Wisconsin, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

470

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

8 8 North Carolina - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. Summary statistics for natural gas - North Carolina, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

471

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

2 2 New Jersey - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. Summary statistics for natural gas - New Jersey, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

472

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Maryland - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S22. Summary statistics for natural gas - Maryland, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 7 7 7 7 8 Production (million cubic feet) Gross Withdrawals From Gas Wells 35 28 43 43 34 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 35

473

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

0 0 New Hampshire - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S31. Summary statistics for natural gas - New Hampshire, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

474

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

2 2 Maryland - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S22. Summary statistics for natural gas - Maryland, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 7 7 7 8 9 Production (million cubic feet) Gross Withdrawals From Gas Wells 28 43 43 34 44 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 28

475

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

2 2 Missouri - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S27. Summary statistics for natural gas - Missouri, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 53 100 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

476

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Massachusetts - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

477

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 South Carolina - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S42. Summary statistics for natural gas - South Carolina, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

478

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

0 0 Rhode Island - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S41. Summary statistics for natural gas - Rhode Island, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

479

DOE/RL-96-68  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

100114 Vol. 4: ix RPD Relative Percent Difference RSD Relative Standard Deviation TIC Tentatively Identified Compound TPU Total Propagated Uncertainty VOC Volatile Organic...

480

Compare All CBECS Activities: Total Energy Use  

U.S. Energy Information Administration (EIA) Indexed Site

Total Energy Use Total Energy Use Compare Activities by ... Total Energy Use Total Major Fuel Consumption by Building Type Commercial buildings in the U.S. used a total of approximately 5.7 quadrillion Btu of all major fuels (electricity, natural gas, fuel oil, and district steam or hot water) in 1999. Office buildings used the most total energy of all the building types, which was not a surprise since they were the most common commercial building type and had an above average energy intensity. Figure showing total major fuel consumption by building type. If you need assistance viewing this page, please call 202-586-8800. Major Fuel Consumption per Building by Building Type Because there were relatively few inpatient health care buildings and they tend to be large, energy intensive buildings, their energy consumption per building was far above that of any other building type.

Note: This page contains sample records for the topic "total propagated uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

TotalView Parallel Debugger at NERSC  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Totalview Totalview Totalview Description TotalView from Rogue Wave Software is a parallel debugging tool that can be run with up to 512 processors. It provides both X Windows-based Graphical User Interface (GUI) and command line interface (CLI) environments for debugging. The performance of the GUI can be greatly improved if used in conjunction with free NX software. The TotalView documentation web page is a good resource for learning more about some of the advanced TotalView features. Accessing Totalview at NERSC To use TotalView at NERSC, first load the TotalView modulefile to set the correct environment settings with the following command: % module load totalview Compiling Code to Run with TotalView In order to use TotalView, code must be compiled with the -g option. We

482

Fixing convergence of Gaussian belief propagation  

SciTech Connect (OSTI)

Gaussian belief propagation (GaBP) is an iterative message-passing algorithm for inference in Gaussian graphical models. It is known that when GaBP converges it converges to the correct MAP estimate of the Gaussian random vector and simple sufficient conditions for its convergence have been established. In this paper we develop a double-loop algorithm for forcing convergence of GaBP. Our method computes the correct MAP estimate even in cases where standard GaBP would not have converged. We further extend this construction to compute least-squares solutions of over-constrained linear systems. We believe that our construction has numerous applications, since the GaBP algorithm is linked to solution of linear systems of equations, which is a fundamental problem in computer science and engineering. As a case study, we discuss the linear detection problem. We show that using our new construction, we are able to force convergence of Montanari's linear detection algorithm, in cases where it would originally fail. As a consequence, we are able to increase significantly the number of users that can transmit concurrently.

Johnson, Jason K [Los Alamos National Laboratory; Bickson, Danny [IBM RESEARCH LAB; Dolev, Danny [HEBREW UNIV

2009-01-01T23:59:59.000Z

483

Mechanical Surface Waves Accompany Action Potential Propagation  

E-Print Network [OSTI]

Many studies have shown that a mechanical displacement of the axonal membrane accompanies the electrical pulse defining the Action Potential (AP). Despite a large and diverse body of experimental evidence, there is no theoretical consensus either for the physical basis of this mechanical wave nor its interdependence with the electrical signal. In this manuscript we present a model for these mechanical displacements as arising from the driving of surface wave modes in which potential energy is stored in elastic properties of the neuronal membrane and cytoskeleton while kinetic energy is carried by the axoplasmic fluid. In our model these surface waves are driven by the traveling wave of electrical depolarization that characterizes the AP, altering the compressive electrostatic forces across the membrane as it passes. This driving leads to co-propagating mechanical displacements, which we term Action Waves (AWs). Our model for these AWs allows us to predict, in terms of elastic constants, axon radius and axoplasmic density and viscosity, the shape of the AW that should accompany any traveling wave of voltage, including the AP predicted by the Hodgkin and Huxley (HH) equations. We show that our model makes predictions that are in agreement with results in experimental systems including the garfish olfactory nerve and the squid giant axon. We expect our model to serve as a framework for understanding the physical origins and possible functional roles of these AWs in neurobiology.

Ahmed El Hady; Benjamin B. Machta

2014-07-28T23:59:59.000Z

484

The influence of mesoscale eddies on shallow water acoustic propagation  

Science Journals Connector (OSTI)

Acoustic propagation measurements in 150 m depth on the Florida escarpment observe the effects of the passage of a cyclonic eddy. As the stream core of the Florida Current meanders the eddy is formed and propagates along the shelf edge. The sequence over a roughly a fortnight is as follows: ahead of the eddy warm surface water and cold bottom water are swept onto the terrace forming a steep thermocline and corresponding strong downward refracting C(z). The gradient produce intense focused RBR arrivals and the thermocline becomes a duct for internal waves to propagate shoreward. At first the internal wave energy is minimal and propagation is stable and coherent. As the internal tides attempt to propagate on shelf the sound speed field and the acoustic signals become increasingly variable. The variability reaches a crescendo as the 200 m long internal tide is blocked from propagating on to the narrower shelf and begins to break and overturn producing small?scale variability. As the eddy passes nearly iso?thermal conditions are restored along with quiescent internal wave fields and reduced signal variability. Here the effects are quantized with data from fixed?system acoustic and oceanographic measurements demonstrating that the mesoscale determines acoustic propagation conditions days in advance.

2003-01-01T23:59:59.000Z

485

Uncertainty analysis of LBLOCA for Advanced Heavy Water Reactor  

Science Journals Connector (OSTI)

The main objective of safety analysis is to demonstrate in a robust way that all safety requirements are met, i.e. sufficient margins exist between real values of important parameters and their threshold values at which damage of the barriers against release of radioactivity would occur. As stated in the IAEA Safety Requirements for Design of \\{NPPs\\} “a safety analysis of the plant design shall be conducted in which methods of both deterministic and probabilistic analysis shall be applied”. It is required that “the computer programs, analytical methods and plant models used in the safety analysis shall be verified and validated, and adequate consideration shall be given to uncertainties”. Uncertainties are present in calculations due to the computer codes, initial and boundary conditions, plant state, fuel parameters, scaling and numerical solution algorithm. All conservative approaches, still widely used, were introduced to cover uncertainties due to limited capability for modelling and understanding of physical phenomena at the early stages of safety analysis. The results obtained by this approach are quite unrealistic and the level of conservatism is not fully known. Another approach is the use of Best Estimate (BE) codes with realistic initial and boundary conditions. If this approach is selected, it should be based on statistically combined uncertainties for plant initial and boundary conditions, assumptions and code models. The current trends are going into direction of the best estimate code with some conservative assumptions of the system with realistic input data with uncertainty analysis. The BE analysis with evaluation of uncertainties offers, in addition, a way to quantify the existing plant safety margins. Its broader use in the future is therefore envisaged, even though it is not always feasible because of the difficulty of quantifying code uncertainties with sufficiently narrow range for every phenomenon and for each accident sequence. In this paper, uncertainty analysis for the Large Break LOCA (200% Inlet Header Break) of Advanced Heavy Water Reactor (AHWR) has been carried out. The uncertainty analysis was carried out for the peak cladding temperature (PCT), based on the two different methods i.e., Wilk’s method and the response surface technique. Their findings have also been compared.

A. Srivastava; H.G. Lele; A.K. Ghosh; H.S. Kushwaha

2008-01-01T23:59:59.000Z

486

Visual Scanning Hartmann Optical Tester (VSHOT) Uncertainty Analysis (Milestone Report)  

SciTech Connect (OSTI)

In 1997, an uncertainty analysis was conducted of the Video Scanning Hartmann Optical Tester (VSHOT). In 2010, we have completed a new analysis, based primarily on the geometric optics of the system, and it shows sensitivities to various design and operational parameters. We discuss sources of error with measuring devices, instrument calibrations, and operator measurements for a parabolic trough mirror panel test. These help to guide the operator in proper setup, and help end-users to understand the data they are provided. We include both the systematic (bias) and random (precision) errors for VSHOT testing and their contributions to the uncertainty. The contributing factors we considered in this study are: target tilt; target face to laser output distance; instrument vertical offset; laser output angle; distance between the tool and the test piece; camera calibration; and laser scanner. These contributing factors were applied to the calculated slope error, focal length, and test article tilt that are generated by the VSHOT data processing. Results show the estimated 2-sigma uncertainty in slope error for a parabolic trough line scan test to be +/-0.2 milliradians; uncertainty in the focal length is +/- 0.1 mm, and the uncertainty in test article tilt is +/- 0.04 milliradians.

Gray, A.; Lewandowski, A.; Wendelin, T.

2010-10-01T23:59:59.000Z

487

Direct tests of measurement uncertainty relations: what it takes  

E-Print Network [OSTI]

The uncertainty principle being a cornerstone of quantum mechanics, it is surprising that in nearly 90 years there have been no direct tests of measurement uncertainty relations. This lacuna was due to the absence of two essential ingredients: appropriate measures of measurement error (and disturbance), and precise formulations of such relations that are {\\em universally valid}and {\\em directly testable}. We formulate two distinct forms of direct tests, based on different measures of error. We present a prototype protocol for a direct test of measurement uncertainty relations in terms of {\\em value deviation errors} (hitherto considered nonfeasible), highlighting the lack of universality of these relations. This shows that the formulation of universal, directly testable measurement uncertainty relations for {\\em state-dependent} error measures remains an important open problem. Recent experiments that were claimed to constitute invalidations of Heisenberg's error-disturbance relation are shown to conform with the spirit of Heisenberg's principle if interpreted as direct tests of measurement uncertainty relations for error measures that quantify {\\em distances between observables}.

Paul Busch; Neil Stevens

2015-01-17T23:59:59.000Z

488

Carbon capture retrofits and the cost of regulatory uncertainty  

SciTech Connect (OSTI)

Power generation firms confront impending replacement of an aging coal-fired fleet in a business environment characterized by volatile natural gas prices and uncertain carbon regulation. We develop a stochastic dynamic programming model of firm investment decisions that minimizes the expected present value of future power generation costs under uncertain natural gas and carbon prices. We explore the implications of regulatory uncertainty on generation technology choice and the optimal timing of investment, and assess the implications of these choices for regulators. We find that interaction of regulatory uncertainty with irreversible investment always raises the social cost of carbon abatement. Further, the social cost of regulatory uncertainty is strongly dependent on the relative competitiveness of IGCC plants, for which the cost of later carbon capture retrofits is comparatively small, and on the firm's ability to use investments in natural gas generation as a transitional strategy to manage carbon regulation uncertainty. Without highly competitive IGCC or low gas prices, regulatory uncertainty can increase the expected social cost of reducing emissions by 40 to 60%.

Reinelt, P.S.; Keith, D.W. [SUNY College of Fredonia, Fredonia, NY (United States). Dept. of Economics

2007-07-01T23:59:59.000Z

489

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

6 6 Tennessee - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S44. Summary statistics for natural gas - Tennessee, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 285 310 230 210 212 Production (million cubic feet) Gross Withdrawals From Gas Wells 4,700 5,478 5,144 4,851 5,825 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

490

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

2 2 Connecticut - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. Summary statistics for natural gas - Connecticut, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

491

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Oregon - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 18 21 24 26 24 Production (million cubic feet) Gross Withdrawals From Gas Wells 409 778 821 1,407 1,344 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

492

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

6 6 District of Columbia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

493

Million Cu. Feet Percent of National Total  

U.S. Energy Information Administration (EIA) Indexed Site

6 6 Oregon - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 21 24 26 24 27 Production (million cubic feet) Gross Withdrawals From Gas Wells 778 821 1,407 1,344 770 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

494

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Georgia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. Summary statistics for natural gas - Georgia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

495

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Delaware - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S8. Summary statistics for natural gas - Delaware, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

496

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 District of Columbia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

497