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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.


1

Combining Total Monte Carlo and Benchmarks for nuclear data uncertainty propagation on an LFRs safety parameters  

E-Print Network (OSTI)

Analyses are carried out to assess the impact of nuclear data uncertainties on keff for the European Lead Cooled Training Reactor (ELECTRA) using the Total Monte Carlo method. A large number of Pu-239 random ENDF-formated libraries generated using the TALYS based system were processed into ACE format with NJOY99.336 code and used as input into the Serpent Monte Carlo neutron transport code to obtain distribution in keff. The keff distribution obtained was compared with the latest major nuclear data libraries - JEFF-3.1.2, ENDF/B-VII.1 and JENDL-4.0. A method is proposed for the selection of benchmarks for specific applications using the Total Monte Carlo approach. Finally, an accept/reject criterion was investigated based on chi square values obtained using the Pu-239 Jezebel criticality benchmark. It was observed that nuclear data uncertainties in keff were reduced considerably from 748 to 443 pcm by applying a more rigid acceptance criteria for accepting random files.

Alhassan, Erwin; Duan, Junfeng; Gustavsson, Cecilia; Koning, Arjan; Pomp, Stephan; Rochman, Dimitri; Österlund, Michael

2013-01-01T23:59:59.000Z

2

Combining Total Monte Carlo and Benchmarks for nuclear data uncertainty propagation on an LFRs safety parameters  

E-Print Network (OSTI)

Analyses are carried out to assess the impact of nuclear data uncertainties on keff for the European Lead Cooled Training Reactor (ELECTRA) using the Total Monte Carlo method. A large number of Pu-239 random ENDF-formated libraries generated using the TALYS based system were processed into ACE format with NJOY99.336 code and used as input into the Serpent Monte Carlo neutron transport code to obtain distribution in keff. The keff distribution obtained was compared with the latest major nuclear data libraries - JEFF-3.1.2, ENDF/B-VII.1 and JENDL-4.0. A method is proposed for the selection of benchmarks for specific applications using the Total Monte Carlo approach. Finally, an accept/reject criterion was investigated based on chi square values obtained using the Pu-239 Jezebel criticality benchmark. It was observed that nuclear data uncertainties in keff were reduced considerably from 748 to 443 pcm by applying a more rigid acceptance criteria for accepting random files.

Erwin Alhassan; Henrik Sjöstrand; Junfeng Duan; Cecilia Gustavsson; Arjan Koning; Stephan Pomp; Dimitri Rochman; Michael Österlund

2013-03-26T23:59:59.000Z

3

Decision Based Uncertainty Propagation Using Adaptive Gaussian Mixtures  

E-Print Network (OSTI)

Propagation, Expected Loss, Improved Forecast. I. Introduction Chemical, Biological, Radiological, and Nuclear (DM) toolbox. Based on these forecasts, decisions can be made on evacuating cities, sheltering into a threat level, such as the population density in a city. Thus the ability to propagate the uncertainty

Singh, Tarunraj

4

PULCINELLA -- A General Tool for Propagating Uncertainty in Valuation Networks  

E-Print Network (OSTI)

We present PULCinella and its use in comparing uncertainty theories. PULCinella is a general tool for Propagating Uncertainty based on the Local Computation technique of Shafer and Shenoy. It may be specialized to different uncertainty theories: at the moment, Pulcinella can propagate probabilities, belief functions, Boolean values, and possibilities. Moreover, Pulcinella allows the user to easily define his own specializations. To illustrate Pulcinella, we analyze two examples by using each of the four theories above. In the first one, we mainly focus on intrinsic differences between theories. In the second one, we take a knowledge engineer viewpoint, and check the adequacy of each theory to a given problem.

Alessandro Saffiotti; Elisabeth Umkehrer

1991-01-01T23:59:59.000Z

5

Propagating and aggregating trust with uncertainty measure  

Science Conference Proceedings (OSTI)

Trust networks have been recognized as a valuable component of many modern systems, such as e-commerce or recommender systems, as they provide a way of quality assessment. In addition to adequate modeling of trust in such network, two fundamental issues ... Keywords: IFS, global trust, intuitionistic fuzzy sets, local trust, relative scalar cardinality of IFS, trust aggregation, trust propagation

Anna Stachowiak

2011-09-01T23:59:59.000Z

6

Propagation of nuclear data uncertainties for ELECTRA burn-up calculations  

E-Print Network (OSTI)

The European Lead-Cooled Training Reactor (ELECTRA) has been proposed as a training reactor for fast systems within the Swedish nuclear program. It is a low-power fast reactor cooled by pure liquid lead. In this work, we propagate the uncertainties in Pu-239 transport data to uncertainties in the fuel inventory of ELECTRA during the reactor life using the Total Monte Carlo approach (TMC). Within the TENDL project the nuclear models input parameters were randomized within their uncertainties and 740 Pu-239 nuclear data libraries were generated. These libraries are used as inputs to reactor codes, in our case SERPENT, to perform uncertainty analysis of nuclear reactor inventory during burn-up. The uncertainty in the inventory determines uncertainties in: the long-term radio-toxicity, the decay heat, the evolution of reactivity parameters, gas pressure and volatile fission product content. In this work, a methodology called fast TMC is utilized, which reduces the overall calculation time. The uncertainty in the long-term radiotoxicity, decay heat, gas pressure and volatile fission products were found to be insignificant. However, the uncertainty of some minor actinides were observed to be rather large and therefore their impact on multiple recycling should be investigated further. It was also found that, criticality benchmarks can be used to reduce inventory uncertainties due to nuclear data. Further studies are needed to include fission yield uncertainties, more isotopes, and a larger set of benchmarks.

H. Sjöstrand; E. Alhassan; J. Duan; C. Gustavsson; A. Koning; S. Pomp; D. Rochman; M. Österlund

2013-04-05T23:59:59.000Z

7

Uncertainty propagation in puff-based dispersion models using polynomial chaos  

Science Conference Proceedings (OSTI)

Atmospheric dispersion is a complex nonlinear physical process with numerous uncertainties in model parameters, inputs, source parameters, initial and boundary conditions. Accurate propagation of these uncertainties through the dispersion models is crucial ... Keywords: Atmospheric dispersion, Non-Gaussian distributions, Polynomial chaos, Sensitivity analysis, Uncertainty propagation

Umamaheswara Konda; Tarunraj Singh; Puneet Singla; Peter Scott

2010-12-01T23:59:59.000Z

8

Propagation of nuclear data uncertainties for ELECTRA burn-up calculations  

E-Print Network (OSTI)

The European Lead-Cooled Training Reactor (ELECTRA) has been proposed as a training reactor for fast systems within the Swedish nuclear program. It is a low-power fast reactor cooled by pure liquid lead. In this work, we propagate the uncertainties in Pu-239 transport data to uncertainties in the fuel inventory of ELECTRA during the reactor life using the Total Monte Carlo approach (TMC). Within the TENDL project the nuclear models input parameters were randomized within their uncertainties and 740 Pu-239 nuclear data libraries were generated. These libraries are used as inputs to reactor codes, in our case SERPENT, to perform uncertainty analysis of nuclear reactor inventory during burn-up. The uncertainty in the inventory determines uncertainties in: the long-term radio-toxicity, the decay heat, the evolution of reactivity parameters, gas pressure and volatile fission product content. In this work, a methodology called fast TMC is utilized, which reduces the overall calculation time. The uncertainty in the ...

ostrand, H; Duan, J; Gustavsson, C; Koning, A; Pomp, S; Rochman, D; Osterlund, M

2013-01-01T23:59:59.000Z

9

Uncertainty Propagation of Regional Climate Model Precipitation Forecasts to Hydrologic Impact Assessment  

Science Conference Proceedings (OSTI)

A Monte Carlo framework is adopted for propagating uncertainty in dynamically downscaled seasonal forecasts of area-averaged daily precipitation to associated streamflow response calculations. Daily precipitation is modeled as a mixture of two ...

Phaedon C. Kyriakidis; Norman L. Miller; Jinwon Kim

2001-04-01T23:59:59.000Z

10

MINERAL: A program for the propagation of analytical uncertainty through mineral formula recalculations  

Science Conference Proceedings (OSTI)

MINERAL (MINeral ERror AnaLysis) is a MATLAB^(R) based program that performs mineral formula recalculations and calculates the error on formula unit cations though the propagation of analytical uncertainties. The program is focused on 9 common mineral ... Keywords: Error, Mineral recalculation, Uncertainty

Sarah M. H. De Angelis; Owen K. Neill

2012-11-01T23:59:59.000Z

11

Bayesian uncertainty quantification and propagation in molecular dynamics simulations: A high performance computing framework  

Science Conference Proceedings (OSTI)

We present a Bayesian probabilistic framework for quantifying and propagating the uncertainties in the parameters of force fields employed in molecular dynamics (MD) simulations. We propose a highly parallel implementation of the transitional Markov chain Monte Carlo for populating the posterior probability distribution of the MD force-field parameters. Efficient scheduling algorithms are proposed to handle the MD model runs and to distribute the computations in clusters with heterogeneous architectures. Furthermore

Panagiotis Angelikopoulos; Costas Papadimitriou; Petros Koumoutsakos

2012-01-01T23:59:59.000Z

12

Nuclear data uncertainty propagation in a lattice physics code using stochastic sampling  

SciTech Connect

A methodology is presented for 'black box' nuclear data uncertainty propagation in a lattice physics code using stochastic sampling. The methodology has 4 components: i) processing nuclear data variance/covariance matrices including converting the native group structure to a group structure 'compatible' with the lattice physics code, ii) generating (relative) random samples of nuclear data, iii) perturbing the lattice physics code nuclear data according to the random samples, and iv) analyzing the distribution of outputs to estimate the uncertainty. The scheme is described as implemented at PSI, in a modified version of the lattice physics code CASMO-5M, including all relevant practical details. Uncertainty results are presented for a BWR pin-cell at hot zero power conditions and a PWR assembly at hot full power conditions with depletion. Results are presented for uncertainties in eigenvalue, 1-group microscopic cross sections, 2-group macroscopic cross sections, and isotopics. Interesting behavior is observed with burnup, including a minimum uncertainty due to the presence of fertile U-238 and a global effect described as 'synergy', observed when comparing the uncertainty resulting from simultaneous and one-at-a-time variations of nuclear data. (authors)

Wieselquist, W.; Vasiliev, A.; Ferroukhi, H. [Paul Scherrer Institut, 5232 Villigen (Switzerland)

2012-07-01T23:59:59.000Z

13

Uncertainty Propagation in Hypersonic Flight Dynamics and Comparison of Different Methods  

E-Print Network (OSTI)

In this work we present a novel computational framework for analyzing evolution of uncertainty in state trajectories of a hypersonic air vehicle due to uncertainty in initial conditions and other system parameters. The framework is built on the so called generalized Polynomial Chaos expansions. In this framework, stochastic dynamical systems are transformed into equivalent deterministic dynamical systems in higher dimensional space. In the research presented here we study evolution of uncertainty due to initial condition, ballistic coefficient, lift over drag ratio and atmospheric density. We compute the statistics using the continuous linearization (CL) approach. This approach computes the jacobian of the perturbational variables about the nominal trajectory. The covariance is then propagated using the riccati equation and the statistics is compared with the Polynomial Chaos method. The latter gives better accuracy as compared to the CL method. The simulation is carried out assuming uniform distribution on the parameters (initial condition, density, ballistic coefficient and lift over drag ratio). The method is then extended for Gaussian distribution on the parameters and the statistics, mean and variance of the states are matched with the standard Monte Carlo methods. The problem studied here is related to the Mars entry descent landing problem.

Prabhakar, Avinash

2008-12-01T23:59:59.000Z

14

2.6.4. Evaluation of type B uncertainty and propagation of ...  

Science Conference Proceedings (OSTI)

... in the formula above; ie, the partial derivative with respect to that variable from the propagation of error ... Resistance ratio, B, a 6 = 900.901, 0.0000308 ...

2012-03-31T23:59:59.000Z

15

THE PROPAGATION OF UNCERTAINTIES IN STELLAR POPULATION SYNTHESIS MODELING. III. MODEL CALIBRATION, COMPARISON, AND EVALUATION  

Science Conference Proceedings (OSTI)

Stellar population synthesis (SPS) provides the link between the stellar and dust content of galaxies and their observed spectral energy distributions. In the present work, we perform a comprehensive calibration of our own flexible SPS (FSPS) model against a suite of data. These data include ultraviolet, optical, and near-IR photometry, surface brightness fluctuations, and integrated spectra of star clusters in the Magellanic Clouds (MCs), M87, M31, and the Milky Way (MW), and photometry and spectral indices of both quiescent and post-starburst galaxies at z {approx} 0. Several public SPS models are intercompared, including the models of Bruzual and Charlot (BC03), Maraston (M05), and FSPS. The relative strengths and weaknesses of these models are evaluated, with the following conclusions: (1) the FSPS and BC03 models compare favorably with MC data at all ages, whereas M05 colors are too red and the age dependence is incorrect; (2) all models yield similar optical and near-IR colors for old metal-poor systems, and yet they all provide poor fits to the integrated J - K and V - K colors of both MW and M31 star clusters; (3) FSPS is able to fit all of the ultraviolet data because both the post-asymptotic giant branch (post-AGB) and horizontal branch evolutionary phases are handled flexibly, while the BC03 and M05 models fail in the far-UV, and both far- and near-UV, respectively; (4) all models predict ugr colors too red, D{sub n}4000 strengths too strong, and Hdelta{sub A} strengths too weak compared to massive red sequence galaxies, under the assumption that such galaxies are composed solely of old metal-rich stars; and (5) FSPS and, to a lesser extent, BC03 can reproduce the optical and near-IR colors of post-starburst galaxies, while M05 cannot. Reasons for these discrepancies are explored. The failure at predicting the ugr colors, D{sub n}4000, and Hdelta{sub A} strengths can be explained by some combination of a minority population of metal-poor stars, young stars, blue straggler and/or blue horizontal branch (HB) stars, but not by appealing to inadequacies in either theoretical stellar atmospheres or canonical evolutionary phases (e.g., the main-sequence turnoff). The different model predictions in the near-IR for intermediate age systems are due to different treatments of the thermally pulsating asymptotic giant branch stellar evolutionary phase. We emphasize that due to a lack of calibrating star cluster data in regions of the metallicity-age plane relevant for galaxies, all of these models continue to suffer from serious uncertainties that are difficult to quantify.

Conroy, Charlie; Gunn, James E. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

2010-04-01T23:59:59.000Z

16

Uncertainty Machine — User's Manual  

Science Conference Proceedings (OSTI)

... Figure 8: Resistance — Densities. ... Supplement 1 to the “Guide to the expression of uncertainty in measurement” — Propagation of distributions ...

2013-07-19T23:59:59.000Z

17

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

Science Conference Proceedings (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.

1999-09-20T23:59:59.000Z

18

Methodology for characterizing modeling and discretization uncertainties in computational simulation  

SciTech Connect

This research effort focuses on methodology for quantifying the effects of model uncertainty and discretization error on computational modeling and simulation. The work is directed towards developing methodologies which treat model form assumptions within an overall framework for uncertainty quantification, for the purpose of developing estimates of total prediction uncertainty. The present effort consists of work in three areas: framework development for sources of uncertainty and error in the modeling and simulation process which impact model structure; model uncertainty assessment and propagation through Bayesian inference methods; and discretization error estimation within the context of non-deterministic analysis.

ALVIN,KENNETH F.; OBERKAMPF,WILLIAM L.; RUTHERFORD,BRIAN M.; DIEGERT,KATHLEEN V.

2000-03-01T23:59:59.000Z

19

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

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

Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Census Division Total South...

20

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

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

Division Total West Mountain Pacific Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

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

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

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

(millions) Census Division Total South Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC13.7...

22

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

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

Census Division Total Midwest Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC12.7...

23

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

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

Census Division Total Northeast Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC11.7...

24

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

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

Census Division Total South Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

25

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

Gasoline and Diesel Fuel Update (EIA)

(millions) Census Division Total West Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC14.7...

26

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

27

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

28

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

29

Application of Gaussian Error Propagation Principles for Theoretical Assessment of Model Uncertainty in Simulated Soil Processes Caused by Thermal and Hydraulic Parameters  

Science Conference Proceedings (OSTI)

Statistical uncertainty in soil temperature and volumetric water content and related moisture and heat fluxes predicted by a state-of-the-art soil module [embedded in a numerical weather prediction (NWP) model] is analyzed by Gaussian error-...

Nicole Mölders; Mihailo Jankov; Gerhard Kramm

2005-12-01T23:59:59.000Z

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

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.....................................................

38

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.....................................................

39

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

40

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

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

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...............................

42

Assessment and Propagation of Model Uncertainty  

E-Print Network (OSTI)

space shuttle Challenger exploded shortly af- ter takeoff, leading to an intensive investigation of the reliability of the shuttle's propulsion

David Draper

2011-01-01T23:59:59.000Z

43

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

44

Quantifying uncertainty in LCA-modelling of waste management systems  

SciTech Connect

Highlights: Black-Right-Pointing-Pointer Uncertainty in LCA-modelling of waste management is significant. Black-Right-Pointing-Pointer Model, scenario and parameter uncertainties contribute. Black-Right-Pointing-Pointer Sequential procedure for quantifying uncertainty is proposed. Black-Right-Pointing-Pointer Application of procedure is illustrated by a case-study. - Abstract: Uncertainty analysis in LCA studies has been subject to major progress over the last years. In the context of waste management, various methods have been implemented but a systematic method for uncertainty analysis of waste-LCA studies is lacking. The objective of this paper is (1) to present the sources of uncertainty specifically inherent to waste-LCA studies, (2) to select and apply several methods for uncertainty analysis and (3) to develop a general framework for quantitative uncertainty assessment of LCA of waste management systems. The suggested method is a sequence of four steps combining the selected methods: (Step 1) a sensitivity analysis evaluating the sensitivities of the results with respect to the input uncertainties, (Step 2) an uncertainty propagation providing appropriate tools for representing uncertainties and calculating the overall uncertainty of the model results, (Step 3) an uncertainty contribution analysis quantifying the contribution of each parameter uncertainty to the final uncertainty and (Step 4) as a new approach, a combined sensitivity analysis providing a visualisation of the shift in the ranking of different options due to variations of selected key parameters. This tiered approach optimises the resources available to LCA practitioners by only propagating the most influential uncertainties.

Clavreul, Julie, E-mail: julc@env.dtu.dk [Department of Environmental Engineering, Technical University of Denmark, Miljoevej, Building 113, DK-2800 Kongens Lyngby (Denmark); Guyonnet, Dominique [BRGM, ENAG BRGM-School, BP 6009, 3 Avenue C. Guillemin, 45060 Orleans Cedex (France); Christensen, Thomas H. [Department of Environmental Engineering, Technical University of Denmark, Miljoevej, Building 113, DK-2800 Kongens Lyngby (Denmark)

2012-12-15T23:59:59.000Z

45

Uncertainty analysis  

SciTech Connect

An evaluation is made of the suitability of analytical and statistical sampling methods for making uncertainty analyses. The adjoint method is found to be well-suited for obtaining sensitivity coefficients for computer programs involving large numbers of equations and input parameters. For this purpose the Latin Hypercube Sampling method is found to be inferior to conventional experimental designs. The Latin hypercube method can be used to estimate output probability density functions, but requires supplementary rank transformations followed by stepwise regression to obtain uncertainty information on individual input parameters. A simple Cork and Bottle problem is used to illustrate the efficiency of the adjoint method relative to certain statistical sampling methods. For linear models of the form Ax=b it is shown that a complete adjoint sensitivity analysis can be made without formulating and solving the adjoint problem. This can be done either by using a special type of statistical sampling or by reformulating the primal problem and using suitable linear programming software.

Thomas, R.E.

1982-03-01T23:59:59.000Z

46

Chamber propagation  

SciTech Connect

Propagation of a heavy ion beam to the target appears possible under conditions thought to be realizable by several reactor designs. Beam quality at the lens is believed to provide adequate intensity at the target -- but the beam must pass through chamber debris and its self fields along the way. This paper reviews present consensus on propagation modes and presents recent results on the effects of photoionization of the beam ions by thermal x-rays from the heated target. Ballistic propagation through very low densities is a conservative mode. The more-speculative self-pinched mode, at 1 to 10 Torr, offers reactor advantages and is being re-examined by others. 13 refs.

Langdon, B.

1991-01-16T23:59:59.000Z

47

Experimental uncertainty estimation and statistics for data having interval uncertainty.  

SciTech Connect

This report addresses the characterization of measurements that include epistemic uncertainties in the form of intervals. It reviews the application of basic descriptive statistics to data sets which contain intervals rather than exclusively point estimates. It describes algorithms to compute various means, the median and other percentiles, variance, interquartile range, moments, confidence limits, and other important statistics and summarizes the computability of these statistics as a function of sample size and characteristics of the intervals in the data (degree of overlap, size and regularity of widths, etc.). It also reviews the prospects for analyzing such data sets with the methods of inferential statistics such as outlier detection and regressions. The report explores the tradeoff between measurement precision and sample size in statistical results that are sensitive to both. It also argues that an approach based on interval statistics could be a reasonable alternative to current standard methods for evaluating, expressing and propagating measurement uncertainties.

Kreinovich, Vladik (Applied Biomathematics, Setauket, New York); Oberkampf, William Louis (Applied Biomathematics, Setauket, New York); Ginzburg, Lev (Applied Biomathematics, Setauket, New York); Ferson, Scott (Applied Biomathematics, Setauket, New York); Hajagos, Janos (Applied Biomathematics, Setauket, New York)

2007-05-01T23:59:59.000Z

48

The uncertainties in estimating measurement uncertainties  

SciTech Connect

All measurements include some error. Whether measurements are used for accountability, environmental programs or process support, they are of little value unless accompanied by an estimate of the measurements uncertainty. This fact is often overlooked by the individuals who need measurements to make decisions. This paper will discuss the concepts of measurement, measurements errors (accuracy or bias and precision or random error), physical and error models, measurement control programs, examples of measurement uncertainty, and uncertainty as related to measurement quality. Measurements are comparisons of unknowns to knowns, estimates of some true value plus uncertainty; and are no better than the standards to which they are compared. Direct comparisons of unknowns that match the composition of known standards will normally have small uncertainties. In the real world, measurements usually involve indirect comparisons of significantly different materials (e.g., measuring a physical property of a chemical element in a sample having a matrix that is significantly different from calibration standards matrix). Consequently, there are many sources of error involved in measurement processes that can affect the quality of a measurement and its associated uncertainty. How the uncertainty estimates are determined and what they mean is as important as the measurement. The process of calculating the uncertainty of a measurement itself has uncertainties that must be handled correctly. Examples of chemistry laboratory measurement will be reviewed in this report and recommendations made for improving measurement uncertainties.

Clark, J.P.; Shull, A.H.

1994-07-01T23:59:59.000Z

49

A surrogate-based uncertainty quantification with quantifiable errors  

Science Conference Proceedings (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

50

Uncertainty quantification using polynomial chaos expansion with points of monomial cubature rules  

Science Conference Proceedings (OSTI)

This paper proposes an efficient method for estimating uncertainty propagation and identifying influence factors contributing to uncertainty. In general, the system is dominated by some of the main effects and lower-order interactions due to the sparsity-of-effect ... Keywords: Monomial cubature rules, Polynomial chaos expansion, Sampling points, Uncertainty quantification

D. L. Wei; Z. S. Cui; J. Chen

2008-12-01T23:59:59.000Z

51

Basic definitions of uncertainty  

Science Conference Proceedings (OSTI)

... Glossary. The following definitions are given in the ISO Guide to the Expression of Uncertainty in Measurement. Many additional ...

52

Sensitivity and Uncertainty Analysis  

Energy.gov (U.S. Department of Energy (DOE))

Summary Notes from 15 November 2007 Generic Technical Issue Discussion on Sensitivity and Uncertainty Analysis and Model Support

53

RUMINATIONS ON NDA MEASUREMENT UNCERTAINTY COMPARED TO DA UNCERTAINTY  

Science Conference Proceedings (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

54

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

55

Stochastic-Integral Models for Propagation-of-Uncertainty Problems ...  

Science Conference Proceedings (OSTI)

Bayesian inference of grain boundary properties from heterogeneous data · Comparison of Novel Microstructure Quantification Frameworks for Visualization,  ...

56

Uncertainty Quantification of Composite Laminate Damage with the Generalized Information Theory  

Science Conference Proceedings (OSTI)

This work presents a survey of five theories to assess the uncertainty of projectile impact induced damage on multi-layered carbon-epoxy composite plates. Because the types of uncertainty dealt with in this application are multiple (variability, ambiguity, and conflict) and because the data sets collected are sparse, characterizing the amount of delamination damage with probability theory alone is possible but incomplete. This motivates the exploration of methods contained within a broad Generalized Information Theory (GIT) that rely on less restrictive assumptions than probability theory. Probability, fuzzy sets, possibility, and imprecise probability (probability boxes (p-boxes) and Dempster-Shafer) are used to assess the uncertainty in composite plate damage. Furthermore, this work highlights the usefulness of each theory. The purpose of the study is not to compare directly the different GIT methods but to show that they can be deployed on a practical application and to compare the assumptions upon which these theories are based. The data sets consist of experimental measurements and finite element predictions of the amount of delamination and fiber splitting damage as multilayered composite plates are impacted by a projectile at various velocities. The physical experiments consist of using a gas gun to impact suspended plates with a projectile accelerated to prescribed velocities, then, taking ultrasound images of the resulting delamination. The nonlinear, multiple length-scale numerical simulations couple local crack propagation implemented through cohesive zone modeling to global stress-displacement finite element analysis. The assessment of damage uncertainty is performed in three steps by, first, considering the test data only; then, considering the simulation data only; finally, performing an assessment of total uncertainty where test and simulation data sets are combined. This study leads to practical recommendations for reducing the uncertainty and improving the prediction accuracy of the damage modeling and finite element simulation.

J. Lucero; F. Hemez; T. Ross; K.Kline; J.Hundhausen; T. Tippetts

2006-05-01T23:59:59.000Z

57

Surge and High Frequency Propagation in Industrial Power ...  

Science Conference Proceedings (OSTI)

... which is close to the result obtained by the pulse propagation time of ... Note also that this shorter line involves a lower total resistance; hence the IN ...

2013-05-17T23:59:59.000Z

58

Sensitivity and uncertainty analysis applied to the JHR reactivity prediction  

SciTech Connect

The on-going AMMON program in EOLE reactor at CEA Cadarache (France) provides experimental results to qualify the HORUS-3D/N neutronics calculation scheme used for the design and safety studies of the new Material Testing Jules Horowitz Reactor (JHR). This paper presents the determination of technological and nuclear data uncertainties on the core reactivity and the propagation of the latter from the AMMON experiment to JHR. The technological uncertainty propagation was performed with a direct perturbation methodology using the 3D French stochastic code TRIPOLI4 and a statistical methodology using the 2D French deterministic code APOLLO2-MOC which leads to a value of 289 pcm (1{sigma}). The Nuclear Data uncertainty propagation relies on a sensitivity study on the main isotopes and the use of a retroactive marginalization method applied to the JEFF 3.1.1 {sup 27}Al evaluation in order to obtain a realistic multi-group covariance matrix associated with the considered evaluation. This nuclear data uncertainty propagation leads to a K{sub eff} uncertainty of 624 pcm for the JHR core and 684 pcm for the AMMON reference configuration core. Finally, transposition and reduction of the prior uncertainty were made using the Representativity method which demonstrates the similarity of the AMMON experiment with JHR (the representativity factor is 0.95). The final impact of JEFF 3.1.1 nuclear data on the Begin Of Life (BOL) JHR reactivity calculated by the HORUS-3D/N V4.0 is a bias of +216 pcm with an associated posterior uncertainty of 304 pcm (1{sigma}). (authors)

Leray, O.; Vaglio-Gaudard, C.; Hudelot, J. P.; Santamarina, A.; Noguere, G. [CEA, DER, SPRC, F-13108 St Paul-Lez-Durance (France); Di-Salvo, J. [CEA, DER, SPEx, F-13108 St Paul-Lez-Durance (France)

2012-07-01T23:59:59.000Z

59

UNCERTAINTIES OF ANION AND TOC MEASUREMENTS AT THE DWPF LABORATORY  

DOE Green Energy (OSTI)

The Savannah River Remediation (SRR) Defense Waste Processing Facility (DWPF) has identified a technical issue related to the amount of antifoam added to the Chemical Process Cell (CPC). Specifically, due to the long duration of the concentration and reflux cycles for the Sludge Receipt and Adjustment Tank (SRAT), additional antifoam has been required. The additional antifoam has been found to impact the melter flammability analysis as an additional source of carbon and hydrogen. To better understand and control the carbon and hydrogen contributors to the melter flammability analysis, SRR's Waste Solidification Engineering (WSE) has requested, via a Technical Task Request (TTR), that the Savannah River National Laboratory (SRNL) conduct an error evaluation of the measurements of key Slurry Mix Evaporator (SME) anions. SRNL issued a Task Technical and Quality Assurance Plan (TTQAP) [2] in response to that request, and the work reported here was conducted under the auspices of that TTQAP. The TTR instructs SRNL to conduct an error evaluation of anion measurements generated by the DWPF Laboratory using Ion Chromatography (IC) performed on SME samples. The anions of interest include nitrate, oxalate, and formate. Recent measurements of SME samples for these anions as well as measurements of total organic carbon (TOC) were provided to SRNL by DWPF Laboratory Operations (Lab OPS) personnel for this evaluation. This work was closely coordinated with the efforts of others within SRNL that are investigating the Chemical Process Cell (CPC) contributions to the melter flammability. The objective of that investigation was to develop a more comprehensive melter flammability control strategy that when implemented in DWPF will rely on process measurements. Accounting for the uncertainty of the measurements is necessary for successful implementation. The error evaluations conducted as part of this task will facilitate the integration of appropriate uncertainties for the measurements utilized in that control strategy. The flammability control strategy presented in relies on SME measurements of TOC and nitrate while one of the uses by WSE of the oxalate and formate measurement data will be the estimation of the amount of carbon coming from antifoam additions. The estimation is to be conducted by backing out contributions to the measured TOC concentration in the SME from the oxalate and the formate concentrations that are measured in the SME. The resulting adjusted TOC value will provide a basis for WSE to estimate the amount of antifoam that was added for that SME batch. The uncertainties of the oxalate, formate, and TOC measurements provided by the evaluations conducted as part of this task will allow for the propagation of their uncertainties into the estimated quantity of carbon coming from the added antifoam. The purpose of this technical report is to present the measurements generated by the DWPF Laboratory for recent SME batches, to conduct an evaluation of their uncertainties, and to provide the approach for propagating the uncertainties associated with these measurements into DWPF's strategies for controlling melter flammability and for monitoring antifoam additions. JMP Version 7.0.2 was used to support the analyses presented in this report.

Edwards, T.

2011-04-07T23:59:59.000Z

60

Including uncertainty in hazard analysis through fuzzy measures  

Science Conference Proceedings (OSTI)

This paper presents a method for capturing the uncertainty expressed by an Hazard Analysis (HA) expert team when estimating the frequencies and consequences of accident sequences and provides a sound mathematical framework for propagating this uncertainty to the risk estimates for these accident sequences. The uncertainty is readily expressed as distributions that can visually aid the analyst in determining the extent and source of risk uncertainty in HA accident sequences. The results also can be expressed as single statistics of the distribution in a manner analogous to expressing a probabilistic distribution as a point-value statistic such as a mean or median. The study discussed here used data collected during the elicitation portion of an HA on a high-level waste transfer process to demonstrate the techniques for capturing uncertainty. These data came from observations of the uncertainty that HA team members expressed in assigning frequencies and consequences to accident sequences during an actual HA. This uncertainty was captured and manipulated using ideas from possibility theory. The result of this study is a practical method for displaying and assessing the uncertainty in the HA team estimates of the frequency and consequences for accident sequences. This uncertainty provides potentially valuable information about accident sequences that typically is lost in the HA process.

Bott, T.F.; Eisenhawer, S.W.

1997-12-01T23:59:59.000Z

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.


61

Mathematical treatment of uncertainty in the speech recognition process  

Science Conference Proceedings (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

62

Characteristic uncertainty relations  

E-Print Network (OSTI)

New uncertainty relations for n observables are established. The relations take the invariant form of inequalities between the characteristic coefficients of order r, r = 1,2,...,n, of the uncertainty matrix and the matrix of mean commutators of the observables. It is shown that the second and the third order characteristic inequalities for the three generators of SU(1,1) and SU(2) are minimized in the corresponding group-related coherent states with maximal symmetry.

D. A. Trifonov; S. G. Donev

1998-09-10T23:59:59.000Z

63

Strategies for Application of Isotopic Uncertainties in Burnup Credit  

SciTech Connect

Uncertainties in the predicted isotopic concentrations in spent nuclear fuel represent one of the largest sources of overall uncertainty in criticality calculations that use burnup credit. The methods used to propagate the uncertainties in the calculated nuclide concentrations to the uncertainty in the predicted neutron multiplication factor (k{sub eff}) of the system can have a significant effect on the uncertainty in the safety margin in criticality calculations and ultimately affect the potential capacity of spent fuel transport and storage casks employing burnup credit. Methods that can provide a more accurate and realistic estimate of the uncertainty may enable increased spent fuel cask capacity and fewer casks needing to be transported, thereby reducing regulatory burden on licensee while maintaining safety for transporting spent fuel. This report surveys several different best-estimate strategies for considering the effects of nuclide uncertainties in burnup-credit analyses. The potential benefits of these strategies are illustrated for a prototypical burnup-credit cask design. The subcritical margin estimated using best-estimate methods is discussed in comparison to the margin estimated using conventional bounding methods of uncertainty propagation. To quantify the comparison, each of the strategies for estimating uncertainty has been performed using a common database of spent fuel isotopic assay measurements for pressurized-light-water reactor fuels and predicted nuclide concentrations obtained using the current version of the SCALE code system. The experimental database applied in this study has been significantly expanded to include new high-enrichment and high-burnup spent fuel assay data recently published for a wide range of important burnup-credit actinides and fission products. Expanded rare earth fission-product measurements performed at the Khlopin Radium Institute in Russia that contain the only known publicly-available measurement for {sup 103}Rh have also been included.

Gauld, I.C.

2002-12-23T23:59:59.000Z

64

Uncertainty and calibration analysis  

SciTech Connect

All measurements contain some deviation from the true value which is being measured. In the common vernacular this deviation between the true value and the measured value is called an inaccuracy, an error, or a mistake. Since all measurements contain errors, it is necessary to accept that there is a limit to how accurate a measurement can be. The undertainty interval combined with the confidence level, is one measure of the accuracy for a measurement or value. Without a statement of uncertainty (or a similar parameter) it is not possible to evaluate if the accuracy of the measurement, or data, is appropriate. The preparation of technical reports, calibration evaluations, and design calculations should consider the accuracy of measurements and data being used. There are many methods to accomplish this. This report provides a consistent method for the handling of measurement tolerances, calibration evaluations and uncertainty calculations. The SRS Quality Assurance (QA) Program requires that the uncertainty of technical data and instrument calibrations be acknowledged and estimated. The QA Program makes some specific technical requirements related to the subject but does not provide a philosophy or method on how uncertainty should be estimated. This report was prepared to provide a technical basis to support the calculation of uncertainties and the calibration of measurement and test equipment for any activity within the Experimental Thermal-Hydraulics (ETH) Group. The methods proposed in this report provide a graded approach for estimating the uncertainty of measurements, data, and calibrations. The method is based on the national consensus standard, ANSI/ASME PTC 19.1.

Coutts, D.A.

1991-03-01T23:59:59.000Z

65

Quantum-Gravity phenomenology and high energy particle propagation  

E-Print Network (OSTI)

Quantum-gravity effects may introduce relevant consequences for the propagation and interaction of high energy cosmic rays particles. Assuming the space-time foamy structure results in an intrinsic uncertainty of energy and momentum of particles, we show how low energy (under GZK) observations can provide strong constraints on the role of the fluctuating space-time structure.

R. Aloisio; P. Blasi; A. Galante; P. L. Ghia; A. F. Grillo

2004-10-18T23:59:59.000Z

66

Numerical approach for quantification of epistemic uncertainty  

Science Conference Proceedings (OSTI)

In the field of uncertainty quantification, uncertainty in the governing equations may assume two forms: aleatory uncertainty and epistemic uncertainty. Aleatory uncertainty can be characterised by known probability distributions whilst epistemic uncertainty ... Keywords: Encapsulation problem, Epistemic uncertainty, Generalized polynomial chaos, Stochastic collocation, Uncertainty quantification

John Jakeman; Michael Eldred; Dongbin Xiu

2010-06-01T23:59:59.000Z

67

Nuclear data uncertainties by the PWR MOX/UO{sub 2} core rod ejection benchmark  

Science Conference Proceedings (OSTI)

Rod ejection transient of the OECD/NEA and U.S. NRC PWR MOX/UO{sub 2} core benchmark is considered under the influence of nuclear data uncertainties. Using the GRS uncertainty and sensitivity software package XSUSA the propagation of the uncertainties in nuclear data up to the transient calculations are considered. A statistically representative set of transient calculations is analyzed and both integral as well as local output quantities are compared with the benchmark results of different participants. It is shown that the uncertainties in nuclear data play a crucial role in the interpretation of the results of the simulation. (authors)

Pasichnyk, I.; Klein, M.; Velkov, K.; Zwermann, W.; Pautz, A. [Boltzmannstr. 14, D-85748 Garching b. Muenchen (Germany)

2012-07-01T23:59:59.000Z

68

Generalized survey propagation  

Science Conference Proceedings (OSTI)

Survey propagation (SP) has recently been discovered as an efficient algorithm in solving classes of hard constraint-satisfaction problems (CSP). Powerful as it is, SP is still a heuristic algorithm, and further understanding its algorithmic nature, ...

Ronghui Tu / Yongyi Mao, Jiying Zhao

2011-01-01T23:59:59.000Z

69

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

SciTech Connect

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

70

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

71

International Journal for Uncertainty Quantification 1(1), xxxxxx (2010) Preprint ANL/MCS-P1806-1110  

E-Print Network (OSTI)

in the propagation of material uncertainties through a simplified model of heat transport in a nuclear reactor core nuclear reactor system simulations, we found that approximation of the uncertainty effect by PRD is more. In Section 4, we describe the nuclear reactor model used in our numerical experiments and apply the PRD

Anitescu, Mihai

72

A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory.  

Science Conference Proceedings (OSTI)

Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and hence appeal, of evidence theory is that it allows a less restrictive specification of uncertainty than is possible within the axiomatic structure on which probability theory is based. Unfortunately, the propagation of an evidence theory representation for uncertainty through a model is more computationally demanding than the propagation of a probabilistic representation for uncertainty, with this difficulty constituting a serious obstacle to the use of evidence theory in the representation of uncertainty in predictions obtained from computationally intensive models. This presentation describes and illustrates a sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Preliminary trials indicate that the presented strategy can be used to propagate uncertainty representations based on evidence theory in analysis situations where naive sampling-based (i.e., unsophisticated Monte Carlo) procedures are impracticable due to computational cost.

Johnson, J. D. (Prostat, Mesa, AZ); Oberkampf, William Louis; Helton, Jon Craig (Arizona State University, Tempe, AZ); Storlie, Curtis B. (North Carolina State University, Raleigh, NC)

2006-10-01T23:59:59.000Z

73

national total  

U.S. Energy Information Administration (EIA)

AC Argentina AR Aruba AA Bahamas, The BF Barbados BB Belize BH Bolivia BL Brazil BR Cayman Islands CJ ... World Total ww NA--Table Posted: December 8, ...

74

Interaction of loading pattern and nuclear data uncertainties in reactor core calculations  

Science Conference Proceedings (OSTI)

Along with best-estimate calculations for design and safety analysis, understanding uncertainties is important to determine appropriate design margins. In this framework, nuclear data uncertainties and their propagation to full core calculations are a critical issue. To deal with this task, different error propagation techniques, deterministic and stochastic are currently developed to evaluate the uncertainties in the output quantities. Among these is the sampling based uncertainty and sensitivity software XSUSA which is able to quantify the influence of nuclear data covariance on reactor core calculations. In the present work, this software is used to investigate systematically the uncertainties in the power distributions of two PWR core loadings specified in the OECD UAM-Benchmark suite. With help of a statistical sensitivity analysis, the main contributors to the uncertainty are determined. Using this information a method is studied with which loading patterns of reactor cores can be optimized with regard to minimizing power distribution uncertainties. It is shown that this technique is able to halve the calculation uncertainties of a MOX/UOX core configuration. (authors)

Klein, M.; Gallner, L.; Krzykacz-Hausmann, B.; Pautz, A.; Velkov, K.; Zwermann, W. [Gesellschaft fuer Anlagen- und Reaktorsicherheit GRS MbH, Boltzmannstr. 14, D- 85748 Garching b. Muenchen (Germany)

2012-07-01T23:59:59.000Z

75

Demand Uncertainty and Price Dispersion.  

E-Print Network (OSTI)

??Demand uncertainty has been recognized as one factor that may cause price dispersion in perfectly competitive markets with costly and perishable capacity. With the persistence… (more)

Li, Suxi

2007-01-01T23:59:59.000Z

76

An Experimental Study of RSS-Based Indoor Localization Using Nonparametric Belief Propagation Based on Spanning Trees  

Science Conference Proceedings (OSTI)

Nonparametric belief propagation (NBP) is the well-known method for cooperative localization in wireless sensor networks. It is capable to provide information about location estimation with appropriate uncertainty and to accommodate non-Gaussian distance ... Keywords: Indoor localization, nonparametric belief propagation, spanning tree, breadth first search, sensor networks

Vladimir Savic; Adrián Población; Santiago Zazo; Mariano García

2010-07-01T23:59:59.000Z

77

Evaluating the role of uncertainty in electric utility capacity planning  

SciTech Connect

This final report on Evaluating the Role of Uncertainty in Electric Utility Capacity Planning is divided into separate sections addressing demand, supply and the simultaneous consideration of both and describes several mathematical characterizations of the effects of uncertainty on the capacity expansion decision. The basic objective is to develop more robust models which can appropriately include the fundamental uncertainties associated with capacity expansion planning in the electric utility industry. Much of what has been developed in this project has been incorporated into a long-term, computer model for capacity expansion planning. A review is provided of certain deterministic capacity expansion methodologies. The effect of load curve uncertainty on capacity planning is considered and the use of a certain expected load curve to account for uncertainty in demand is proposed. How uncertainty influences the allocation of capital costs among the various load curve realizations is also discussed. The supply side uncertainties of fuel prices and random availability of generating units are considered. In certain cases it is shown that the use of the expected fuel costs will furnish a solution which minimizes the total expected costs. The effect of derating units to account for their random availability is also characterized. A stochastic linear program formulated to examine the simultaneous consideration of fuel cost and demand uncertainties is analyzed. This volume includes the report text one appendix with information on linear programming-based analysis of marginal cost pricing in the electric utility industry.

Soyster, A.L.

1981-08-31T23:59:59.000Z

78

Quantum Gravitational Uncertainty of Transverse Position  

E-Print Network (OSTI)

It is argued that holographic bounds on the information content of spacetime might be directly measurable. A new uncertainty principle is conjectured to arise from quantum indeterminacy of nearly flat spacetime: Angular orientations of null trajectories of spatial length L are uncertain, with standard deviation in each transverse direction \\Delta \\theta> \\sqrt{l_P/L}, where l_p denotes the Planck length. It is shown that this angular uncertainty corresponds to the information loss and nonlocality that occur if 3+1-D spacetime has a holographic dual description in terms of Planck-scale waves on a 2+1D screen with encoding close to the Planck diffraction limit, and agrees with covariant holographic entropy bounds on total number of degrees of freedom. The spectrum and spatial structure of predicted quantum-gravitational ``holographic noise'' are estimated to be directly measurable over a broad range of frequencies using interferometers with current technology.

Craig J. Hogan

2007-03-29T23:59:59.000Z

79

Uncertainty in Integrated Assessment Scenarios  

SciTech Connect

The determination of climate policy is a decision under uncertainty. The uncertainty in future climate change impacts is large, as is the uncertainty in the costs of potential policies. Rational and economically efficient policy choices will therefore seek to balance the expected marginal costs with the expected marginal benefits. This approach requires that the risks of future climate change be assessed. The decision process need not be formal or quantitative for descriptions of the risks to be useful. Whatever the decision procedure, a useful starting point is to have as accurate a description of climate risks as possible. Given the goal of describing uncertainty in future climate change, we need to characterize the uncertainty in the main causes of uncertainty in climate impacts. One of the major drivers of uncertainty in future climate change is the uncertainty in future emissions, both of greenhouse gases and other radiatively important species such as sulfur dioxide. In turn, the drivers of uncertainty in emissions are uncertainties in the determinants of the rate of economic growth and in the technologies of production and how those technologies will change over time. This project uses historical experience and observations from a large number of countries to construct statistical descriptions of variability and correlation in labor productivity growth and in AEEI. The observed variability then provides a basis for constructing probability distributions for these drivers. The variance of uncertainty in growth rates can be further modified by expert judgment if it is believed that future variability will differ from the past. But often, expert judgment is more readily applied to projected median or expected paths through time. Analysis of past variance and covariance provides initial assumptions about future uncertainty for quantities that are less intuitive and difficult for experts to estimate, and these variances can be normalized and then applied to mean trends from a model for uncertainty projections. The probability distributions of these critical model drivers, and the resulting uncertainty in projections from a range of models, can provide the basis of future emission scenario set designs.

Mort Webster

2005-10-17T23:59:59.000Z

80

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.

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

Phenomenons and Methods: Uncertainty in Internal Symmetry Nets with Backpropagation in Image Processing  

Science Conference Proceedings (OSTI)

Internal Symmetry Nets are a new developed class of cellular neural networks. It originated from internal symmetry quantum physics, and noted by five irreducible representations from group theory. In this paper, uncertainty of the nets in a series of ... Keywords: internal symmetry, back propagation, momentum and learning rate, overfitting, recurrent cycles

Guanzhong Li

2009-05-01T23:59:59.000Z

82

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.

83

Autonomous Exploration: Driven by Uncertainty  

E-Print Network (OSTI)

Autonomous Exploration: Driven by Uncertainty Peter Whaite and Frank P. Ferrie TR-CIM-93-17 1993-6319 Telex: 05 268510 FAX: 514 398-7348 Email: cim@cim.mcgill.ca #12;Autonomous Exploration: Driven

Dudek, Gregory

84

Bayesian calibration Uncertainty Sensitivity analysis  

E-Print Network (OSTI)

available at www.sciencedirect.com journal homepage: www.elsevier.com/locate/ecolmodel Sensitivity and uncertainty analysis from a coupled 3-PG and soil organic matter decomposition model

Monte Carlo; Markov Chain

2008-01-01T23:59:59.000Z

85

Uncertainty in Air Quality Modeling  

Science Conference Proceedings (OSTI)

Under the direction of the AMS Steering Committee for the EPA Cooperative Agreement on Air Quality Modeling, a small group of scientists convened to consider the question of uncertainty in air quality modeling. Because the group was particularly ...

Douglas G. Fox

1984-01-01T23:59:59.000Z

86

Harvesting a renewable resource under uncertainty  

E-Print Network (OSTI)

Consider a valuable renewable resource whose biomass X2003. “Harvesting a renewable resource under uncertainty,”Harvesting a Renewable Resource under Uncertainty 1 (with

Saphores, Jean-Daniel M

2003-01-01T23:59:59.000Z

87

How do Uncertainties in the Surface Chemical Abundances of the Sun Affect the Predicted Solar Neutrino Fluxes?  

E-Print Network (OSTI)

We show that uncertainties in the values of the surface heavy element abundances of the Sun are the largest source of the theoretical uncertainty in calculating the p-p, pep, 8B, 13N, 15O, and 17F solar neutrino fluxes. We evaluate for the first time the sensitivity (partial derivative) of each solar neutrino flux with respect to the surface abundance of each element. We then calculate the uncertainties in each neutrino flux using `conservative (preferred)' and `optimistic' estimates for the uncertainties in the element abundances. The total conservative (optimistic) composition uncertainty in the predicted 8B neutrino flux is 11.6% (5.0%) when sensitivities to individual element abundances are used. The traditional method that lumps all abundances into a single quantity (total heavy element to hydrogen ratio, Z/X) yields a larger uncertainty, 20%. The uncertainties in the carbon, oxygen, neon, silicon, sulphur, and iron abundances all make significant contributions to the uncertainties in calculating solar neutrino fluxes; the uncertainties of different elements are most important for different neutrino fluxes. The uncertainty in the iron abundance is the largest source of the estimated composition uncertainties of the important 7Be and 8B solar neutrinos. Carbon is the largest contributor to the uncertainty in the calculation of the p-p, 13N, and 15O neutrino fluxes. However, for all neutrino fluxes, several elements contribute comparable amounts to the total composition uncertainty.

John N. Bahcall; Aldo M. Serenelli

2004-12-03T23:59:59.000Z

88

TRITIUM UNCERTAINTY ANALYSIS FOR SURFACE WATER SAMPLES AT THE SAVANNAH RIVER SITE  

Science Conference Proceedings (OSTI)

Radiochemical analyses of surface water samples, in the framework of Environmental Monitoring, have associated uncertainties for the radioisotopic results reported. These uncertainty analyses pertain to the tritium results from surface water samples collected at five locations on the Savannah River near the U.S. Department of Energy's Savannah River Site (SRS). Uncertainties can result from the field-sampling routine, can be incurred during transport due to the physical properties of the sample, from equipment limitations, and from the measurement instrumentation used. The uncertainty reported by the SRS in their Annual Site Environmental Report currently considers only the counting uncertainty in the measurements, which is the standard reporting protocol for radioanalytical chemistry results. The focus of this work is to provide an overview of all uncertainty components associated with SRS tritium measurements, estimate the total uncertainty according to ISO 17025, and to propose additional experiments to verify some of the estimated uncertainties. The main uncertainty components discovered and investigated in this paper are tritium absorption or desorption in the sample container, HTO/H{sub 2}O isotopic effect during distillation, pipette volume, and tritium standard uncertainty. The goal is to quantify these uncertainties and to establish a combined uncertainty in order to increase the scientific depth of the SRS Annual Site Environmental Report.

Atkinson, R.

2012-07-31T23:59:59.000Z

89

Uncertainty quantification for large-scale ocean circulation predictions.  

SciTech Connect

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

90

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.

91

Uncertainty Analysis for Broadband Solar Radiometric Instrumentation Calibrations and Measurements: An Update; Preprint  

DOE Green Energy (OSTI)

The measurement of broadband solar radiation has grown in importance since the advent of solar renewable energy technologies in the 1970's, and the concern about the Earth's radiation balance related to climate change in the 1990's. In parallel, standardized methods of uncertainty analysis and reporting have been developed. Historical and updated uncertainties are based on the current international standardized uncertainty analysis method. Despite the fact that new and sometimes overlooked sources of uncertainty have been identified over the period 1988 to 2004, uncertainty in broadband solar radiometric instrumentation remains at 3% to 5% for pyranometers, and 2% to 3% for pyrheliometers. Improvements in characterizing correction functions for radiometer data may reduce total uncertainty. We analyze the theoretical standardized uncertainty sensitivity coefficients for the instrumentation calibration measurement equation and highlight the single parameter (thermal offset voltages), which contributes the most to the observed calibration responsivities.

Myers, D. R.; Reda, I. M.; Wilcox, S. M.; Stoffel, T. L.

2004-04-01T23:59:59.000Z

92

Numerical study of error propagation in Monte Carlo depletion simulations  

Science Conference Proceedings (OSTI)

Improving computer technology and the desire to more accurately model the heterogeneity of the nuclear reactor environment have made the use of Monte Carlo depletion codes more attractive in recent years, and feasible (if not practical) even for 3-D depletion simulation. However, in this case statistical uncertainty is combined with error propagating through the calculation from previous steps. In an effort to understand this error propagation, a numerical study was undertaken to model and track individual fuel pins in four 17 x 17 PWR fuel assemblies. By changing the code's initial random number seed, the data produced by a series of 19 replica runs was used to investigate the true and apparent variance in k{sub eff}, pin powers, and number densities of several isotopes. While this study does not intend to develop a predictive model for error propagation, it is hoped that its results can help to identify some common regularities in the behavior of uncertainty in several key parameters. (authors)

Wyant, T.; Petrovic, B. [Nuclear and Radiological Engineering, Georgia Inst. of Technology, 770 State Street, Atlanta, GA 30332-0745 (United States)

2012-07-01T23:59:59.000Z

93

Propagation of trust and distrust  

Science Conference Proceedings (OSTI)

A (directed) network of people connected by ratings or trust scores, and a model for propagating those trust scores, is a fundamental building block in many of today's most successful e-commerce and recommendation systems. We develop a framework of trust ... Keywords: distrust, trust propagation, web of trust

R. Guha; Ravi Kumar; Prabhakar Raghavan; Andrew Tomkins

2004-05-01T23:59:59.000Z

94

Gas Explosion Characterization, Wave Propagation  

E-Print Network (OSTI)

of nuclear power plants. However, an evi- dent lack of knowledge in the field had demanded for a detaileds & Dt^boooo^j Risø-R-525 Gas Explosion Characterization, Wave Propagation (Small-Scale Experiments EXPLOSION CHARACTERIZATION, WAVE PROPAGATION (Small-Scale Experiments) G.C. Larsen Abstract. A number

95

IAEA CRP on HTGR Uncertainty Analysis: Benchmark Definition and Test Cases  

SciTech Connect

Uncertainty and sensitivity studies are essential elements of the reactor simulation code verification and validation process. Although several international uncertainty quantification activities have been launched in recent years in the LWR, BWR and VVER domains (e.g. the OECD/NEA BEMUSE program [1], from which the current OECD/NEA LWR Uncertainty Analysis in Modelling (UAM) benchmark [2] effort was derived), the systematic propagation of uncertainties in cross-section, manufacturing and model parameters for High Temperature Reactor (HTGR) designs has not been attempted yet. This paper summarises the scope, objectives and exercise definitions of the IAEA Coordinated Research Project (CRP) on HTGR UAM [3]. Note that no results will be included here, as the HTGR UAM benchmark was only launched formally in April 2012, and the specification is currently still under development.

Gerhard Strydom; Frederik Reitsma; Hans Gougar; Bismark Tyobeka; Kostadin Ivanov

2012-11-01T23:59:59.000Z

96

Propagating vs. Non-propagating Madden-Julian Oscillation Events  

Science Conference Proceedings (OSTI)

Basin-wide convective anomalies over the Indian Ocean (IO) associated with the Madden-Julian oscillation (MJO) sometimes propagate eastward and reach the west Pacific (WP), but sometimes do not. Long-term observations and reanalysis products are ...

Daehyun Kim; Jong-Seong Kug; Adam H. Sobel

97

Quantum Gravitational Uncertainty of Transverse Position  

E-Print Network (OSTI)

It is argued that holographic bounds on the information content of spacetime might be directly measurable. A new holographic uncertainty principle is conjectured as a quantum property of nearly flat spacetime: The spatial wavefunction of a body at rest at position L relative to any observer has a width in directions transverse to L greater than Delta x_H=C(Ll_P)^{1/2}, where l_p denotes the Planck length and C is of the order of unity. It is shown that this angular uncertainty Delta theta > C (l_P/L)^{1/2} corresponds to the information loss and nonlocality that occur if 3D space has a holographic dual description in terms of Planck-scale waves on a 2D screen with encoding close to the diffraction limit, and agrees with covariant holographic entropy bounds on total number of degrees of freedom. It is estimated that this effect can be precisely tested by interferometers capable of transverse position measurements, such as the Laser Interferometer Space Antenna.

Hogan, Craig J

2007-01-01T23:59:59.000Z

98

The method of belief scales as a means for dealing with uncertainty in tough regulatory decisions.  

SciTech Connect

Modeling and simulation is playing an increasing role in supporting tough regulatory decisions, which are typically characterized by variabilities and uncertainties in the scenarios, input conditions, failure criteria, model parameters, and even model form. Variability exists when there is a statistically significant database that is fully relevant to the application. Uncertainty, on the other hand, is characterized by some degree of ignorance. A simple algebraic problem was used to illustrate how various risk methodologies address variability and uncertainty in a regulatory context. These traditional risk methodologies include probabilistic methods (including frequensic and Bayesian perspectives) and second-order methods where variabilities and uncertainties are treated separately. Representing uncertainties with (subjective) probability distributions and using probabilistic methods to propagate subjective distributions can lead to results that are not logically consistent with available knowledge and that may not be conservative. The Method of Belief Scales (MBS) is developed as a means to logically aggregate uncertain input information and to propagate that information through the model to a set of results that are scrutable, easily interpretable by the nonexpert, and logically consistent with the available input information. The MBS, particularly in conjunction with sensitivity analyses, has the potential to be more computationally efficient than other risk methodologies. The regulatory language must be tailored to the specific risk methodology if ambiguity and conflict are to be avoided.

Pilch, Martin M.

2005-10-01T23:59:59.000Z

99

Incorporation of parametric uncertainty into complex kinetic mechanisms: Application to hydrogen oxidation in supercritical water  

SciTech Connect

In this study, uncertainty analysis is applied to a supercritical water hydrogen oxidation mechanism to determine the effect of uncertainties in reaction rate constants and species thermochemistry on predicted species concentrations. Forward rate constants and species thermochemistry are assumed to be the sole contributors to uncertainty in the reaction model with all other model parameters and inputs treated as deterministic quantities. Uncertainty propagation is performed using traditional Monte Carlo (MC) simulation and a new, more computationally efficient, probabilistic collocation method called the Deterministic Equivalent Modeling Method (DEMM). The results of both analyses show that there is considerable uncertainty in all predicted species concentrations. The predicted H{sub 2} and O{sub 2} concentrations vary {+-}70% from their median values. Similarly, the HO{sub 2} concentration ranges from +90 to {minus}70% of its median, while the H{sub 2}O{sub 2} concentration varies by +180 to {minus}80%. In addition, the DEMM methodology identified two key model parameters, the standard-state heat of formation of HO{sub 2} radical and the forward rate constant for H{sub 2}O{sub 2} dissociation, as the largest contributors to the uncertainty in the predicted hydrogen and oxygen species concentrations. The analyses further show that the change in model predictions due to the inclusion of real-gas effects, which are potentially important for SCWO process modeling, is small relative to the uncertainty introduced by the model parameters themselves.

Phenix, B.D.; Dinaro, J.L.; Tatang, M.A.; Tester, J.W.; Howard, J.B.; McRae, G.J. [Massachusetts Inst. of Tech., Cambridge, MA (United States). Dept. of Chemical Engineering and Energy Lab.

1998-01-01T23:59:59.000Z

100

An EPGPT-based approach for uncertainty quantification  

SciTech Connect

Generalized Perturbation Theory (GPT) has been widely used by many scientific disciplines to perform sensitivity analysis and uncertainty quantification. This manuscript employs recent developments in GPT theory, collectively referred to as Exact-to-Precision Generalized Perturbation Theory (EPGPT), to enable uncertainty quantification for computationally challenging models, e.g. nonlinear models associated with many input parameters and many output responses and with general non-Gaussian parameters distributions. The core difference between EPGPT and existing GPT is in the way the problem is formulated. GPT formulates an adjoint problem that is dependent on the response of interest. It tries to capture via the adjoint solution the relationship between the response of interest and the constraints on the state variations. EPGPT recasts the problem in terms of a smaller set of what is referred to as the 'active' responses which are solely dependent on the physics model and the boundary and initial conditions rather than on the responses of interest. The objective of this work is to apply an EPGPT methodology to propagate cross-sections variations in typical reactor design calculations. The goal is to illustrate its use and the associated impact for situations where the typical Gaussian assumption for parameters uncertainties is not valid and when nonlinear behavior must be considered. To allow this demonstration, exaggerated variations will be employed to stimulate nonlinear behavior in simple prototypical neutronics models. (authors)

Wang, C.; Abdel-Khalik, H. S. [Dept. of Nuclear Engineering, North Caroline State Univ., Raleigh, NC 27695 (United States)

2012-07-01T23:59:59.000Z

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.


101

Reconstruction of nonlinear wave propagation  

DOE Patents (OSTI)

Disclosed are systems and methods for characterizing a nonlinear propagation environment by numerically propagating a measured output waveform resulting from a known input waveform. The numerical propagation reconstructs the input waveform, and in the process, the nonlinear environment is characterized. In certain embodiments, knowledge of the characterized nonlinear environment facilitates determination of an unknown input based on a measured output. Similarly, knowledge of the characterized nonlinear environment also facilitates formation of a desired output based on a configurable input. In both situations, the input thus characterized and the output thus obtained include features that would normally be lost in linear propagations. Such features can include evanescent waves and peripheral waves, such that an image thus obtained are inherently wide-angle, farfield form of microscopy.

Fleischer, Jason W; Barsi, Christopher; Wan, Wenjie

2013-04-23T23:59:59.000Z

102

Sound propagation around underwater seamounts  

E-Print Network (OSTI)

In the ocean, low frequency acoustic waves propagate with low attenuation and cylindrical spreading loss over long-ranges, making them an effective tool for underwater source localization, tomography, and communications. ...

Sikora, Joseph J., III

2009-01-01T23:59:59.000Z

103

Analysis of the lumped fission-product uncertainty in CRBR  

Science Conference Proceedings (OSTI)

An approximation made in most fast reactor analyses is to utilize a single lumped fission product (FP) cross-section set to represent the total effect of the approximately 800 possible fission product nuclides in a depleted reactor model. Recent investigations have analyzed several aspects of this one-lump approximation (burnup dependence, comparison with a two-lump model, etc.), but little has been done in addressing the quality, or uncertainty, in the basic cross-section data utilized in any such representation. Thus, the purpose of this study is to investigate the uncertainty in the FP reactivity effect due to the data uncertainties inherent in an ENDF/B-V composite FP representation specifically designed for application with the current CRBR heterogeneous core concept.

White, J.R.; Schenter, R.E.

1981-01-01T23:59:59.000Z

104

Propagation in nonlocal optical potentials  

SciTech Connect

It is shown that a nonlocal optical potential implies multiple eigenmode propagation. This is important when the mean free path becomes of the order of the nonlocality, such as in the strong absorption situation occurring for pion scattering near the 3-3 resonance, and consequently the propagation cannot be described reasonably by one complex wave number. The eigenmode structure can be seen most directly in quasielastic scattering.

Lenz, F.; Moniz, E.J.

1975-09-01T23:59:59.000Z

105

Quantifying uncertainty from material inhomogeneity.  

SciTech Connect

Most engineering materials are inherently inhomogeneous in their processing, internal structure, properties, and performance. Their properties are therefore statistical rather than deterministic. These inhomogeneities manifest across multiple length and time scales, leading to variabilities, i.e. statistical distributions, that are necessary to accurately describe each stage in the process-structure-properties hierarchy, and are ultimately the primary source of uncertainty in performance of the material and component. When localized events are responsible for component failure, or when component dimensions are on the order of microstructural features, this uncertainty is particularly important. For ultra-high reliability applications, the uncertainty is compounded by a lack of data describing the extremely rare events. Hands-on testing alone cannot supply sufficient data for this purpose. To date, there is no robust or coherent method to quantify this uncertainty so that it can be used in a predictive manner at the component length scale. The research presented in this report begins to address this lack of capability through a systematic study of the effects of microstructure on the strain concentration at a hole. To achieve the strain concentration, small circular holes (approximately 100 {micro}m in diameter) were machined into brass tensile specimens using a femto-second laser. The brass was annealed at 450 C, 600 C, and 800 C to produce three hole-to-grain size ratios of approximately 7, 1, and 1/7. Electron backscatter diffraction experiments were used to guide the construction of digital microstructures for finite element simulations of uniaxial tension. Digital image correlation experiments were used to qualitatively validate the numerical simulations. The simulations were performed iteratively to generate statistics describing the distribution of plastic strain at the hole in varying microstructural environments. In both the experiments and simulations, the deformation behavior was found to depend strongly on the character of the nearby microstructure.

Battaile, Corbett Chandler; Emery, John M.; Brewer, Luke N.; Boyce, Brad Lee

2009-09-01T23:59:59.000Z

106

Quantifying Uncertainty in Epidemiological Models  

SciTech Connect

Modern epidemiology has made use of a number of mathematical models, including ordinary differential equation (ODE) based models and agent based models (ABMs) to describe the dynamics of how a disease may spread within a population and enable the rational design of strategies for intervention that effectively contain the spread of the disease. Although such predictions are of fundamental importance in preventing the next global pandemic, there is a significant gap in trusting the outcomes/predictions solely based on such models. Hence, there is a need to develop approaches such that mathematical models can be calibrated against historical data. In addition, there is a need to develop rigorous uncertainty quantification approaches that can provide insights into when a model will fail and characterize the confidence in the (possibly multiple) model outcomes/predictions, when such retrospective analysis cannot be performed. In this paper, we outline an approach to develop uncertainty quantification approaches for epidemiological models using formal methods and model checking. By specifying the outcomes expected from a model in a suitable spatio-temporal logic, we use probabilistic model checking methods to quantify the probability with which the epidemiological model satisfies the specification. We argue that statistical model checking methods can solve the uncertainty quantification problem for complex epidemiological models.

Ramanathan, Arvind [ORNL; Jha, Sumit Kumar [University of Central Florida

2012-01-01T23:59:59.000Z

107

Multidelity approaches for design under uncertainty  

E-Print Network (OSTI)

Uncertainties are present in many engineering applications and it is important to account for their effects during engineering design to achieve robust and reliable systems. One approach is to represent uncertainties as ...

Ng, Leo Wai-Tsun

2013-01-01T23:59:59.000Z

108

Optimization under uncertainty in radiation therapy  

E-Print Network (OSTI)

In the context of patient care for life-threatening illnesses, the presence of uncertainty may compromise the quality of a treatment. In this thesis, we investigate robust approaches to managing uncertainty in radiation ...

Chan, Timothy Ching-Yee

2007-01-01T23:59:59.000Z

109

Reliable water supply system design under uncertainty  

Science Conference Proceedings (OSTI)

Given the natural variability and uncertainties in long-term predictions, reliability is a critical design factor for water supply systems. However, the large scale of the problem and the correlated nature of the involved uncertainties result in models ... Keywords: Data uncertainty, Robust optimization, Spatially correlated data, Water supply system

G. Chung; K. Lansey; G. Bayraksan

2009-04-01T23:59:59.000Z

110

Quantum Mechanics and the Generalized Uncertainty Principle  

E-Print Network (OSTI)

The generalized uncertainty principle has been described as a general consequence of incorporating a minimal length from a theory of quantum gravity. We consider a simple quantum mechanical model where the operator corresponding to position has discrete eigenvalues and show how the generalized uncertainty principle results for minimum uncertainty wave packets.

Jang Young Bang; Micheal S. Berger

2006-10-11T23:59:59.000Z

111

Uncertainty Assessments in Severe Nuclear Accident Scenarios  

Science Conference Proceedings (OSTI)

Managing uncertainties in industrial systems is a daily challenge to ensure improved design, robust operation, accountable performance and responsive risk control. This paper aims to illustrate the different depth analyses that the uncertainty software ... Keywords: Monte Carlo simulation, nuclear power plant, sensitivity analysis, severe accident, uncertainty

Bertrand Iooss; Fabrice Gaudier; Michel Marques; Bertrand Spindler; Bruno Tourniaire

2009-09-01T23:59:59.000Z

112

Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment. Volume 3, Appendices C, D, E, F, and G  

SciTech Connect

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, completed in 1990, 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 objective was to develop credible and traceable uncertainty distributions for the input variables of the codes. Expert elicitation, developed independently, 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. 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 along with the Gaussian plume model (GPM) implemented in the MACCS and COSYMA codes. Resulting distributions closely replicated the aggregated elicited wet deposition distributions. 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 third of a three-volume document describing the project and contains descriptions of the probability assessment principles; the expert identification and selection process; the weighting methods used; the inverse modeling methods; case structures; and summaries of the consequence codes.

Harper, F.T.; Young, M.L.; Miller, L.A. [Sandia National Labs., Albuquerque, NM (United States)] [and others

1995-01-01T23:59:59.000Z

113

Uncertainties in forecasting future climate  

SciTech Connect

The increasing atmospheric concentrations of carbon dioxide, methane, chlorofluorocarbons, and other trace gases (collectively, greenhouse gases) pose a three-part challenge: (1) What the changes to atmospheric composition and the climate system will be; (2) What impacts (both detrimental and beneficial) these changes will induce on the biosphere and natural and societal resources; and (3) What the appropriate response, if any, might be when considering the changes themselves, the resulting impacts, and the benefits and other impacts of the activities generating the emissions. This brief summary will address only areas of agreement and areas of uncertainty related to the first challenge.

MacCracken, M.C.

1990-11-01T23:59:59.000Z

114

Essays on pricing under uncertainty  

E-Print Network (OSTI)

This dissertation analyzes pricing under uncertainty focusing on the U.S. airline industry. It sets to test theories of price dispersion driven by uncertainty in the demand by taking advantage of very detailed information about the dynamics of airline prices and inventory levels as the flight date approaches. Such detailed information about inventories at a ticket level to analyze airline pricing has been used previously by the author to show the importance of capacity constraints in airline pricing. This dissertation proposes and implements many new ideas to analyze airline pricing. Among the most important are: (1) It uses information about inventories at a ticket level. (2) It is the first to note that fare changes can be explained by adding dummy variables representing ticket characteristics. Therefore, the load factor at a ticket level will lose its explanatory power on fares if all ticket characteristics are included in a pricing equation. (3) It is the first to propose and implement a measure of Expected Load Factor as a tool to identify which flights are peak and which ones are not. (4) It introduces a novel idea of comparing actual sales with average sales at various points prior departure. Using these deviations of actual sales from sales under average conditions, it presents is the first study to show empirical evidence of peak load pricing in airlines. (5) It controls for potential endogeneity of sales using dynamic panels. The first essay tests the empirical importance of theories that explain price dispersion under costly capacity and demand uncertainty. The essay calculates a measure of an Expected Load Factor, that is used to calibrate the distribution of demand uncertainty and to identify which flights are peak and which ones are off-peak. It shows that different prices can be explained by the different selling probabilities. The second essay is the first study to provide formal evidence of stochastic peak-load pricing in airlines. It shows that airlines learn about the demand and respond to early sales setting higher prices when expected demand is high and more likely to exceed capacity.

Escobari Urday, Diego Alfonso

2008-05-01T23:59:59.000Z

115

The Generalized Uncertainty Principle and Black Hole Remnants  

DOE Green Energy (OSTI)

In the current standard viewpoint small black holes are believed to emit black body radiation at the Hawking temperature, at least until they approach Planck size, after which their fate is open to conjecture. A cogent argument against the existence of remnants is that, since no evident quantum number prevents it, black holes should radiate completely away to photons and other ordinary stable particles and vacuum, like any unstable quantum system. Here we argue the contrary, that the generalized uncertainty principle may prevent their total evaporation in exactly the same way that the uncertainty principle prevents the hydrogen atom from total collapse: the collapse is prevented, not by symmetry, but by dynamics, as a minimum size and mass are approached.

Chen, Pisin

2001-06-01T23:59:59.000Z

116

Quantification of Uncertainties Due to Opacities in a Laser-Driven Radiative-Shock Problem  

E-Print Network (OSTI)

This research presents new physics-based methods to estimate predictive uncertainty stemming from uncertainty in the material opacities in radiative transfer computations of key quantities of interest (QOIs). New methods are needed because it is infeasible to apply standard uncertainty-propagation techniques to the O(105) uncertain opacities in a realistic simulation. The new approach toward uncertainty quantification applies the uncertainty analysis to the physical parameters in the underlying model used to calculate the opacities. This set of uncertain parameters is much smaller (O(102)) than the number of opacities. To further reduce the dimension of the set of parameters to be rigorously explored, we use additional screening applied at two different levels of the calculational hierarchy: first, physics-based screening eliminates the physical parameters that are unimportant from underlying physics models a priori; then, sensitivity analysis in simplified versions of the complex problem of interest screens out parameters that are not important to the QOIs. We employ a Bayesian Multivariate Adaptive Regression Spline (BMARS) emulator for this sensitivity analysis. The high dimension of the input space and large number of samples test the efficacy of these methods on larger problems. Ultimately, we want to perform uncertainty quantification on the large, complex problem with the reduced set of parameters. Results of this research demonstrate that the QOIs for target problems agree at for different parameter screening criteria and varying sample sizes. Since the QOIs agree, we have gained confidence in our results using the multiple screening criteria and sample sizes.

Hetzler, Adam C

2013-05-01T23:59:59.000Z

117

Bayesian Neural Networks for Uncertainty Analysis of Hydrologic Modeling: A Comparison of Two Schemes  

SciTech Connect

Bayesian Neural Networks (BNNs) have been shown as useful tools to analyze modeling uncertainty of Neural Networks (NNs). This research focuses on the comparison of two BNNs. The first BNNs (BNN-I) use statistical methods to describe the characteristics of different uncertainty sources (input, parameter, and model structure) and integrate these uncertainties into a Markov Chain Monte Carlo (MCMC) framework to estimate total uncertainty. The second BNNs (BNN-II) lump all uncertainties into a single error term (i.e. the residual between model prediction and measurement). In this study, we propose a simple BNN-II, which use Genetic Algorithms (GA) and Bayesian Model Averaging (BMA) to calibrate Neural Networks with different structures (number of hidden units) and combine the predictions from different NNs to derive predictions and uncertainty analysis. We tested these two BNNs in two watersheds for daily and monthly hydrologic simulation. The BMA based BNNs developed in this study outperforms BNN-I in the two watersheds in terms of both accurate prediction and uncertainty estimation. These results show that, given incomplete understanding of the characteristics associated with each uncertainty source, the simple lumped error approach may yield better prediction and uncertainty estimation.

Zhang, Xuesong; Zhao, Kaiguang

2012-06-01T23:59:59.000Z

118

Quantification of stochastic uncertainty propagation for Monte Carlo depletion methods in reactor analysis.  

E-Print Network (OSTI)

??The Monte Carlo method provides powerful geometric modeling capabilities for large problem domains in 3-D; therefore, the Monte Carlo method is becoming popular for 3-D… (more)

Newell, Quentin Thomas

2011-01-01T23:59:59.000Z

119

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

120

Propagating Subsurface Uncertainty to the Atmosphere Using Fully Coupled Stochastic Simulations  

Science Conference Proceedings (OSTI)

Feedbacks between the land surface and the atmosphere, manifested as mass and energy fluxes, are strongly correlated with soil moisture, making soil moisture an important factor in land–atmosphere interactions. It is shown that a reduction of the ...

John L. Williams III; Reed M. Maxwell

2011-08-01T23:59:59.000Z

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.  

Science Conference Proceedings (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

Propagators in Nonrelativistic Quantum Mechanics  

Science Conference Proceedings (OSTI)

A discussion of propagators (Green's functions) and methods for calculating them for the simplest systems in nonrelativistic quantum mechanics is given from several points of view. The relevance of such techniques to partition function calculations is pointed out. Finally

Laurent A. Beauregard

1966-01-01T23:59:59.000Z

123

A flexible numerical approach for quantification of epistemic uncertainty  

Science Conference Proceedings (OSTI)

In the field of uncertainty quantification (UQ), epistemic uncertainty often refers to the kind of uncertainty whose complete probabilistic description is not available, largely due to our lack of knowledge about the uncertainty. Quantification of the ... Keywords: Encapsulation problem, Epistemic uncertainty, Generalized polynomial chaos, Uncertainty quantification

Xiaoxiao Chen; Eun-Jae Park; Dongbin Xiu

2013-05-01T23:59:59.000Z

124

Holographic Indeterminacy, Uncertainty and Noise  

E-Print Network (OSTI)

A theory is developed to describe the nonlocal effect of spacetime quantization on position measurements transverse to macroscopic separations. Spacetime quantum states close to a classical null trajectory are approximated by plane wavefunctions of Planck wavelength (l_P) reference beams; these are used to connect transverse position operators at macroscopically separated events. Transverse positions of events with null spacetime separation, but separated by macroscopic spatial distance $L$, are shown to be quantum conjugate observables, leading to holographic indeterminacy and a new uncertainty principle, a lower bound on the standard deviation of relative transverse position \\Delta x_\\perp > \\sqrt{l_PL} or angular orientation \\Delta\\theta > \\sqrt{l_P/L}. The resulting limit on the number of independent degrees of freedom is shown to agree quantitatively with holographic covariant entropy bounds derived from black hole physics and string theory. The theory predicts a universal ``holographic noise'' of spacet...

Hogan, Craig J

2007-01-01T23:59:59.000Z

125

ARM - PI Product - Direct Aerosol Forcing Uncertainty  

NLE Websites -- All DOE Office Websites (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

126

Joint quantum measurements with minimum uncertainty  

E-Print Network (OSTI)

Quantum physics constrains the accuracy of joint measurements of incompatible observables. Here we test tight measurement-uncertainty relations using single photons. We implement two independent, idealized uncertainty-estimation methods, the 3-state method and the weak-measurement method, and adapt them to realistic experimental conditions. Exceptional quantum state fidelities of up to 0.99998(6) allow us to verge upon the fundamental limits of measurement uncertainty.

Martin Ringbauer; Devon N. Biggerstaff; Matthew A. Broome; Alessandro Fedrizzi; Cyril Branciard; Andrew G. White

2013-08-26T23:59:59.000Z

127

Long Term Power Generation Planning Under Uncertainty.  

E-Print Network (OSTI)

??Generation expansion planning concerns investment and operation decisions for different types of power plants over a multi-decade horizon under various uncertainties. The goal of this… (more)

Jin, Shan

2009-01-01T23:59:59.000Z

128

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

129

Dynamic Linear Production Games under Uncertainty  

E-Print Network (OSTI)

Oct 2, 2013 ... Abstract: In situations where uncertain costs are shared over time, static ... under uncertainty, generalizing classical linear production games to ...

130

A Partial Order on Uncertainty and Information  

E-Print Network (OSTI)

Information and uncertainty are closely related and extensively studied concepts in a number of scientific disciplines such as communication theory, probability theory, and statistics. Increasing the information arguably reduces the uncertainty on a given random subject. Consider the uncertainty measure as the variance of a random variable. Given the information that its outcome is in an interval, the uncertainty is expected to reduce when the interval shrinks. This proposition is not generally true. In this paper, we provide a necessary and sufficient condition for this proposition when the random variable is absolutely continuous or integer valued. We also give a similar result on Shannon information.

Chen, Jiahua

2011-01-01T23:59:59.000Z

131

High-Dose Dosimetry Uncertainty Tables  

Science Conference Proceedings (OSTI)

... 4.0. Alanine Transfer - E-Beam, Uncertainty Source, Type A (%), Type B (%). ... Calibration Curve, 0.50, 0.10. Electron Energy Dependence, 0.10. ...

2013-04-02T23:59:59.000Z

132

Essays in inventory decisions under uncertainty .  

E-Print Network (OSTI)

??Uncertainty is a norm in business decisions. In this research, we focus on the inventory decisions for companies with uncertain customer demands. We first investigate… (more)

Manikas, Andrew Steven

2008-01-01T23:59:59.000Z

133

Design Feasibility Analysis and Optimization under Uncertainty...  

NLE Websites -- All DOE Office Websites (Extended Search)

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...

134

Rossby Wave Propagation an Beta-Planes  

Science Conference Proceedings (OSTI)

The numerical modeling of stratospheric, quasi-geostrophic Rossby wave propagation on a beta-plane channel is examined to determine how wave propagation is affected by the use of low horizontal (spectral) resolution. This study considers time ...

Donal O'Sullivan

1988-01-01T23:59:59.000Z

135

Propagation of Tracer Signals in Boundary Currents  

Science Conference Proceedings (OSTI)

The propagation of a range of tracer signals in a simple model of the deep western boundary current is examined. Analytical expressions are derived in certain limits for the transit-time distributions and the propagation times (tracer ages) of ...

Darryn W. Waugh; Timothy M. Hall

2005-09-01T23:59:59.000Z

136

Monte Carlo parameter studies and uncertainty analyses with MCNP5  

SciTech Connect

A software tool called mcnp-pstudy has been developed to automate the setup, execution, and collection of results from a series of MCNPS Monte Carlo calculations. This tool provides a convenient means of performing parameter studies, total uncertainty analyses, parallel job execution on clusters, stochastic geometry modeling, and other types of calculations where a series of MCNPS jobs must be performed with varying problem input specifications. Monte Carlo codes are being used for a wide variety of applications today due to their accurate physical modeling and the speed of today's computers. In most applications for design work, experiment analysis, and benchmark calculations, it is common to run many calculations, not just one, to examine the effects of design tolerances, experimental uncertainties, or variations in modeling features. We have developed a software tool for use with MCNP5 to automate this process. The tool, mcnp-pstudy, is used to automate the operations of preparing a series of MCNP5 input files, running the calculations, and collecting the results. Using this tool, parameter studies, total uncertainty analyses, or repeated (possibly parallel) calculations with MCNP5 can be performed easily. Essentially no extra user setup time is required beyond that of preparing a single MCNP5 input file.

Brown, F. B. (Forrest B.); Sweezy, J. E. (Jeremy E.); Hayes, R. B. (Robert B.)

2004-01-01T23:59:59.000Z

137

EMISSION AND TRANSMISSION NOISE PROPAGATION IN POSITRON EMISSION COMPUTED TOMOGRAPHY  

E-Print Network (OSTI)

26-29, 1979 EMISSION AND TRANSMISSION NOISE PROPAGATION INLBL-9783 EMISSION AND TRANSMISSION NOISE PROPAGATION INl·. LBL-9783 EMISSION AND TRANSMISSION NOISE PROPAGATION IN

Gullberg, G.T.

2010-01-01T23:59:59.000Z

138

Stochastic Programming of Vehicle to Building Interactions with Uncertainty  

NLE Websites -- All DOE Office Websites (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.

139

Propagation of Trust and Distrust  

E-Print Network (OSTI)

A network of people connected by directed ratings or trust scores, and a model for propagating those trust scores, is a fundamental building block in many of today's most successful e-commerce and recommendation systems. In eBay, such a model of trust has significant influence on the price an item may command. In Epinions (epinions.com), conclusions drawn from the web of trust are linked to many behaviors of the system, including decisions on items to which each user is exposed. We develop a framework of trust propagation schemes, each of which may be appropriate in certain circumstances, and evaluate the schemes on a large trust network consisting of 800K trust scores expressed among 130K people. We show that a small number of expressed trusts/distrust per individual allows us to predict reliably trust between any two people in the system with high accuracy: a quadratic increase in actionable information. Our work appears to be the first to incorporate distrust in a computational trust propagation setting.

R. Guha; Ravi Kumar; Prabhakar Raghavan; Andrew Tomkins

2004-01-01T23:59:59.000Z

140

CALiPER Exploratory Study: Accounting for Uncertainty in Lumen Measurements  

SciTech Connect

With a well-defined and shared understanding of uncertainty in lumen measurements, testing laboratories can better evaluate their processes, contributing to greater consistency and credibility of lighting testing a key component of the U.S. Department of Energy (DOE) Commercially Available LED Product Evaluation and Reporting (CALiPER) program. Reliable lighting testing is a crucial underlying factor contributing toward the success of many energy-efficient lighting efforts, such as the DOE GATEWAY demonstrations, Lighting Facts Label, ENERGY STAR® energy efficient lighting programs, and many others. Uncertainty in measurements is inherent to all testing methodologies, including photometric and other lighting-related testing. Uncertainty exists for all equipment, processes, and systems of measurement in individual as well as combined ways. A major issue with testing and the resulting accuracy of the tests is the uncertainty of the complete process. Individual equipment uncertainties are typically identified, but their relative value in practice and their combined value with other equipment and processes in the same test are elusive concepts, particularly for complex types of testing such as photometry. The total combined uncertainty of a measurement result is important for repeatable and comparative measurements for light emitting diode (LED) products in comparison with other technologies as well as competing products. This study provides a detailed and step-by-step method for determining uncertainty in lumen measurements, working closely with related standards efforts and key industry experts. This report uses the structure proposed in the Guide to Uncertainty Measurements (GUM) for evaluating and expressing uncertainty in measurements. The steps of the procedure are described and a spreadsheet format adapted for integrating sphere and goniophotometric uncertainty measurements is provided for entering parameters, ordering the information, calculating intermediate values and, finally, obtaining expanded uncertainties. Using this basis and examining each step of the photometric measurement and calibration methods, mathematical uncertainty models are developed. Determination of estimated values of input variables is discussed. Guidance is provided for the evaluation of the standard uncertainties of each input estimate, covariances associated with input estimates and the calculation of the result measurements. With this basis, the combined uncertainty of the measurement results and finally, the expanded uncertainty can be determined.

Bergman, Rolf; Paget, Maria L.; Richman, Eric E.

2011-03-31T23:59:59.000Z

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

Constructing Uncertainty Sets for Robust Linear Optimization  

Science Conference Proceedings (OSTI)

In this paper, we propose a methodology for constructing uncertainty sets within the framework of robust optimization for linear optimization problems with uncertain parameters. Our approach relies on decision maker risk preferences. Specifically, we ... Keywords: coherent risk measures, distortion risk measures, robust optimization, uncertainty sets

Dimitris Bertsimas; David B. Brown

2009-11-01T23:59:59.000Z

142

Uncertainty and Inference for Verification Measures  

Science Conference Proceedings (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

143

Stochastic Variational Approach to Minimum Uncertainty States  

E-Print Network (OSTI)

We introduce a new variational characterization of Gaussian diffusion processes as minimum uncertainty states. We then define a variational method constrained by kinematics of diffusions and Schr\\"{o}dinger dynamics to seek states of local minimum uncertainty for general non-harmonic potentials.

F. Illuminati; L. Viola

1995-01-11T23:59:59.000Z

144

Holographic Indeterminacy, Uncertainty and Noise  

E-Print Network (OSTI)

A theory is developed to describe the nonlocal effect of spacetime quantization on position measurements transverse to macroscopic separations. Spacetime quantum states close to a classical null trajectory are approximated by plane wavefunctions of Planck wavelength (l_P) reference beams; these are used to connect transverse position operators at macroscopically separated events. Transverse positions of events with null spacetime separation, but separated by macroscopic spatial distance $L$, are shown to be quantum conjugate observables, leading to holographic indeterminacy and a new uncertainty principle, a lower bound on the standard deviation of relative transverse position \\Delta x_\\perp > \\sqrt{l_PL} or angular orientation \\Delta\\theta > \\sqrt{l_P/L}. The resulting limit on the number of independent degrees of freedom is shown to agree quantitatively with holographic covariant entropy bounds derived from black hole physics and string theory. The theory predicts a universal ``holographic noise'' of spacetime, appearing as shear perturbations with a frequency-independent power spectral density S_H=l_P/c, or in equivalent metric perturbation units, h_{H,rms} \\sqrt{l_P/c} = 2.3 \\times 10^{-22} /\\sqrt{Hz}. If this description of holographic phenomenology is valid, interferometers with current technology could undertake direct quantitative studies of quantum gravity.

Craig J. Hogan

2007-09-05T23:59:59.000Z

145

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

Science Conference Proceedings (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

146

Uncertainty quantification approaches for advanced reactor analyses.  

SciTech Connect

The original approach to nuclear reactor design or safety analyses was to make very conservative modeling assumptions so as to ensure meeting the required safety margins. Traditional regulation, as established by the U. S. Nuclear Regulatory Commission required conservatisms which have subsequently been shown to be excessive. The commission has therefore moved away from excessively conservative evaluations and has determined best-estimate calculations to be an acceptable alternative to conservative models, provided the best-estimate results are accompanied by an uncertainty evaluation which can demonstrate that, when a set of analysis cases which statistically account for uncertainties of all types are generated, there is a 95% probability that at least 95% of the cases meet the safety margins. To date, nearly all published work addressing uncertainty evaluations of nuclear power plant calculations has focused on light water reactors and on large-break loss-of-coolant accident (LBLOCA) analyses. However, there is nothing in the uncertainty evaluation methodologies that is limited to a specific type of reactor or to specific types of plant scenarios. These same methodologies can be equally well applied to analyses for high-temperature gas-cooled reactors and to liquid metal reactors, and they can be applied to steady-state calculations, operational transients, or severe accident scenarios. This report reviews and compares both statistical and deterministic uncertainty evaluation approaches. Recommendations are given for selection of an uncertainty methodology and for considerations to be factored into the process of evaluating uncertainties for advanced reactor best-estimate analyses.

Briggs, L. L.; Nuclear Engineering Division

2009-03-24T23:59:59.000Z

147

On the Fatigue Crack Propagation Behavior of Superalloys at ...  

Science Conference Proceedings (OSTI)

ON THE FATIGUE CRACK PROPAGATION BEHAVIOR. OF SUPERALLOYS AT ... the FCP resistance of superalloys ... lead to poor crack propagation behavior.

148

Statistical Uncertainty Analysis Applied to Criticality Calculation  

Science Conference Proceedings (OSTI)

In this paper, we present an uncertainty methodology based on a statistical approach, for assessing uncertainties in criticality prediction using monte carlo method due to uncertainties in the isotopic composition of the fuel. The methodology has been applied to criticality calculations with MCNP5 with additional stochastic input of the isotopic fuel composition. The stochastic input were generated using the latin hypercube sampling method based one the probability density function of each nuclide composition. The automatic passing of the stochastic input to the MCNP and the repeated criticality calculation is made possible by using a python script to link the MCNP and our latin hypercube sampling code.

Hartini, Entin; Andiwijayakusuma, Dinan; Susmikanti, Mike; Nursinta, A. W. [Centre for Nuclear Informatics Development, National Nuclear Energy Agency of Indonesia (Indonesia)

2010-06-22T23:59:59.000Z

149

Uncertainties in Cancer Risk Coefficients for Environmental Exposure to Radionuclides. An Uncertainty Analysis for Risk Coefficients Reported in Federal Guidance Report No. 13  

Science Conference Proceedings (OSTI)

Federal Guidance Report No. 13 (FGR 13) provides risk coefficients for estimation of the risk of cancer due to low-level exposure to each of more than 800 radionuclides. Uncertainties in risk coefficients were quantified in FGR 13 for 33 cases (exposure to each of 11 radionuclides by each of three exposure pathways) on the basis of sensitivity analyses in which various combinations of plausible biokinetic, dosimetric, and radiation risk models were used to generate alternative risk coefficients. The present report updates the uncertainty analysis in FGR 13 for the cases of inhalation and ingestion of radionuclides and expands the analysis to all radionuclides addressed in that report. The analysis indicates that most risk coefficients for inhalation or ingestion of radionuclides are determined within a factor of 5 or less by current information. That is, application of alternate plausible biokinetic and dosimetric models and radiation risk models (based on the linear, no-threshold hypothesis with an adjustment for the dose and dose rate effectiveness factor) is unlikely to change these coefficients by more than a factor of 5. In this analysis the assessed uncertainty in the radiation risk model was found to be the main determinant of the uncertainty category for most risk coefficients, but conclusions concerning the relative contributions of risk and dose models to the total uncertainty in a risk coefficient may depend strongly on the method of assessing uncertainties in the risk model.

Pawel, David [U.S. Environmental Protection Agency; Leggett, Richard Wayne [ORNL; Eckerman, Keith F [ORNL; Nelson, Christopher [U.S. Environmental Protection Agency

2007-01-01T23:59:59.000Z

150

All wind farm uncertainty is not the same: The economics of common versus independent causes  

DOE Green Energy (OSTI)

There is uncertainty in the performance of wind energy installations due to unknowns in the local wind environment, machine response to the environment, and the durability of materials. Some of the unknowns are inherently independent from machine to machine while other uncertainties are common to the entire fleet equally. The FAROW computer software for fatigue and reliability of wind turbines is used to calculate the probability of component failure due to a combination of all sources of uncertainty. Although the total probability of component failure due to all effects is sometimes interpreted as the percentage of components likely to fail, this perception is often far from correct. Different amounts of common versus independent uncertainty are reflected in economic risk due to either high probabilities that a small percentage of the fleet will experience problems or low probabilities that the entire fleet will have problems. The average, or expected cost is the same as would be calculated by combining all sources of uncertainty, but the risk to the fleet may be quite different in nature. Present values of replacement costs are compared for two examples reflecting different stages in the design and development process. Results emphasize that an engineering effort to test and evaluate the design assumptions is necessary to advance a design from the high uncertainty of the conceptual stages to the lower uncertainty of a well engineered and tested machine.

Veers, P.S.

1994-12-31T23:59:59.000Z

151

Sensitivity and uncertainty in the effective delayed neutron fraction ({beta}{sub eff})  

SciTech Connect

Precise knowledge of effective delayed neutron fraction ({beta}{sub eff}) and of the corresponding uncertainty is important for reactor safety analysis. The interest in developing the methodology for estimating the uncertainty in {beta}{sub eff} was expressed in the scope of the UAM project of the OECD/NEA. A novel approach for the calculation of the nuclear data sensitivity and uncertainty of the effective delayed neutron fraction is proposed, based on the linear perturbation theory. The method allows the detailed analysis of components of {beta}{sub eff} uncertainty. The procedure was implemented in the SUSD3D sensitivity and uncertainty code applied to several fast neutron benchmark experiments from the ICSBEP and IRPhE databases. According to the JENDL-4 covariance matrices and taking into account the uncertainty in the cross sections and in the prompt and delayed fission spectra the total uncertainty in {beta}eff was found to be of the order of {approx}2 to {approx}3.5 % for the studied fast experiments. (authors)

Kodeli, I. I. [Jozef Stefan Inst., Jamova 39, Ljubljana (Slovenia)

2012-07-01T23:59:59.000Z

152

Meteorological Data Needs for Modeling Air Quality Uncertainties  

Science Conference Proceedings (OSTI)

A probabilistic framework for incorporating uncertainty in air quality models is described. The quantitative dependence of the uncertainty in calculated air quality concentrations on the uncertainty in the input meteorological data is illustrated ...

W. S. Lewellen; R. I. Sykes

1989-10-01T23:59:59.000Z

153

SENSITIVITY OF ASTROPHYSICAL REACTION RATES TO NUCLEAR UNCERTAINTIES  

Science Conference Proceedings (OSTI)

Sensitivities of nuclear reaction rates to a variation of nuclear properties are studied. Target nuclei range from proton- to neutron dripline for 10 {<=} Z {<=} 83. Reactions considered are nucleon- and {alpha}-induced reactions mediated by strong interaction. The contribution of reactions occurring on the target ground state to the total stellar rate is also given. General dependencies on various input quantities are discussed. Additionally, sensitivities of laboratory cross-sections of nucleon-, {alpha}-, and {gamma}-induced reactions are shown, allowing us to estimate the impact of cross-section measurements. Finally, recommended procedures to explore and improve reaction rate uncertainties using the present sensitivity data are outlined.

Rauscher, T. [Department of Physics, University of Basel, CH-4056 Basel (Switzerland)

2012-08-01T23:59:59.000Z

154

Nuclear Data Uncertainties in 2004: A Perspective  

Science Conference Proceedings (OSTI)

Interest in nuclear data uncertainties is growing robustly after having languished for several years. Renewed attention to this topic is being motivated by the practical need for assuring that nuclear systems will be safe

Donald L. Smith

2005-01-01T23:59:59.000Z

155

MOS Uncertainty Estimates in an Ensemble Framework  

Science Conference Proceedings (OSTI)

It is being increasingly recognized that the uncertainty in weather forecasts should be quantified and furnished to users along with the single-value forecasts usually provided. Probabilistic forecasts of “events” have been made in special cases; ...

Bob Glahn; Matthew Peroutka; Jerry Wiedenfeld; John Wagner; Greg Zylstra; Bryan Schuknecht; Bryan Jackson

2009-01-01T23:59:59.000Z

156

Climate Science and the Uncertainty Monster  

Science Conference Proceedings (OSTI)

How to understand and reason about uncertainty in climate science is a topic that is receiving increasing attention in both the scientific and philosophical literature. This paper provides a perspective on exploring ways to understand, assess, and reason ...

J. A. Curry; P. J. Webster

2011-12-01T23:59:59.000Z

157

Microsoft Word - Price Uncertainty Supplement.doc  

Annual Energy Outlook 2012 (EIA)

0 1 August 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 August 10, 2010 Release WTI crude oil spot prices averaged 76.32 per barrel in July...

158

Quantifying reliability uncertainty : a proof of concept.  

SciTech Connect

This paper develops Classical and Bayesian methods for quantifying the uncertainty in reliability for a system of mixed series and parallel components for which both go/no-go and variables data are available. Classical methods focus on uncertainty due to sampling error. Bayesian methods can explore both sampling error and other knowledge-based uncertainties. To date, the reliability community has focused on qualitative statements about uncertainty because there was no consensus on how to quantify them. This paper provides a proof of concept that workable, meaningful quantification methods can be constructed. In addition, the application of the methods demonstrated that the results from the two fundamentally different approaches can be quite comparable. In both approaches, results are sensitive to the details of how one handles components for which no failures have been seen in relatively few tests.

Diegert, Kathleen V.; Dvorack, Michael A.; Ringland, James T.; Mundt, Michael Joseph; Huzurbazar, Aparna (Los Alamos National Laboratory, Los Alamos, NM); Lorio, John F.; Fatherley, Quinn (Los Alamos National Laboratory, Los Alamos, NM); Anderson-Cook, Christine (Los Alamos National Laboratory, Los Alamos, NM); Wilson, Alyson G. (Los Alamos National Laboratory, Los Alamos, NM); Zurn, Rena M.

2009-10-01T23:59:59.000Z

159

Classification of Unseen Examples under Uncertainty  

Science Conference Proceedings (OSTI)

Very frequently machine learning from real-life data is affected by uncertainty. There are three main reasons for imperfection in data: incompleteness, imprecision (also called vagueness), and errors. In this paper the main emphasis is on classification ...

Jerzy W. Grzymala-Busse

1997-12-01T23:59:59.000Z

160

Operational Forecaster Uncertainty Needs and Future Roles  

Science Conference Proceedings (OSTI)

Key results of a comprehensive survey of U.S. National Weather Service operational forecast managers concerning the assessment and communication of forecast uncertainty are presented and discussed. The survey results revealed that forecasters are ...

David R. Novak; David R. Bright; Michael J. Brennan

2008-12-01T23:59:59.000Z

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.


161

Parameterizing Mesoscale Wind Uncertainty for Dispersion Modeling  

Science Conference Proceedings (OSTI)

A parameterization of numerical weather prediction uncertainty is presented for use by atmospheric transport and dispersion models. The theoretical development applies Taylor dispersion concepts to diagnose dispersion metrics from numerical wind ...

Leonard J. Peltier; Sue Ellen Haupt; John C. Wyngaard; David R. Stauffer; Aijun Deng; Jared A. Lee; Kerrie J. Long; Andrew J. Annunzio

2010-08-01T23:59:59.000Z

162

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.

163

Multifidelity methods for multidisciplinary design under uncertainty  

E-Print Network (OSTI)

For computational design and analysis tasks, scientists and engineers often have available many different simulation models. The output of each model has an associated uncertainty that is a result of the modeling process. ...

Christensen, Daniel Erik

2012-01-01T23:59:59.000Z

164

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

165

Environmental issues: still clouded in uncertainty  

SciTech Connect

The key environmental obstacle affecting oil shale development is uncertainty. Little is known with much degree of certainty about potential environmental consequences of oil shale mining or processing. Primary uncertainties include: environmental compliance costs and their effects on investment decisions/ reliability and acceptability of anticipated pollution control technologies/ and confusing, time consuming environmental regulatory framework. The availability of water supplies, protection of air and water quality, impacts on boom-towns, and spent shale disposal are other related issues. (2 photos)

Stanwood, R.M.

1981-01-01T23:59:59.000Z

166

Wave propagation through soils in centrifuge testing  

E-Print Network (OSTI)

Wave propagation phenomena in soils can be experimentally simulated using centrifuge scale models. An original excitation device (drop-ball arrangement) is proposed to generate short wave trains. Wave reflections on model boundaries are taken into account and removed by homomorphic filtering. Propagation is investigated through dispersion laws. For drop-ball experiments, spherical wave field analysis assuming linear viscoelasticity leads to a complete analytical description of wave propagation. Damping phenomena are examined and evaluated using this description.

Semblat, J F; 10.1142/S1363246998000071

2009-01-01T23:59:59.000Z

167

Uncertainty Study of INEEL EST Laboratory Battery Testing Systems  

NLE Websites -- All DOE Office Websites (Extended Search)

INEELEXT-01-00505 December 2001 Uncertainty Study of INEEL EST Laboratory Battery Testing Systems Volume 1 Background and Derivation of Uncertainty Relationships John L. Morrison...

168

Distributed Generation Investment by a Microgrid Under Uncertainty  

E-Print Network (OSTI)

operating strategy of the microgrid is not known in advance,Generation Investment by a Microgrid Under Uncertainty AfzalGeneration Investment by a Microgrid Under Uncertainty Afzal

Siddiqui, Afzal; Marnay, Chris

2006-01-01T23:59:59.000Z

169

Distributed Generation Investment by a Microgrid under Uncertainty  

E-Print Network (OSTI)

Effects of carbon tax on microgrid combined heat and powerGeneration Investment by a Microgrid under Uncertainty AfzalGeneration Investment by a Microgrid under Uncertainty Afzal

Siddiqui, Afzal

2008-01-01T23:59:59.000Z

170

Discrete Frontal Propagation in a Nonconvective Environment  

Science Conference Proceedings (OSTI)

Surface discrete frontal propagation in a wintertime, nonconvective environment is documented using conventional surface and upper-air data and simulated using the PSU–NCAR mesoscale model.

Joseph J. Charney; J. Michael Fritsch

1999-09-01T23:59:59.000Z

171

Oxidation Assisted Crack Propagation of Alloy 718  

Science Conference Proceedings (OSTI)

A material which relax quickly would have a better propagation resistance. For a given alloy, a microstructure exhibiting a fast relaxation of the stresses ahead of ...

172

Light propagation and Imaging in Indefinite Metamaterials  

E-Print Network (OSTI)

photolithography by polarized light,” Applied PhysicsZhang, “Imaging visible light using anisotropic metamaterialcross-sectional review of the light propagation of TE mode (

Yao, Jie

2010-01-01T23:59:59.000Z

173

Propagation of premixed flames in confined channels.  

E-Print Network (OSTI)

??The propagation of premixed flames in confined channels is investigated. In the unconfined case, the structure of the flame and the flame speed for the… (more)

Navaneetha, Arjun

2013-01-01T23:59:59.000Z

174

Epistemic Uncertainty in Evalustion of Evapotranspiration and Net Infiltration Using Analogue Meteorological Data  

SciTech Connect

Uncertainty is typically defined as a potential deficiency in the modeling of a physical process, owing to a lack of knowledge. Uncertainty can be categorized as aleatoric (inherent uncertainty caused by the intrinsic randomness of the system) or epistemic (uncertainty caused by using various model simplifications and their parameters). One of the main reasons for model simplifications is a limited amount of meteorological data. This paper is devoted to the epistemic uncertainty quantification involved in two components of the hydrologic balance-evapotranspiration and net infiltration for interglacial (present day), and future monsoon, glacial transition, and glacial climates at Yucca Mountain, using the data from analogue meteorological stations. In particular, the author analyzes semi-empirical models used for evaluating (1) reference-surface potential evapotranspiration, including temperature-based models (Hargreaves-Samani, Thornthwaite, Hamon, Jensen-Haise, and Turc) and radiation-based models (Priestly-Taylor and Penman), and (2) surface-dependent potential evapotranspiration (Penman-Monteith and Shuttleworth-Wallace models). Evapotranspiration predictions are then used as inputs for the evaluation of net infiltration using the semi-empirical models of Budyko, Fu, Milly, Turc-Pike, and Zhang. Results show that net infiltration ranges are expected to generally increase from the present-day climate to monsoon climate, to glacial transition climate, and then to the glacial climate. The propagation of uncertainties through model predictions for different climates is characterized using statistical measures. Predicted evapotranspiration ranges are reasonably corroborated against the data from Class A pan evaporometers (taking into account evaporation-pan adjustment coefficients), and ranges of net infiltration predictions are corroborated against the geochemical and temperature-based estimates of groundwater recharge and percolation rates through the unsaturated zone obtained at Yucca Mountain.

B. Faybishenko

2006-09-01T23:59:59.000Z

175

Estimating uncertainty of inference for validation  

SciTech Connect

We present a validation process based upon the concept that validation is an inference-making activity. This has always been true, but the association has not been as important before as it is now. Previously, theory had been confirmed by more data, and predictions were possible based on data. The process today is to infer from theory to code and from code to prediction, making the role of prediction somewhat automatic, and a machine function. Validation is defined as determining the degree to which a model and code is an accurate representation of experimental test data. Imbedded in validation is the intention to use the computer code to predict. To predict is to accept the conclusion that an observable final state will manifest; therefore, prediction is an inference whose goodness relies on the validity of the code. Quantifying the uncertainty of a prediction amounts to quantifying the uncertainty of validation, and this involves the characterization of uncertainties inherent in theory/models/codes and the corresponding data. An introduction to inference making and its associated uncertainty is provided as a foundation for the validation problem. A mathematical construction for estimating the uncertainty in the validation inference is then presented, including a possibility distribution constructed to represent the inference uncertainty for validation under uncertainty. The estimation of inference uncertainty for validation is illustrated using data and calculations from Inertial Confinement Fusion (ICF). The ICF measurements of neutron yield and ion temperature were obtained for direct-drive inertial fusion capsules at the Omega laser facility. The glass capsules, containing the fusion gas, were systematically selected with the intent of establishing a reproducible baseline of high-yield 10{sup 13}-10{sup 14} neutron output. The deuterium-tritium ratio in these experiments was varied to study its influence upon yield. This paper on validation inference is the first in a series of inference uncertainty estimations. While the methods demonstrated are primarily statistical, these do not preclude the use of nonprobabilistic methods for uncertainty characterization. The methods presented permit accurate determinations for validation and eventual prediction. It is a goal that these methods establish a standard against which best practice may evolve for determining degree of validation.

Booker, Jane M [Los Alamos National Laboratory; Langenbrunner, James R [Los Alamos National Laboratory; Hemez, Francois M [Los Alamos National Laboratory; Ross, Timothy J [UNM

2010-09-30T23:59:59.000Z

176

Report on INL Activities for Uncertainty Reduction Analysis of FY12  

SciTech Connect

The work scope of this project related to the Work Packages of “Uncertainty Reduction Analyses” with the goal of reducing nuclear data uncertainties is to produce a set of improved nuclear data to be used both for a wide range of validated advanced fast reactor design calculations, and for providing guidelines for further improvements of the ENDF/B files (i.e. ENDF/B-VII, and future releases). Recent extensive sensitivity/uncertainty studies, performed within an international OECD-NEA initiative, have quantified for the first time the impact of current nuclear data uncertainties on design parameters of the major FCR&D and GEN-IV systems, and in particular on Na-cooled fast reactors with different fuels (oxide or metal), fuel composition (e.g. different Pu/TRU ratios) and different conversion ratios. These studies have pointed out that present uncertainties on the nuclear data should be significantly reduced, in order to get full benefit from the advanced modeling and simulation initiatives. Nuclear data plays a fundamental role in performance calculations of advanced reactor concepts. Uncertainties in the nuclear data propagate into uncertainties in calculated integral quantities, driving margins and costs in advanced system design, operation and safeguards. This package contributes to the resolution of technical, cost, safety, security and proliferation concerns in a multi-pronged, systematic, science-based R&D approach. The Nuclear Data effort identifies and develops small scale, phenomenon-specific experiments informed by theory and engineering to reduce the number of large, expensive integral experiments. The Nuclear Data activities are leveraged by effective collaborations between experiment and theory, between DOE programs and offices, at national laboratories and universities, both domestic and international. The primary objective is to develop reactor core sensitivity and uncertainty analyses that identify the improvement needs of key nuclear data which would facilitate fast spectrum system optimization and assure safety performance. The inclusion of fast spectrum integral experiment data is key to minimizing the impact of nuclear data uncertainties on reactor core performance calculations, thus providing the best nuclear data needs assessment. This report presents the status of activities performed at INL under the ARC Work Package previously mentioned. As major achievement this year a comprehensive adjustment, including 87 experiments, was carried out. The results of this adjustment provide useful insights and helpful feedback to both nuclear data evaluation and measurer communities. In the following, we will document first the theory that underlines the adjustment methodology, and then we will illustrate the sensitivity coefficient computation and the nuclear data and experiment selection. Subsequently, the adjustment results will be shown, and, finally, conclusions, including future work, will be provided.

G. Palmiotti; M. Salvatores

2012-09-01T23:59:59.000Z

177

Simulation of a Serial Upstream-Propagating Mesoscale Convective System Event over Southeastern South America Using Composite Initial Conditions  

Science Conference Proceedings (OSTI)

Serial upstream-propagating mesoscale convective system (MCS) events over southeastern South America are important contributors to the local hydrologic cycle as they can provide roughly half of the total monthly summer precipitation. However, the ...

Vagner Anabor; David J. Stensrud; Osvaldo L. L. de Moraes

2009-07-01T23:59:59.000Z

178

Coupled Parabolic Equations for Wave Propagation  

E-Print Network (OSTI)

Coupled Parabolic Equations for Wave Propagation Kai Huang, Knut Solna and Hongkai Zhao #3; April 30, 2004 Abstract We develop an algorithm using two coupled parabolic equations for numerical simulation of wave propagation over long distances. The coupled parabolic equations are derived from a two

Zhao, Hongkai

179

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

180

Random matrix theory for underwater sound propagation  

E-Print Network (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.

Katherine C. Hegewisch; Steven Tomsovic

2011-04-20T23:59:59.000Z

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

Report: Technical Uncertainty and Risk Reduction  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

182

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

183

Evaluation of Uncertainties in Cost Estimations  

E-Print Network (OSTI)

This paper examines uncertainty in several cost estimation methods for large infrastructure projects. In particular the impact and consequences of different unexpected events that have occurred during the construction of various tunnels and aqueducts will be treated. Combined with the cost estimation development, several hypotheses concerning uncertainty prediction and correlation will be verified. First, the basis for researching this topic is described and the methods of estimation and uncertainty prediction are presented. Based upon the results of an extensive investigation into the occurrence of unexpected events, several hypotheses concerning unexpected events and correlations are verified. Other related topics that have been researched are also briefly mentioned. Finally the findings are contemplated in a larger context based upon which the conclusions are presented

Meint Boschloo; Meint Boschloo; Pieter Van Gelder; Han Vrijling; Han Vrijling

2001-01-01T23:59:59.000Z

184

Generalized Uncertainty Principle and Dark Matter  

DOE Green Energy (OSTI)

There have been proposals that primordial black hole remnants (BHRs) are the dark matter, but the idea is somewhat vague. Recently we argued that the generalized uncertainty principle (GUP) may prevent black holes from evaporating completely, in a similar way that the standard uncertainty principle prevents the hydrogen atom from collapsing. We further noted that the hybrid inflation model provides a plausible mechanism for production of large numbers of small black holes. Combining these we suggested that the dark matter might be composed of Planck-size BHRs. In this paper we briefly review these arguments, and discuss the reheating temperature as a result of black hole evaporation.

Chen, P

2004-01-13T23:59:59.000Z

185

Uncertainty in in-place filter test results  

SciTech Connect

Some benefits of accounting for uncertainty in in-place filter test results are explored. Information the test results provide relative to system performance acceptance limits is evaluated in terms of test result uncertainty. An expression for test result uncertainty is used to estimate uncertainty in in-place filter tests on an example air cleaning system. Modifications to the system test geometry are evaluated in terms of effects on test result uncertainty.

Scripsick, R.C.; Beckman, R.J.; Mokler, B.V.

1996-12-31T23:59:59.000Z

186

Incorporating uncertainties into risk assessment with an application to the exploratory studies facilities at Yucca Mountain  

Science Conference Proceedings (OSTI)

A methodology that incorporates variability and reducible sources of uncertainty into the probabilistic and consequence components of risk was developed. The method was applied to the north tunnel of the Exploratory Studies Facility at Yucca Mountain in Nevada. In this assessment, variability and reducible sources of uncertainty were characterized and propagated through the risk assessment models using a Monte Carlo based software package. The results were then manipulated into risk curves at the 5% and 95% confidence levels for both the variability and overall uncertainty analyses, thus distinguishing between variability and reducible sources of uncertainty. In the Yucca Mountain application, the designation of the north tunnel as an item important to public safety, as defined by 10 CFR 60, was determined. Specifically, the annual frequency of a rock fall breaching a waste package causing an off-site dose of 500 mrem (5x10{sup -3} Sv) was calculated. The annual frequency, taking variability into account, ranged from 1.9x10{sup -9} per year at the 5% confidence level to 2.5x10{sup -9} per year at the 95% confidence level. The frequency range after including all uncertainty was 9.5x10{sup -10} to 1.8x10{sup -8} per year. The maximum observable frequency, at the 100% confidence level, was 4.9x10{sup -8} per year. This is below the 10{sup -6} per year frequency criteria of 10 CFR 60. Therefore, based on this work, the north tunnel does not fall under the items important to public safety designation for the event studied.

Fathauer, P.M.

1995-08-01T23:59:59.000Z

187

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

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...

188

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

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*...

189

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

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*...

190

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

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...

191

Requirements Uncertainty in a Software Product Line  

Science Conference Proceedings (OSTI)

A complex system's requirements almost always remain uncertain late into its software development. In gas turbine engine control systems at Rolls-Royce, for a traditional project (non-product line) typically 50% of requirements will change between Critical ... Keywords: Requirements, Uncertainty, Software Product Lines

Andy J. Nolan; Silvia Abrahao; Paul C. Clements; Andy Pickard

2011-08-01T23:59:59.000Z

192

Uncertainty analysis of well test data  

E-Print Network (OSTI)

During a well test a transient pressure response is created by a temporary change in production rate. The well response is usually monitored during a relatively short period of time, depending upon the test objectives. Reservoir properties are determined from well test data via an inverse problem approach. Uncertainty is inherent in any nonlinear inverse problem. Unfortunately, well test interpretation suffers particularly from a variety of uncertainties that, when combined, reduce the confidence that can be associated with the estimated reservoir properties. The specific factors that have been analyzed in this work are: 1. Pressure noise (random noise) 2. Pressure drift (systematic variation) 3. Rate history effects Our work is based on the analysis of the effects of random pressure noise, the drift error, and the rate history on the estimation of typical reservoir parameters for two common reservoir models: A vertical well with a constant wellbore storage and skin in a homogeneous reservoir. A vertical well with a finite conductivity vertical fracture including wellbore effects in a homogeneous reservoir. This work represents a sensitivity study of the impact of pressure and rate uncertainty on parameter estimation and the confidence intervals associated with these results. In this work we statistically analyze the calculated reservoir parameters to quantify the impact of pressure and rate uncertainty on them.

Merad, Mohamed Belgacem

2002-01-01T23:59:59.000Z

193

Higher-order differencing for phase-front propagation in geothermal systems  

DOE Green Energy (OSTI)

We are testing higher-order differencing total variation diminishing schemes implemented in the reservoir simulator TOUGH2 to reduce numerical dispersion of phase fronts in geothermal flow problems. The schemes are called total variation diminishing because they employ flux limiters to prevent spurious oscillations that sometimes occur with other higher-order differencing schemes near sharp fronts. Thus it appears that total variation diminishing schemes rely on an implicit assumption that the overall variability of advected quantities stays constant or diminishes with time. We use the Leonard total variation diminishing scheme in two special problems designed to test the applicability of the scheme for cases where this implicit assumption is violated. In the first problem, we investigate the isothermal propagation of a phase front in a composite porous medium where phase saturation increases as the front enters the second medium. In the second problem, we investigate the propagation of a phase front where boiling increases the saturation difference across the front as it propagates. In the composite porous medium problem, we find that spurious phase saturations can arise if the weighting scheme is based on relative permeability; for weighting based on phase saturation, no such oscillation arises. In the boiling front propagation problem, the front position is highly sensitive to weighting scheme, and the Leonard total variation diminishing scheme is more accurate than upstream weighting because it decreases numerical dispersion in the thermal energy equation.

Oldenburg, Curtis; Pruess, Karsten

1998-01-09T23:59:59.000Z

194

High cycle fatigue and fatigue crack propagation behavior of ...  

Science Conference Proceedings (OSTI)

And fatigue crack propagation rates of modified A7075 showed slightly lower. Those superior fatigue strength and resistance of fatigue crack propagation of ...

195

Statistical Timing Analysis using Levelized Covariance Propagation  

Science Conference Proceedings (OSTI)

Variability in process parameters is making accurate timing analysis of nano-scale integrated circuits an extremely challenging task. In this paper, we propose a new algorithm for statistical timing analysis using Levelized Covariance Propagation (LCP). ...

Kunhyuk Kang; Bipul C. Paul; Kaushik Roy

2005-03-01T23:59:59.000Z

196

Propagative hough voting for human activity recognition  

Science Conference Proceedings (OSTI)

Hough-transform based voting has been successfully applied to both object and activity detections. However, most current Hough voting methods will suffer when insufficient training data is provided. To address this problem, we propose propagative Hough ...

Gang Yu; Junsong Yuan; Zicheng Liu

2012-10-01T23:59:59.000Z

197

Sound Propagation in the Nocturnal Boundary Layer  

Science Conference Proceedings (OSTI)

An experimental study of sound propagation near the ground in stable, nighttime conditions was performed in conjunction with the Cooperative Atmosphere–Surface Exchange Study-1999 (CASES-99). Low-frequency sound transmissions were continuously ...

D. Keith Wilson; John M. Noble; Mark A. Coleman

2003-10-01T23:59:59.000Z

198

Linear and Nonlinear Propagation of Supercell Storms  

Science Conference Proceedings (OSTI)

A nonlinear formula for updraft motion in supercell storms is derived from Petterssen's formula for the motion of systems and the vertical equation of motion, and tested on form-preserving disturbances. At each level, continuous propagation of an ...

Robert Davies-Jones

2002-11-01T23:59:59.000Z

199

Propagation of Rossby Waves of Nonzero Frequency  

Science Conference Proceedings (OSTI)

The propagation of Rossby waves of positive and negative frequency, corresponding to eastward and westward phase speeds, respectively, is investigated. The techniques used are theoretical analysis, ray tracing, and initial value problems in ...

Gui-Ying Yang; Brian J. Hoskins

1996-08-01T23:59:59.000Z

200

Change propagation in large technical systems  

E-Print Network (OSTI)

Propagation of engineering changes has gained increasing scrutiny as the complexity and scale of engineered systems has increased. Over the past decade academic interest has risen, yielding some small-scale in-depth studies, ...

Giffin, Monica L. (Monica Lee)

2007-01-01T23:59:59.000Z

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.


201

Shock wave propagation in vibrofluidized granular materials  

E-Print Network (OSTI)

Shock wave formation and propagation in two-dimensional granular materials under vertical vibration are studied by digital high speed photography. The steepen density and temperature wave fronts form near the plate as granular layer collides with vibrating plate and propagate upward through the layer. The temperature front is always in the transition region between the upward and downward granular flows. The effects of driving parameters and particle number on the shock are also explored.

Kai Huang; Guoqing Miao; Peng Zhang; Yi Yun; Rongjue Wei

2005-11-29T23:59:59.000Z

202

Assessing uncertainties in the relationship between inhaled particle  

NLE Websites -- All DOE Office Websites (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.

203

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other...

204

Total aerosol effect: forcing or radiative flux perturbation?  

Science Conference Proceedings (OSTI)

Uncertainties in aerosol forcings, especially those associated with clouds, contribute to a large extent to uncertainties in the total anthropogenic forcing. The interaction of aerosols with clouds and radiation introduces feedbacks which can affect the rate of rain formation. Traditionally these feedbacks were not included in estimates of total aerosol forcing. Here we argue that they should be included because these feedbacks act quickly compared with the time scale of global warming. We show that for different forcing agents (aerosols and greenhouse gases) the radiative forcings as traditionally defined agree rather well with estimates from a method, here referred to as radiative flux perturbations (RFP), that takes these fast feedbacks and interactions into account. Thus we propose replacing the direct and indirect aerosol forcing in the IPCC forcing chart with RFP estimates. This implies that it is better to evaluate the total anthropogenic aerosol effect as a whole.

Lohmann, Ulrike; Storelvmo, Trude; Jones, Andy; Rotstayn, Leon; Menon, Surabi; Quaas, Johannes; Ekman, Annica; Koch, Dorothy; Ruedy, Reto

2009-09-25T23:59:59.000Z

205

Global Warming Mitigation Investments Optimized under Uncertainty  

NLE Websites -- All DOE Office Websites (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

206

Interpolation Uncertainties Across the ARM SGP Area  

NLE Websites -- All DOE Office Websites (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

207

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

208

Uncertainty of the Solar Neutrino Energy Spectrum  

E-Print Network (OSTI)

The solar neutrino spectrum measured by the Super-Kamiokande shows an excess in high energy bins, which may be explained by vacuum oscillation solution or $hep$ neutrino effect. Here we reconsider an uncertainty of the data caused by the tail of the energy resolution function. Events observed at energy higher than 13.5 MeV are induced by the tail of the resolution. At Super-Kamiokande precision level this uncertainty is no more than few percent within a Gaussian tail. But a power-law decay tail at 3 $\\sigma$ results considerable excesses in these bins, which may be another possible explanation of the anomaly in 708d(825d) data.

Q. Y. Liu

1999-06-30T23:59:59.000Z

209

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

210

Inductively Coupled Plasma Mass Spectrometry Uranium Error Propagation  

SciTech Connect

The Hazards Control Department at Lawrence Livermore National Laboratory (LLNL) uses Inductively Coupled Plasma Mass Spectrometer (ICP/MS) technology to analyze uranium in urine. The ICP/MS used by the Hazards Control Department is a Perkin-Elmer Elan 6000 ICP/MS. The Department of Energy Laboratory Accreditation Program requires that the total error be assessed for bioassay measurements. A previous evaluation of the errors associated with the ICP/MS measurement of uranium demonstrated a {+-} 9.6% error in the range of 0.01 to 0.02 {micro}g/l. However, the propagation of total error for concentrations above and below this level have heretofore been undetermined. This document is an evaluation of the errors associated with the current LLNL ICP/MS method for a more expanded range of uranium concentrations.

Hickman, D P; Maclean, S; Shepley, D; Shaw, R K

2001-07-01T23:59:59.000Z

211

Uncertainties in risk assessment at USDOE facilities  

Science Conference Proceedings (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

212

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

SciTech Connect

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

213

Evaluating Uncertainties in the Projection of Future Drought  

Science Conference Proceedings (OSTI)

The uncertainty in the projection of future drought occurrence was explored for four different drought indices using two model ensembles. The first ensemble expresses uncertainty in the parameter space of the third Hadley Centre climate model, ...

Eleanor J. Burke; Simon J. Brown

2008-04-01T23:59:59.000Z

214

Estimates of Uncertainty in Predictions of Global Mean Surface Temperature  

Science Conference Proceedings (OSTI)

A method for estimating uncertainty in future climate change is discussed in detail and applied to predictions of global mean temperature change. The method uses optimal fingerprinting to make estimates of uncertainty in model simulations of ...

J. A. Kettleborough; B. B. B. Booth; P. A. Stott; M. R. Allen

2007-03-01T23:59:59.000Z

215

Treatment of measurement uncertainties at the power burst facility  

SciTech Connect

The treatment of measurement uncertainty at the Power Burst Facility provides a means of improving data integrity as well as meeting standard practice reporting requirements. This is accomplished by performing the uncertainty analysis in two parts, test independent uncertainty analysis and test dependent uncertainty analysis. The test independent uncertainty analysis is performed on instrumentation used repeatedly from one test to the next, and does not have to be repeated for each test except for improved or new types of instruments. A test dependent uncertainty analysis is performed on each test based on the test independent uncertainties modified as required by test specifications, experiment fixture design, and historical performance of instruments on similar tests. The methodology for performing uncertainty analysis based on the National Bureau of Standards method is reviewed with examples applied to nuclear instrumentation.

Meyer, L.C.

1980-01-01T23:59:59.000Z

216

U.S. Total Exports  

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

TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Kenai, AK Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to...

217

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

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...

218

Uncertainty Budgets for SOP 5: 2013-06-19  

Science Conference Proceedings (OSTI)

... DEVELOP an uncertainty budget based on concepts ... for participation using the Office of Weights and Measures Contact Management System. ...

2013-07-01T23:59:59.000Z

219

Uncertainty Budgets for SOP 4: 2013-06-17  

Science Conference Proceedings (OSTI)

... DEVELOP an uncertainty budget based on concepts ... for participation using the Office of Weights and Measures Contact Management System. ...

2013-07-01T23:59:59.000Z

220

Investment and Upgrade in Distributed Generation under Uncertainty  

E-Print Network (OSTI)

AS, Marnay, C. Distributed generation investment by aand Upgrade in Distributed Generation under Uncertaintyand Upgrade in Distributed Generation under Uncertainty ?

Siddiqui, Afzal

2008-01-01T23:59:59.000Z

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.


221

Group decision making under uncertainty Type="Italic ...  

Science Conference Proceedings (OSTI)

JEAN LAINI~., MICHEL LE BRETON AND ALAIN TRANNOY. GROUP DECISION MAKING UNDER UNCERTAINTY. A NOTE ON THE AGGREGA TION.

222

Making Life and Death Decisions in Conditions of Uncertainty ...  

Science Conference Proceedings (OSTI)

Making Life and Death Decisions in Conditions of Uncertainty THE 2008 RUSSIAN-GEORGIAN WAR. Andrei Illarionov ...

2010-10-05T23:59:59.000Z

223

The NIST Reference on Constants, Units, and Uncertainty  

Science Conference Proceedings (OSTI)

The NIST Reference on Constants, Units and Uncertainty, Information at the foundation of modern science and technology from the Physical ...

224

A SAMPLING-FREE APPROACH TO THE PROPAGATION OF ...  

Science Conference Proceedings (OSTI)

A SAMPLING-FREE APPROACH TO THE PROPAGATION OF DISTRIBUTIONS. Mark Campanelli. Many problems involve ...

225

Probabilistic surfaces: point based primitives to show surface uncertainty  

Science Conference Proceedings (OSTI)

Efficient and informative visualization of surfaces with uncertainties is an important topic with many applications in science and engineering. Examples include environmental pollution borderline identification, identification of the limits of an oil ... Keywords: points as display primitives, uncertainty, visualizing surface uncertainty

Gevorg Grigoryan; Penny Rheingans

2002-10-01T23:59:59.000Z

226

Visualization of gridded scalar data with uncertainty in geosciences  

Science Conference Proceedings (OSTI)

Characterization of the earth's subsurface involves the construction of 3D models from sparse data and so leads to simulation results that involve some degree of uncertainty. This uncertainty is often neglected in the subsequent visualization, due to ... Keywords: 3D, Monte carlo simulation, Scalar fields, Uncertainty, Visualisation, Visualization

Björn Zehner; Norihiro Watanabe; Olaf Kolditz

2010-10-01T23:59:59.000Z

227

State of the Science FACT SHEET Weather Forecast Uncertainty  

E-Print Network (OSTI)

State of the Science FACT SHEET Weather Forecast Uncertainty December, 2009 This document represents the state of the science of quantifying and communicating weather forecast uncertainty. Decisions can be improved by better understanding the uncertainties in the weather forecasts. NOAA seeks to help

228

21 briefing pages total  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

229

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

Science Conference Proceedings (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

230

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

231

Summary Max Total Units  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

232

Yang-Mills Propagators and QCD  

E-Print Network (OSTI)

We present a strong coupling expansion that permits to develop analysis of quantum field theory in the infrared limit. Application to a quartic massless scalar field gives a massive spectrum and the propagator in this regime. We extend the approach to a pure Yang-Mills theory obtaining analogous results. The gluon propagator is compared satisfactorily with lattice results and similarly for the spectrum. Comparison with experimental low energy spectrum of QCD supports the view that $\\sigma$ resonance is indeed a glueball. The gluon propagator we obtained is finally used to formulate a low energy Lagrangian for QCD that reduces to a Nambu-Jona-Lasinio model with all the parameters fixed by those of the full theory.

Marco Frasca

2008-07-27T23:59:59.000Z

233

Anisotropic Shock Propagation in Single Crystals  

Science Conference Proceedings (OSTI)

Most single-crystal shock experiments have been performed in high-symmetry directions while the nature of shock propagation in low-symmetry directions remains relatively unstudied. It is well known that small-amplitude, linear acoustic waves propagating in low-symmetry directions can focus and/or form caustics (Wolfe, 1995). In this report we provide evidence for similar focusing behavior in nonlinear (shock) waves propagating in single crystals of silicon and diamond. Using intense lasers, we have driven non-planar (divergent geometry) shock waves through single-crystals of silicon or diamond and into an isotropic backing plate. On recovery of the backing plates we observe a depression showing evidence of anisotropic plastic strain with well-defined crystallographic registration. We observe 4-, 2-, and 3-fold symmetric impressions for [100], [110], and [111] oriented crystals respectively.

Eggert, J; Hicks, D; Celliers, P; Bradley, D; Cox, J; Unites, W; Collins, G; McWilliams, R; Jeanloz, R; Bruygoo, S; Loubeyre, P

2005-05-26T23:59:59.000Z

234

A Bayesian approach to simultaneously quantify assignments and linguistic uncertainty  

SciTech Connect

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

235

Risk communication: Uncertainties and the numbers game  

Science Conference Proceedings (OSTI)

The science of risk assessment seeks to characterize the potential risk in situations that may pose hazards to human health or the environment. However, the conclusions reached by the scientists and engineers are not an end in themselves - they are passed on to the involved companies, government agencies, legislators, and the public. All interested parties must then decide what to do with the information. Risk communication is a type of technical communication that involves some unique challenges. This paper first defines the relationships between risk assessment, risk management, and risk communication and then explores two issues in risk communication: addressing uncertainty and putting risk number into perspective.

Ortigara, M. [ed.

1995-08-30T23:59:59.000Z

236

Air pollution uncertainty exists in radon measurements  

SciTech Connect

This report discusses radon which is a colorless, odorless gas formed by the decay of radium and uranium that has been shown to cause lung cancer. Progress has been made in ensuring the accuracy of home radon measurements. According to this report, however, radon measurements are uncertain because the ability of the devices that measure radon and the companies analyzing the devices' readings varies and homeowners may not be following EPA's recommended testing procedures. Several possible causes for the uncertainty in radon measurements are cited.

1989-01-01T23:59:59.000Z

237

Uncertainty Budget Analysis for Dimensional Inspection Processes (U)  

SciTech Connect

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

238

Thermal hydraulic limits analysis for the MIT Research Reactor low enrichment uranium core conversion using statistical propagation of parametric uncertainties  

E-Print Network (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 from 15 to 18 plates per element, a reactor ...

Chiang, Keng-Yen

2012-01-01T23:59:59.000Z

239

U.S. Total Exports  

Annual Energy Outlook 2012 (EIA)

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...

240

Constraining uncertainties about the sources and magnitude of polycyclic  

NLE Websites -- All DOE Office Websites (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

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

Dealing with Uncertainties During Heat Exchanger Design  

E-Print Network (OSTI)

Over the last thirty years much progress has been made in heat exchanger design methodology. Even so, the design engineer still has to deal with a great deal of uncertainty. Whilst the methods used to predict heat transfer coefficients are now quite sophisticated and take account of many physical factors, the results they yield are still inaccurate. Physical property information is required for the estimation of heat transfer coefficients. Available information is often of dubious accuracy. Even given accurate properties modern methods for the predictions of tube-side heat transfer coefficient can be expected to have an accuracy of only ± 10%. For the shell-side, higher errors (say, around ±15%) can be expected. Perhaps worst of all, comes the specification of fouling resistance (the allowance made for the thermal resistance presented by dirt layers deposited on the heat exchanger tubes). In most instances there is little science or understanding behind the specification of these resistances. Traditionally there have been two approaches to dealing with these uncertainties: over-specification of fouling resistance; and, addition of 'design margin' (i.e. addition of extra surface area). There are cases in which both approaches are adopted. The engineer specifying the required duty provides a higher than necessary fouling resistance whilst the exchanger designer adds design margin! Both approaches result in 'over-design'.

Polley, G. T.; Pugh, S. J.

2001-05-01T23:59:59.000Z

242

Westward propagation of the Indian monsoon  

E-Print Network (OSTI)

Being restricted in their vertical development by the Tibetan high, monsoon depressions propagate westward against monsoon westerlies embedded in the Indian monsoon trough. The cause of this peculiar propagation has not been well explained. Special characteristics of individual depressions were revealed from observations of previous studies; particularly, the major rainfall of a depression occurs over its west–south-west sector. The latent heat released by this rainfall forms east–west differential heating across the depression in developing an east–west asymmetric circulation. Because this east–west circulation is a part of the depression’s divergent circulation, a spatial quadrature relationship exists between this divergent circulation and the depression. Based on these characteristics, a westward propagation mechanism of the depression is introduced. The depression’s rainfall is supported by the convergence of water vapor transported by the low-level divergent circulation. In turn, the divergent circulation is maintained through a feedback of the latent heat released by the rainfall. The upward branch of the east–west circulation coupled with the convergent center of the low-level divergent circulation generates a negative streamfunction tendency. The depression is propagated westward by a dynamic interaction between rainfall/convection and this monsoon disturbance through the negative streamfunction tendency. The spatial quadrature relationship between a depression and its east–west (divergent) circulation rejuvenates the water vapor supply maintaining diabatic heating and the divergent circulation, and perpetuating

unknown authors

2004-01-01T23:59:59.000Z

243

Propagation algorithms for lexicographic ordering constraints  

Science Conference Proceedings (OSTI)

Finite-domain constraint programming has been used with great success to tackle a wide variety of combinatorial problems in industry and academia. To apply finite-domain constraint programming to a problem, it is modelled by a set of constraints on a ... Keywords: artificial intelligence, constraint programming, constraint propagation, constraints, generalized arc consistency, lexicographic ordering, matrix models, symmetry, symmetry breaking

Alan M. Frisch; Brahim Hnich; Zeynep Kiziltan; Ian Miguel; Toby Walsh

2006-07-01T23:59:59.000Z

244

Detonation propagation in a high loss configuration  

SciTech Connect

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

245

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

246

Survey and Evaluate Uncertainty Quantification Methodologies  

SciTech Connect

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

247

Propagation of Chaos for a Thermostated Kinetic Model  

E-Print Network (OSTI)

We consider a system of N point particles moving on a d-dimensional torus. Each particle is subject to a uniform field E and random speed conserving collisions. This model is a variant of the Drude-Lorentz model of electrical conduction. In order to avoid heating by the external field, the particles also interact with a Gaussian thermostat which keeps the total kinetic energy of the system constant. The thermostat induces a mean-field type of interaction between the particles. Here we prove that, starting from a product measure, in the large N limit, the one particle velocity distribution satisfies a self consistent Vlasov-Boltzmann equation.. This is a consequence of "propagation of chaos", which we also prove for this model.

F. Bonetto; E. A. Carlen; R. Esposito; J. L. Lebowitz; R. Marra

2013-05-31T23:59:59.000Z

248

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

249

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

250

Reducing long-term reservoir performance uncertainty  

DOE Green Energy (OSTI)

Reservoir performance is one of the key issues that have to be addressed before going ahead with the development of a geothermal field. In order to select the type and size of the power plant and design other surface installations, it is necessary to know the characteristics of the production wells and of the produced fluids, and to predict the changes over a 10--30 year period. This is not a straightforward task, as in most cases the calculations have to be made on the basis of data collected before significant fluid volumes have been extracted from the reservoir. The paper describes the methodology used in predicting the long-term performance of hydrothermal systems, as well as DOE/GTD-sponsored research aimed at reducing the uncertainties associated with these predictions. 27 refs., 1 fig.

Lippmann, M.J.

1988-04-01T23:59:59.000Z

251

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,

252

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

253

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

254

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).

255

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)

256

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

257

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

258

Uncertainty quantification in kinematic wave models  

SciTech Connect

We developed a probabilistic approach to quantify parametric uncertainty in first-order hyperbolic conservation laws (kinematic wave equations). The approach relies on the derivation of a deterministic equation for the cumulative density function (CDF) of the system state, in which probabilistic descriptions (probability density functions or PDFs) of the system parameters and/or initial and boundary conditions serve as inputs. In contrast to PDF equations, which are often used in other contexts, CDF equations allow for straightforward and unambiguous determination of boundary conditions with respect to sample variables.The accuracy and robustness of solutions of the CDF equation for one such system, the Saint-Venant equations of river flows, were investigated via comparison with Monte Carlo simulations.

Wang, Peng; Tartakovsky, Daniel M.

2012-10-01T23:59:59.000Z

259

Radiotherapy Dose Fractionation under Parameter Uncertainty  

SciTech Connect

In radiotherapy, radiation is directed to damage a tumor while avoiding surrounding healthy tissue. Tradeoffs ensue because dose cannot be exactly shaped to the tumor. It is particularly important to ensure that sensitive biological structures near the tumor are not damaged more than a certain amount. Biological tissue is known to have a nonlinear response to incident radiation. The linear quadratic dose response model, which requires the specification of two clinically and experimentally observed response coefficients, is commonly used to model this effect. This model yields an optimization problem giving two different types of optimal dose sequences (fractionation schedules). Which fractionation schedule is preferred depends on the response coefficients. These coefficients are uncertainly known and may differ from patient to patient. Because of this not only the expected outcomes but also the uncertainty around these outcomes are important, and it might not be prudent to select the strategy with the best expected outcome.

Davison, Matt [Department of Applied Mathematics, University of Western Ontario, London, Ontario (Canada); Department of Statistical and Actuarial Science, University of Western Ontario, London, Ontario (Canada); Ivey School of Business, University of Western Ontario, London, Ontario (Canada); Kim, Daero [Department of Applied Mathematics, University of Western Ontario, London, Ontario (Canada); Keller, Harald [Department Radiation Oncology, University of Toronto, Toronto, Ontario (Canada); Radiation Medicine Program, Princess Margaret Hospital, Toronto, Ontario (Canada)

2011-11-30T23:59:59.000Z

260

Incorporating uncertainty in RADTRAN 6.0 input files.  

SciTech Connect

Uncertainty may be introduced into RADTRAN analyses by distributing input parameters. The MELCOR Uncertainty Engine (Gauntt and Erickson, 2004) has been adapted for use in RADTRAN to determine the parameter shape and minimum and maximum of the distribution, to sample on the distribution, and to create an appropriate RADTRAN batch file. Coupling input parameters is not possible in this initial application. It is recommended that the analyst be very familiar with RADTRAN and able to edit or create a RADTRAN input file using a text editor before implementing the RADTRAN Uncertainty Analysis Module. Installation of the MELCOR Uncertainty Engine is required for incorporation of uncertainty into RADTRAN. Gauntt and Erickson (2004) provides installation instructions as well as a description and user guide for the uncertainty engine.

Dennis, Matthew L.; Weiner, Ruth F.; Heames, Terence John (Alion Science and Technology)

2010-02-01T23:59:59.000Z

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.


261

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 ........................................

262

We underestimate uncertainties in our predictions.  

Science Conference Proceedings (OSTI)

Prediction is defined in the American Heritage Dictionary as follows: 'To state, tell about, or make known in advance, especially on the basis of special knowledge.' What special knowledge do we demand of modeling and simulation to assert that we have a predictive capability for high consequence applications? The 'special knowledge' question can be answered in two dimensions: the process and rigor by which modeling and simulation is executed and assessment results for the specific application. Here we focus on the process and rigor dimension and address predictive capability in terms of six attributes: (1) geometric and representational fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) validation, and (6) uncertainty quantification. This presentation will demonstrate through mini-tutorials, simple examples, and numerous case studies how each attribute creates opportunities for errors, biases, or uncertainties to enter into simulation results. The demonstrations will motivate a set of practices that minimize the risk in using modeling and simulation for high-consequence applications while defining important research directions. It is recognized that there are cultural, technical, infrastructure, and resource barriers that prevent analysts from performing all analyses at the highest levels of rigor. Consequently, the audience for this talk is (1) analysts, so they can know what is expected of them, (2) decision makers, so they can know what to expect from modeling and simulation, and (3) the R&D community, so they can address the technical and infrastructure issues that prevent analysts from executing analyses in a practical, timely, and quality manner.

Pilch, Martin M.

2010-04-01T23:59:59.000Z

263

Discrete Propagation in Numerically Simulated Nocturnal Squall Lines  

Science Conference Proceedings (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

264

The Propagation Mechanism of a Vortex on the ? Plane  

Science Conference Proceedings (OSTI)

The propagation velocity and propagation mechanism for vortices on a ? plane are determined for a reduced-gravity model by integrating the momentum equations over the ? plane. Isolated vortices, vortices in a background current, and initial ...

Peter Jan van Leeuwen

2007-09-01T23:59:59.000Z

265

Effects of uncertainties and errors on Lyapunov control  

E-Print Network (OSTI)

Lyapunov control (open-loop) is often confronted with uncertainties and errors in practical applications. In this paper, we analyze the robustness of Lyapunov control against the uncertainties and errors in quantum control systems. The analysis is carried out through examinations of uncertainties and errors, calculations of the control fidelity under influences of the certainties and errors, as well as discussions on the caused effects. Two examples, a closed control system and an open control system, are presented to illustrate the general formulism.

Yi, X X; Wu, Chunfeng; Oh, C H

2010-01-01T23:59:59.000Z

266

Total Biofuels Consumption (2005 - 2009) Total annual biofuels...  

Open Energy Info (EERE)

Total Biofuels Consumption (2005 - 2009) Total annual biofuels consumption (Thousand Barrels Per Day) for 2005 - 2009 for over 230 countries and regions.      ...

267

Perturbative eigenvalue techniques for global?scale hydroacoustic pulse propagation  

Science Conference Proceedings (OSTI)

Because of the computational difficulties associated with three?dimensional acoustic propagation on global scales in the ocean

Gregory J. Orris; John S. Perkins; Laurie T. Fialkowski

1999-01-01T23:59:59.000Z

268

CHAPTER 10 10.3.1. Radio Propagation Factors ....................... ...  

Science Conference Proceedings (OSTI)

... entails propagation of electromagnetic radiation through some ... degrees by extraneous radiations in the ... path inter- ference, nuclear blast effects ...

2002-08-23T23:59:59.000Z

269

Uncertainty Principle Inequalities Related to Laguerre-Bessel Transform  

E-Print Network (OSTI)

In this paper, an analogous of Heisenberg inequality is established for Laguerre-Bessel transform. Also, a local uncertainty principle for this transform is investigate

Hamem, Soumeya

2011-01-01T23:59:59.000Z

270

Gas Exploration Software for Reducing Uncertainty in Gas ...  

... * Improve estimation of reservoir parameters and quantify uncertainty in the estimation when exploring for gas and oil deposits using geophysical data More ...

271

Approaches to uncertainty evaluation based on proficiency testing ...  

Science Conference Proceedings (OSTI)

example (glucose in human serum) where the uncertainty .... to the normalised error, EN, (Eq. 2). ... a human plasma sample, expressed in mmol/L. The ana-.

272

Characterizing Uncertainty for Regional Climate Change Mitigation and Adaptation Decisions  

SciTech Connect

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

273

Investment and Upgrade in Distributed Generation under Uncertainty  

E-Print Network (OSTI)

generation investment by a microgrid under uncertainty.M. E?ects of carbon tax on microgrid combined heat and powersite generation. Nevertheless, a microgrid contemplating the

Siddiqui, Afzal

2008-01-01T23:59:59.000Z

274

Reducing Uncertainties in Life Limits of Titanium Alloys in Turbine ...  

Science Conference Proceedings (OSTI)

Presentation Title, Reducing Uncertainties in Life Limits of Titanium Alloys in Turbine Engine Rotors. Author(s), James M. Larsen, Sushant Jha, Christopher J.

275

Model simplification of chemical kinetic systems under uncertainty  

E-Print Network (OSTI)

This thesis investigates the impact of uncertainty on the reduction and simplification of chemical kinetics mechanisms. Chemical kinetics simulations of complex fuels are very computationally expensive, especially when ...

Coles, Thomas Michael Kyte

2011-01-01T23:59:59.000Z

276

The effects of incorporating dynamic data on estimates of uncertainty  

E-Print Network (OSTI)

Petroleum exploration and development are capital intensive and smart economic decisions that need to be made to profitably extract oil and gas from the reservoirs. Accurate quantification of uncertainty in production forecasts will help in assessing risk and making good economic decisions. This study investigates the effect of combining dynamic data with the uncertainty in static data to see the effect on estimates of uncertainty in production forecasting. Fifty permeability realizations were generated for a reservoir in west Texas from available petrophysical data. We quantified the uncertainty in the production forecasts using a likelihood weighting method and an automatic history matching technique combined with linear uncertainty analysis. The results were compared with the uncertainty predicted using only static data. We also investigated approaches for best selecting a smaller number of models from a larger set of realizations to be history matched for quantification of uncertainty. We found that incorporating dynamic data in a reservoir model will result in lower estimates of uncertainty than considering only static data. However, incorporation of dynamic data does not guarantee that the forecasted ranges will encompass the true value. Reliability of the forecasted ranges depends on the method employed. When sampling multiple realizations of static data for history matching to quantify uncertainty, a sampling over the entire range of realization likelihoods shows larger confidence intervals and is more likely to encompass the true value for predicted fluid recoveries, as compared to selecting the best models.

Mulla, Shahebaz Hisamuddin

2003-12-01T23:59:59.000Z

277

Relating confidence to measured information uncertainty in qualitative reasoning  

SciTech Connect

Qualitative reasoning makes use of qualitative assessments provided by subject matter experts to model factors such as security risk. Confidence in a result is important and useful when comparing competing results. Quantifying the confidence in an evidential reasoning result must be consistent and based on the available information. A novel method is proposed to relate confidence to the available information uncertainty in the result using fuzzy sets. Information uncertainty can be quantified through measures of non-specificity and conflict. Fuzzy values for confidence are established from information uncertainty values that lie between the measured minimum and maximum information uncertainty values.

Chavez, Gregory M [Los Alamos National Laboratory; Zerkle, David K [Los Alamos National Laboratory; Key, Brian P [Los Alamos National Laboratory; Shevitz, Daniel W [Los Alamos National Laboratory

2010-10-07T23:59:59.000Z

278

Decision making under epistemic uncertainty : an application to seismic design  

E-Print Network (OSTI)

The problem of accounting for epistemic uncertainty in risk management decisions is conceptually straightforward, but is riddled with practical difficulties. Simple approximations are often used whereby future variations ...

Agarwal, Anna

2008-01-01T23:59:59.000Z

279

Measurement uncertainty analysis techniques applied to PV performance measurements  

DOE Green Energy (OSTI)

The purpose of this presentation is to provide a brief introduction to measurement uncertainty analysis, outline how it is done, and illustrate uncertainty analysis with examples drawn from the PV field, with particular emphasis toward its use in PV performance measurements. The uncertainty information we know and state concerning a PV performance measurement or a module test result determines, to a significant extent, the value and quality of that result. What is measurement uncertainty analysis It is an outgrowth of what has commonly been called error analysis. But uncertainty analysis, a more recent development, gives greater insight into measurement processes and tests, experiments, or calibration results. Uncertainty analysis gives us an estimate of the I interval about a measured value or an experiment's final result within which we believe the true value of that quantity will lie. Why should we take the time to perform an uncertainty analysis A rigorous measurement uncertainty analysis: Increases the credibility and value of research results; allows comparisons of results from different labs; helps improve experiment design and identifies where changes are needed to achieve stated objectives (through use of the pre-test analysis); plays a significant role in validating measurements and experimental results, and in demonstrating (through the post-test analysis) that valid data have been acquired; reduces the risk of making erroneous decisions; demonstrates quality assurance and quality control measures have been accomplished; define Valid Data as data having known and documented paths of: Origin, including theory; measurements; traceability to measurement standards; computations; uncertainty analysis of results.

Wells, C.

1992-10-01T23:59:59.000Z

280

Uncertainty relation for non-Hamiltonian quantum systems  

SciTech Connect

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

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

Robust Dynamic Traffic Assignment under Demand and Capacity Uncertainty  

E-Print Network (OSTI)

Assignment under Demand and Capacity Uncertainty ? Giuseppeworst-case sce- nario of demand and capacity con?gurations.uncertain demands and capacities are modeled as unknown-but-

Calafiore, Giuseppe; El Ghaoui, Laurent

2008-01-01T23:59:59.000Z

282

Cosmic ray propagation in galactic turbulence  

E-Print Network (OSTI)

We revisit propagation of galactic cosmic rays in light of recent advances in cosmic ray diffusion theory in realistic interstellar turbulence. We use tested model of turbulence in which it has been shown that fast modes dominate scattering of cosmic rays. As a result, propagation becomes inhomogeneous and environment dependent. By adopting the formalism of the nonlinear theory (NLT) developed by Yan & Lazarian (2008), we calculate diffusion of cosmic rays self-consistently from first principles. We assume a two-phase model for the Galaxy to account for different damping mechanisms of the fast modes, and we find that the energy dependence of the diffusion coefficient is mainly affected by medium properties. We show that it gives a correct framework to interpret some of the recent CR puzzles.

Evoli, Carmelo

2013-01-01T23:59:59.000Z

283

Surge propagation in gas insulated substation  

SciTech Connect

Surge propagation performance in a 550 kV gas insulated substation is studied experimentally and by computer simulation using the Electro-Magnetic Transients Program. Extra capacitance added to the system by the components of GIS such as potential devices, branch buses, circuit breakers deform the wave shape of the travelling surges. A simple modeling technique to represent GIS in surge analysis is proposed and its applicability is proved. Paper No. 80 SM 658-5.

Matsumura, S.; Nitta, T.

1981-06-01T23:59:59.000Z

284

EFFECT OF CREVICE FORMER ON CORROSION DAMAGE PROPAGATION  

SciTech Connect

The objectives of this report are: (1) To determine the effect of the crevice former on the localized corrosion damage propagation; (2) FOCUS on post initiation stage, crevice propagation and arrest processes; (3) Determine the evolution of damage--severity, shape, location/distribution, damage profile; and (4) Model of crevice corrosion propagation, i.e. the evolution of the crevice corrosion damage profile.

J.H. Payer; U. Landau; X. Shan; A.S. Agarwal

2006-03-01T23:59:59.000Z

285

Estimation of radial acoustic wave propagation in relative motion  

Science Conference Proceedings (OSTI)

Sound emission and propagation through the moving air in front of aircraft compressors and behind the turbine assemblies is investigated at UPB in a current research program. Results of the sound waves radial propagation in the first stage of the low ... Keywords: acoustics, finite volumes method, relative fluid mechanics, sound pressure level, sound propagation, sound waves, wave modeling

Alina Bogoi; Radu D. Rugescu

2008-11-01T23:59:59.000Z

286

Quantum Graphical Models and Belief Propagation  

E-Print Network (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 Hammersely-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.

Matthew Leifer; David Poulin

2007-08-09T23:59:59.000Z

287

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

288

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

Science Conference Proceedings (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

289

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

Science Conference Proceedings (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

290

Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for deposited material and external doses. Volume 2: Appendices  

SciTech Connect

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 deposited material and external dose 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 deposited material and external doses, (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); Boardman, J. [AEA Technology (United Kingdom); Jones, J.A. [National Radiological Protection Board (United Kingdom); Harper, F.T.; Young, M.L. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

1997-12-01T23:59:59.000Z

291

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

Science Conference Proceedings (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

292

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 ....................

293

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 ....................

294

Planning electricity transmission to accommodate renewables: Using two-stage programming to evaluate flexibility and the cost of disregarding uncertainty  

E-Print Network (OSTI)

 uncertainty, ECIU), and the value of being able to  postpone  decisions  until  some  uncertainty  is  resolved  (the  expected  cost  of  ignoring  optionality,  ECIO).  These  indices  quantify,  in  different  ways,  the  benefits  of  considering    Thirdly, concern about climate...  the total generation capacity at each bus or  in each zone. This capacity  is often  taken  to  be  a  function  of  uncertain  electricity  demand,  or  simply  presumed  to  have  an  exogenous probability distribution. Other risks that have been considered by some of these  models  are...

van der Weijde, Adriaan Hendrik; Hobbs, Benjamin F.

2011-01-31T23:59:59.000Z

295

Impact of parton distribution function and {alpha}{sub s} uncertainties on Higgs boson production in gluon fusion at hadron colliders  

SciTech Connect

We present a systematic study of uncertainties due to parton distributions (PDFs) and the strong coupling on the gluon-fusion production cross section of the standard model Higgs at the Tevatron and LHC colliders. We compare procedures and results when three recent sets of PDFs are used, CTEQ6.6, MSTW08, and NNPDF1.2, and we discuss specifically the way PDF and strong coupling uncertainties are combined. We find that results obtained from different PDF sets are in reasonable agreement if a common value of the strong coupling is adopted. We show that the addition in quadrature of PDF and {alpha}{sub s} uncertainties provides an adequate approximation to the full result with exact error propagation. We discuss a simple recipe to determine a conservative PDF+{alpha}{sub s} uncertainty from available global parton sets, and we use it to estimate this uncertainty on the given process to be about 10% at the Tevatron and 5% at the LHC for a light Higgs.

Demartin, Federico; Mariani, Elisa [Dipartimento di Fisica, Universita di Milano, Via Celoria 16, I-20133 Milano (Italy); Forte, Stefano; Vicini, Alessandro [Dipartimento di Fisica, Universita di Milano, Via Celoria 16, I-20133 Milano (Italy); INFN, Sezione di Milano, Via Celoria 16, I-20133 Milano (Italy); Rojo, Juan [INFN, Sezione di Milano, Via Celoria 16, I-20133 Milano (Italy)

2010-07-01T23:59:59.000Z

296

Random matrix theory for modeling uncertainties in computational mechanics  

E-Print Network (OSTI)

Random matrix theory for modeling uncertainties in computational mechanics C. Soize Laboratory of Engineering Mechanics, University of Marne-la-Vall´ee, 5 boulevard Descartes, 77454 Marne-la-Vallée, France, e in computational mechanics. If data uncertainties can be modeled by parametric probabilistic methods, for a given

Paris-Sud XI, Université de

297

Poster: Data intensive uncertainty quantification: applications to climate modeling  

Science Conference Proceedings (OSTI)

In October of 2009, LLNL began a three-year Strategic Initiative, "The Advance of Uncertainty Quantification Science with Application to Climate Modeling, Inertial Confinement Fusion Design, and Stockpile Stewardship Science." The goal of the project ... Keywords: climate model, uncertainty quantification

John Tannahill; Donald D. Lucas; David Domyancic; Scott Brandon; Richard Klein

2011-11-01T23:59:59.000Z

298

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

299

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.

Djurcic, Z; Piepke, A; Foster, V R; Miller, L; Gratta, G

2008-01-01T23:59:59.000Z

300

A New Measure of Earnings Forecast Uncertainty Xuguang Sheng  

E-Print Network (OSTI)

A New Measure of Earnings Forecast Uncertainty Xuguang Sheng American University Washington, D of earnings forecast uncertainty as the sum of dispersion among analysts and the variance of mean forecast available to analysts at the time they make their forecasts. Hence, it alleviates some of the limitations

Kim, Kiho

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

Engineering computation under uncertainty - Capabilities of non-traditional models  

Science Conference Proceedings (OSTI)

This paper provides a review of various non-traditional uncertainty models for engineering computation and responds to the criticism of those models. This criticism imputes inappropriateness in representing uncertain quantities and an absence of numerically ... Keywords: Computational efficiency, Fuzzy models, Fuzzy randomness, Imprecise probabilities, Interval analysis, Uncertainty modeling

Bernd Möller; Michael Beer

2008-05-01T23:59:59.000Z

302

Efficient Algorithms for Heavy-Tail Analysis under Interval Uncertainty  

E-Print Network (OSTI)

Efficient Algorithms for Heavy-Tail Analysis under Interval Uncertainty Vladik Kreinovich1 heavy-tailed distri- butions, i.e., distributions in which (x) decreases as (x) x- . To properly take for computing these ranges. Keywords: heavy-tailed distributions, interval uncertainty, efficient algorithms

Kreinovich, Vladik

303

Distributed Generation Investment by a Microgrid Under Uncertainty  

E-Print Network (OSTI)

LBNL-60592 Distributed Generation Investment by a Microgrid Under Uncertainty Afzal Siddiqui'06 1 Distributed Generation Investment by a Microgrid Under Uncertainty Afzal Siddiqui University a California-based microgrid's decision to invest in a distributed generation (DG) unit that operates

304

Short title: STOCHASTIC VARIATIONAL APPROACH TO MINIMUM UNCERTAINTY  

E-Print Network (OSTI)

We introduce a new variational characterization of Gaussian diffusion processes as minimum uncertainty states. We then define a variational method constrained by kinematics of diffusions and Schrödinger dynamics to seek states of local minimum uncertainty for general non-harmonic potentials. PACS numbers:03.65.-w, 03.65.Ca, 03.65.Bz 1.

Fabrizio Illuminati; Lorenza Viola

1995-01-01T23:59:59.000Z

305

Uncertainty measures for general Type-2 fuzzy sets  

Science Conference Proceedings (OSTI)

Five uncertainty measures have previously been defined for interval Type-2 fuzzy sets (IT2 FSs), namely centroid, cardinality, fuzziness, variance and skewness. Based on a recently developed @a-plane representation for a general T2 FS, this paper generalizes ... Keywords: ?-Plane representation, Cardinality, Centroid, Fuzziness, Skewness, Type-2 fuzzy sets, Uncertainty measures, Variance

Daoyuan Zhai; Jerry M. Mendel

2011-02-01T23:59:59.000Z

306

Uncertainty quantification of limit-cycle oscillations  

SciTech Connect

Different computational methodologies have been developed to quantify the uncertain response of a relatively simple aeroelastic system in limit-cycle oscillation, subject to parametric variability. The aeroelastic system is that of a rigid airfoil, supported by pitch and plunge structural coupling, with nonlinearities in the component in pitch. The nonlinearities are adjusted to permit the formation of a either a subcritical or supercritical branch of limit-cycle oscillations. Uncertainties are specified in the cubic coefficient of the torsional spring and in the initial pitch angle of the airfoil. Stochastic projections of the time-domain and cyclic equations governing system response are carried out, leading to both intrusive and non-intrusive computational formulations. Non-intrusive formulations are examined using stochastic projections derived from Wiener expansions involving Haar wavelet and B-spline bases, while Wiener-Hermite expansions of the cyclic equations are employed intrusively and non-intrusively. Application of the B-spline stochastic projection is extended to the treatment of aerodynamic nonlinearities, as modeled through the discrete Euler equations. The methodologies are compared in terms of computational cost, convergence properties, ease of implementation, and potential for application to complex aeroelastic systems.

Beran, Philip S. [Multidisciplinary Technologies Center, Air Vehicles Directorate, AFRL/VASD, Building 146, 2210 Eighth Street, WPAFB, OH 45433 (United States)]. E-mail: philip.beran@wpafb.af.mil; Pettit, Chris L. [United States Naval Academy, 590 Holloway Rd., MS 11-B, Annapolis, MD 21402 (United States)]. E-mail: pettitcl@usna.edu; Millman, Daniel R. [USAF TPS/EDT, 220 South Wolfe Ave, Bldg. 1220, Rm. 131, Edwards AFB, CA 93524-6485 (United States)]. E-mail: daniel.millman@edwards.af.mil

2006-09-01T23:59:59.000Z

307

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

308

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 $\\rho_{de}=\\frac{6}{\\pi}L_{P}^{-2}L_{H}^{-2}$, where $L_{P}$ and $L_{H}$ are the Planck and Hubble scale cut-off. The expectation value of zero-point energy automatically vanishes under the quantum dynamical time variable. The fraction of the dark energy is precisely given by $\\Omega_{de}=\\frac{2}{\\pi}$, which does not evolve with the quantum dynamical time variable, so it is "always" comparable to the matter energy density or the critical density. This theory is consistent with current cosmic observations.

M. J. Luo

2014-01-11T23:59:59.000Z

309

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

SciTech Connect

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

310

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

311

Design Feasibility Analysis and Optimization under Uncertainty - A Bayesian  

NLE Websites -- All DOE Office Websites (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.

312

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

Science Conference Proceedings (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

313

Uncertainties in Predicted Ozone Concentrations Due to Input Uncertainties for the UAM-V Photochemical Grid Model  

Science Conference Proceedings (OSTI)

Based on studies of ozone episodes in the eastern United States using the photochemical grid model, UAM-V, regulatory agencies have made decisions concerning emissions controls. This project analyzes effects of uncertainties in UAM-V input variables (emissions, initial and boundary conditions, meteorological variables, and chemical reactions) on uncertainties in UAM-V ozone predictions for the July 1995 episode.

2000-11-06T23:59:59.000Z

314

Acoustic Propagation Prediction in Shallow Water  

E-Print Network (OSTI)

An acoustic propagation experiment was conducted on 17 May 2000 in a shallow water site off the Perth metropolitan coast with the view of obtaining reflection and refraction data to contribute to developing a geoacoustic model of the area. The site proposed has constant bathymetry, though the geological properties of the site are not well known. The experiment used two hydrophones, one situated mid-water and the other moored to the seabed to explore the possibility of receiving head waves. The acoustic sources used were a 20-cui air gun and imploding sources comprising 60W and 75W light globes and purpose built evacuated spheres.

Justin Hoffman John; John D. Penrose; Darryl R. Mcmahon

2000-01-01T23:59:59.000Z

315

Uncertainty quantification in the presence of limited climate model data with discontinuities.  

SciTech Connect

Uncertainty quantification in climate models is challenged by the prohibitive cost of a large number of model evaluations for sampling. Another feature that often prevents classical uncertainty analysis from being readily 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 a discontinuity across a curve in the space of two uncertain parameters, namely climate sensitivity and CO2 forcing. In order to propagate uncertainties from model parameters to model output we use polynomial chaos (PC) expansions to represent the maximum overturning stream function in terms of the uncertain climate sensitivity and CO2 forcing parameters. Since the spectral methodology assumes a certain degree of smoothness, the presence of discontinuities suggests that separate PC expansions on each side of the discontinuity will lead to more accurate descriptions of the climate model output compared to global PC expansions. We propose a methodology that first finds a probabilistic description of the discontinuity given a number of data points. Assuming the discontinuity curve is a polynomial, the algorithm is based on Bayesian inference of its coefficients. Markov chain Monte Carlo sampling is used to obtain joint distributions for the polynomial coefficients, effectively parameterizing the distribution over all possible discontinuity curves. Next, we apply the Rosenblatt transformation to the irregular parameter domains on each side of the discontinuity. This transformation maps a space of uncertain parameters with specific probability distributions to a space of i.i.d standard random variables where orthogonal projections can be used to obtain PC coefficients. In particular, we use uniform random variables that are compatible with PC expansions based on Legendre polynomials. The Rosenblatt transformation and the corresponding PC expansions for the model output on either side of the discontinuity are applied successively for several realizations of the discontinuity curve. The climate model output and its associated uncertainty at specific design points is then computed by taking a quadrature-based integration average over PC expansions corresponding to possible realizations of the discontinuity curve.

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

2010-09-01T23:59:59.000Z

316

Sources of uncertainty in the calculation of loads on supports of piping systems  

SciTech Connect

Loads on piping systems are obtained from an analysis of the piping system. The piping system analysis involves uncertainties from various sources. These sources of uncertainties are discussed and ranges of uncertainties are illustrated by simple examples. The sources of uncertainties are summarized and assigned a judgmental ranking of the typical relative significance of the uncertainty.

Rodabaugh, E.C.

1984-06-01T23:59:59.000Z

317

Measurement uncertainty analysis techniques applied to PV performance measurements  

DOE Green Energy (OSTI)

The purpose of this presentation is to provide a brief introduction to measurement uncertainty analysis, outline how it is done, and illustrate uncertainty analysis with examples drawn from the PV field, with particular emphasis toward its use in PV performance measurements. The uncertainty information we know and state concerning a PV performance measurement or a module test result determines, to a significant extent, the value and quality of that result. What is measurement uncertainty analysis? It is an outgrowth of what has commonly been called error analysis. But uncertainty analysis, a more recent development, gives greater insight into measurement processes and tests, experiments, or calibration results. Uncertainty analysis gives us an estimate of the I interval about a measured value or an experiment`s final result within which we believe the true value of that quantity will lie. Why should we take the time to perform an uncertainty analysis? A rigorous measurement uncertainty analysis: Increases the credibility and value of research results; allows comparisons of results from different labs; helps improve experiment design and identifies where changes are needed to achieve stated objectives (through use of the pre-test analysis); plays a significant role in validating measurements and experimental results, and in demonstrating (through the post-test analysis) that valid data have been acquired; reduces the risk of making erroneous decisions; demonstrates quality assurance and quality control measures have been accomplished; define Valid Data as data having known and documented paths of: Origin, including theory; measurements; traceability to measurement standards; computations; uncertainty analysis of results.

Wells, C.

1992-10-01T23:59:59.000Z

318

Combinatorial aspects of total positivity  

E-Print Network (OSTI)

In this thesis I study combinatorial aspects of an emerging field known as total positivity. The classical theory of total positivity concerns matrices in which all minors are nonnegative. While this theory was pioneered ...

Williams, Lauren Kiyomi

2005-01-01T23:59:59.000Z

319

Total correlations and mutual information  

E-Print Network (OSTI)

In quantum information theory it is generally accepted that quantum mutual information is an information-theoretic measure of total correlations of a bipartite quantum state. We argue that there exist quantum states for which quantum mutual information cannot be considered as a measure of total correlations. Moreover, for these states we propose a different way of quantifying total correlations.

Zbigniew Walczak

2008-06-30T23:59:59.000Z

320

Uncertainty and sensitivity analysis of food pathway results with the MACCS Reactor Accident Consequence Model  

Science Conference Proceedings (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 food 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 87 imprecisely-known input variables on the following reactor accident consequences are studied: crop growing season dose, crop long-term dose, milk growing season dose, total food pathways dose, total ingestion pathways dose, total long-term pathways dose, area dependent cost, crop disposal cost, milk disposal cost, condemnation area, 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: fraction of cesium deposition on grain fields that is retained on plant surfaces and transferred directly to grain, maximum allowable ground concentrations of Cs-137 and Sr-90 for production of crops, ground concentrations of Cs-134, Cs-137 and I-131 at which the disposal of milk will be initiated due to accidents that occur during the growing season, ground concentrations of Cs-134, I-131 and Sr-90 at which the disposal of crops will be initiated due to accidents that occur during the growing season, rate of depletion of Cs-137 and Sr-90 from the root zone, transfer of Sr-90 from soil to legumes, transfer of Cs-137 from soil to pasture, transfer of cesium from animal feed to meat, and the transfer of cesium, iodine and strontium from animal feed to milk.

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

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321

The Propagation of Photons in the Dilute Ionized Gas  

E-Print Network (OSTI)

The dilute ionized gas is very popular in the Universe. Usually only the Compton interactions, the "Sunyaev-Zel'dovich" effect, were considered while photons propagated in this medium. In this paper the "soft-photon process" is considered. Due to the soft photons emitted during the propagation of a photon in the dilute ionized gas, the main photon (propagating in the original direction) will be redshifted. The formula to calculate this redshift is derived.

Yijia Zheng

2013-05-02T23:59:59.000Z

322

The Propagation of Photons in the Dilute Ionized Gas  

E-Print Network (OSTI)

The dilute ionized gas is very popular in the Universe. Usually only the Compton interactions, the "Sunyaev-Zel'dovich" effect, were considered while photons propagated in this medium. In this paper the "soft-photon process" is considered. Due to the soft photons emitted during the propagation of a photon in the dilute ionized gas, the main photon (propagating in the original direction) will be redshifted. The formula to calculate this redshift is derived.

Zheng, Yijia

2013-01-01T23:59:59.000Z

323

Fatigue reliability of wind turbine fleets: The effect of uncertainty of projected costs  

DOE Green Energy (OSTI)

The cost of repairing or replacing failed components depends on the number and timing of failures. Although the total probability of individual component failure is sometimes interpreted as the percentage of components likely to fail, this perception is often far from correct. Different amounts of common versus independent uncertainty can cause different numbers of components to be at risk of failure. The FAROW tool for fatigue and reliability analysis of wind turbines makes it possible for the first time to conduct a detailed economic analysis of the effects of uncertainty on fleet costs. By dividing the uncertainty into common and independent parts, the percentage of components expected to fail in each year of operation is estimated. Costs are assigned to the failures and the yearly costs and present values are computed. If replacement cost is simply a constant multiple of the number of failures, the average, or expected cost is the same as would be calculated by multiplying by the probability of individual component failure. However, more complicated cost models require a break down of how many components are likely to fail. This break down enables the calculation of costs associated with various probability of occurrence levels, illustrating the variability in projected costs. Estimating how the numbers of components expected to fail evolves over time is also useful in calculating the present value of projected costs and in understanding the nature of the financial risk.

Veers, P.S.

1995-12-31T23:59:59.000Z

324

Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint  

DOE Green Energy (OSTI)

One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

2013-10-01T23:59:59.000Z

325

Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems  

E-Print Network (OSTI)

We considered a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a high dimension spatial field. The Bayesian approach contains a natural mechanism for regularization in the form of prior information, can incorporate information from heterogeneous sources and provides a quantitative assessment of uncertainty in the inverse solution. The Bayesian setting casts the inverse solution as a posterior probability distribution over the model parameters. Karhunen-Lo'eve expansion and Discrete Cosine transform were used for dimension reduction of the random spatial field. Furthermore, we used a hierarchical Bayes model to inject multiscale data in the modeling framework. In this Bayesian framework, we have shown that this inverse problem is well-posed by proving that the posterior measure is Lipschitz continuous with respect to the data in total variation norm. The need for multiple evaluations of the forward model on a high dimension spatial field (e.g. in the context of MCMC) together with the high dimensionality of the posterior, results in many computation challenges. We developed two-stage reversible jump MCMC method which has the ability to screen the bad proposals in the first inexpensive stage. Channelized spatial fields were represented by facies boundaries and variogram-based spatial fields within each facies. Using level-set based approach, the shape of the channel boundaries was updated with dynamic data using a Bayesian hierarchical model where the number of points representing the channel boundaries is assumed to be unknown. Statistical emulators on a large scale spatial field were introduced to avoid the expensive likelihood calculation, which contains the forward simulator, at each iteration of the MCMC step. To build the emulator, the original spatial field was represented by a low dimensional parameterization using Discrete Cosine Transform (DCT), then the Bayesian approach to multivariate adaptive regression spline (BMARS) was used to emulate the simulator. Various numerical results were presented by analyzing simulated as well as real data.

Mondal, Anirban

2011-08-01T23:59:59.000Z

326

Neural network uncertainty assessment using Bayesian statistics with application to remote sensing  

E-Print Network (OSTI)

Neural network uncertainty assessment using Bayesian statistics with application to remote sensing for many inversion problems in remote sensing; however, uncertainty estimates are rarely provided Meteorology and Atmospheric Dynamics: General or miscellaneous; KEYWORDS: remote sensing, uncertainty, neural

Aires, Filipe

327

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

328

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..............................................................

329

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.....................................................

330

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.......................................................

331

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

332

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.................................

333

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...........................

334

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)

335

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

336

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.................................................................

337

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)...........................

338

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.........................................................

339

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

340

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.................................

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

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.......................................................

342

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.................................

343

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..........................

344

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.................................

345

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..........................

346

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..........................................................

347

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

348

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.......................................................................

349

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.....................................................................

350

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...................................................................

351

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.........................................................

352

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.....................................................................

353

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.................................

354

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....................................................

355

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.......................................................

356

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.................................

357

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.................................

358

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.................................................................

359

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

360

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.........................................................

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

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.................................

362

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.............................................................

363

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.......................................................

364

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......................................................................

365

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..........................................

366

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.........................................................

367

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

368

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.........................................................

369

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

370

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

371

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...................................................................

372

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......................................................................

373

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

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

60,000 to 79,999 80,000 or More Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

374

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

Annual Energy Outlook 2012 (EIA)

Usage Indicators by U.S. Census Region, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators U.S. Census Region Northeast Midwest South West Energy Information...

375

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

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

Homes Million U.S. Housing Units Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.7...

376

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

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

Homes Million U.S. Housing Units Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC4.7...

377

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

Annual Energy Outlook 2012 (EIA)

Self-Reported) City Town Suburbs Rural Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC8.7...

378

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

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

East North Central West North Central Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

379

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

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

U.S. Housing Units Home Electronics Usage Indicators Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005 Housing Units (millions) Energy Information...

380

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

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

U.S. Housing Units Home Electronics Usage Indicators Table HC8.12 Home Electronics Usage Indicators by UrbanRural Location, 2005 Housing Units (millions) Energy Information...

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

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

Gasoline and Diesel Fuel Update (EIA)

7.0 7.7 6.6 Have Equipment But Do Not Use it... 1.9 Q N Q 0.6 Air-Conditioning Equipment 1, 2 Central System......

382

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

Annual Energy Outlook 2012 (EIA)

Air-Conditioning Equipment 1, 2 Central System... 65.9 47.5 4.0 2.8 7.9 3.7 Without a Heat Pump... 53.5...

383

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

Gasoline and Diesel Fuel Update (EIA)

91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it... 1.9 Q Q Q Air-Conditioning Equipment 1, 2 Central System......

384

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

Gasoline and Diesel Fuel Update (EIA)

18.0 Have Equipment But Do Not Use it... 1.9 0.9 0.3 0.3 0.4 Air-Conditioning Equipment 1, 2 Central System......

385

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

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

m... 3.2 0.2 Q 0.1 Telephone and Office Equipment CellMobile Telephone... 84.8 14.9 11.1 3.9 Cordless...

386

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

Gasoline and Diesel Fuel Update (EIA)

m... 3.2 0.9 0.7 Q Telephone and Office Equipment CellMobile Telephone... 84.8 19.3 13.2 6.1 Cordless...

387

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

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

Q 0.5 Q Q Monitor is Turned Off... 0.5 N Q Q Q Q N Q Use of Internet Have Access to Internet Yes... 66.9...

388

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

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

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

389

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...

390

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...

391

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

Annual Energy Outlook 2012 (EIA)

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......

392

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

Annual Energy Outlook 2012 (EIA)

... 25.8 2.8 5.8 5.5 3.8 7.9 1.4 5.1 Use of Most-Used Ceiling Fan Used All Summer... 18.7 4.2 4.9 4.1 2.1 3.4 2.4 6.3...

393

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

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

Heating Characteristics Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC5.4 Space Heating...

394

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

Annual Energy Outlook 2012 (EIA)

at All... 2.9 1.1 0.5 Q 0.4 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools......

395

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

Annual Energy Outlook 2012 (EIA)

3.3 Not Used at All... 2.9 0.7 0.5 Q Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools... 54.9...

396

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

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

3.6 Not Used at All... 2.9 0.8 0.3 0.4 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools... 54.9...

397

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

Gasoline and Diesel Fuel Update (EIA)

1.1 Not Used at All... 2.9 0.4 Q 0.2 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools... 54.9...

398

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

Gasoline and Diesel Fuel Update (EIA)

at All... 2.9 1.4 0.4 0.4 0.7 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools......

399

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

Gasoline and Diesel Fuel Update (EIA)

5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business Yes......

400

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

Annual Energy Outlook 2012 (EIA)

... 34.3 1.2 0.9 2.2 2.9 5.4 7.0 8.2 6.6 Adequacy of Insulation Well Insulated... 29.5 1.5 0.9 2.3 2.7 4.1...

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

Valid Inequalities Based on Demand Propagation for Chemical ...  

E-Print Network (OSTI)

Oct 26, 2012 ... Valid Inequalities Based on Demand Propagation for Chemical Production Scheduling MIP Models. Sara Velez(szenner ***at*** wisc.edu)

402

Corrosion Fatigue and Crack Propagation of Different Austenitic ...  

Science Conference Proceedings (OSTI)

A FIB Study of the Resistance of Grain Boundaries to Short Fatigue Crack Propagation in Three-Dimensions in High Strength Al Alloys · A Non-Linear Damage ...

403

The Propagation and Attenuation of Surge Voltages and ...  

Science Conference Proceedings (OSTI)

... reflected pulse appearing 740 ns later, from which a propagation speed of ... nonreflection obtained by terminating the line with a resistance equal to ...

2013-05-17T23:59:59.000Z

404

Fatigue and Fatigue Crack Propagation Behaviors of High ...  

Science Conference Proceedings (OSTI)

The S-N fatigue and fatigue crack propagation (FCP) behaviors of high ... The mechanisms associated with the improved fatigue resistance for the high ...

405

Effects of Off-fault Damage on Earthquake Rupture Propagation ...  

Science Conference Proceedings (OSTI)

Instantaneous velocity was found by differentiating an interpolated cubic spline fit ..... propagation velocities determined for the angle b of the Mach cone in ...

406

Fast magnetosonic wave propagation and absorption in Tokamaks  

DOE Green Energy (OSTI)

Fast magnetostatic wave propagation and absorption in a tokamak model consisting of an axially symmetric cylindrical plasma column with a radially varying density profile is considered.

Phillips, C.K.; Perkins, F.W.; Hwang, D.Q.

1985-07-01T23:59:59.000Z

407

Methods for forecasting impulse noise propagation through the atmosphere  

Science Conference Proceedings (OSTI)

Predicting the sound levels outdoors at long distances from a given noisesource is a challenging and important problem. The propagation depends strongly on several environmental factors

Michael J. White

1991-01-01T23:59:59.000Z

408

Uncertainty Quantification Tools for Multiphase Flow Simulations using MFIX  

NLE Websites -- All DOE Office Websites (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

409

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

410

Sensitivity Studies of the Models of Radar-Rainfall Uncertainties  

Science Conference Proceedings (OSTI)

It is well acknowledged that there are large uncertainties associated with the operational quantitative precipitation estimates produced by the U.S. national network of the Weather Surveillance Radar-1988 Doppler (WSR-88D). These errors result ...

Gabriele Villarini; Witold F. Krajewski

2010-02-01T23:59:59.000Z

411

Patent Protection, Market Uncertainty, and R&D Investment  

E-Print Network (OSTI)

Wesley M. Cohen. (2003). “R&D and the Patent Premuim,” NBERDoes market uncertainty reduce R&D investments? A firm-level2001). “Irreversibility of R&D investment and the adverse

Toole, Andrew A; Czarnitzki, Dirk

2006-01-01T23:59:59.000Z

412

Creating value from uncertainty : a study of ocean transportation contracting  

E-Print Network (OSTI)

How can financial tools like real options and hedging mitigate and create value from uncertainty in transportation? This paper describes these concepts and identifies research on them that has relevance to transportation. ...

Pálsson, Sigurjón

2005-01-01T23:59:59.000Z

413

A Simple Equation for Regional Climate Change and Associated Uncertainty  

Science Conference Proceedings (OSTI)

Simple equations are developed to express regional climate changes for the twenty-first century and associated uncertainty in terms of the global temperature change (GTC) without a dependence on the underlying emission pathways. The equations are ...

Filippo Giorgi

2008-04-01T23:59:59.000Z

414

Reducing CO2 Emissions: Technology, Uncertainty, Decision Making...  

NLE Websites -- All DOE Office Websites (Extended Search)

Reducing CO2 Emissions: Technology, Uncertainty, Decision Making and Consumer Behavior Speaker(s): Ins Magarida Lima de Azevedo Date: October 31, 2012 - 4:00pm Location: 90-3122...

415

Uncertainties in the Anti-neutrino Production at Nuclear Reactors  

E-Print Network (OSTI)

39] “Improving Thermal Power Accuracy and Plant Safety WhileCanyon Power Plant (DCPP) (California, USA), the thermalthermal power measure- ments and ?ssion rate calculations. The uncertainties in these quantities for commercial power plants

Djurcic, Zelimir

2009-01-01T23:59:59.000Z

416

Uncertainty management in a distributed knowledge based system  

Science Conference Proceedings (OSTI)

In many situations, a knowledge source may not give definite hypothesis; it can only express its belief and disbelief in multiple hypotheses, We present a scheme of uncertainty management in such a system. Disbelief is given a considerable importance ...

Naseem A. Khan; Ramesh Jain

1985-08-01T23:59:59.000Z

417

Investment and Upgrade in Distributed Generation under Uncertainty  

E-Print Network (OSTI)

of the uncertainty in the natural gas price. Treat- ment ofits exposure to risk from natural gas price volatility. Inits exposure to the natural gas price and maximising its

Siddiqui, Afzal

2008-01-01T23:59:59.000Z

418

Analysis and reduction of chemical models under uncertainty.  

SciTech Connect

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

419

Quantifying Global Uncertainties in a Simple Microwave Rainfall Algorithm  

Science Conference Proceedings (OSTI)

While a large number of methods exist in the literature for retrieving rainfall from passive microwave brightness temperatures, little has been written about the quantitative assessment of the expected uncertainties in these rainfall products at ...

Christian Kummerow; Wesley Berg; Jody Thomas-Stahle; Hirohiko Masunaga

2006-01-01T23:59:59.000Z

420

Analysis of automated highway system risks and uncertainties. Volume 5  

SciTech Connect

This volume describes a risk analysis performed to help identify important Automated Highway System (AHS) deployment uncertainties and quantify their effect on costs and benefits for a range of AHS deployment scenarios. The analysis identified a suite of key factors affecting vehicle and roadway costs, capacities and market penetrations for alternative AHS deployment scenarios. A systematic protocol was utilized for obtaining expert judgments of key factor uncertainties in the form of subjective probability percentile assessments. Based on these assessments, probability distributions on vehicle and roadway costs, capacity and market penetration were developed for the different scenarios. The cost/benefit risk methodology and analysis provide insights by showing how uncertainties in key factors translate into uncertainties in summary cost/benefit indices.

Sicherman, A.

1994-10-01T23:59:59.000Z

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

Uncertainty of Tropical Cyclone Best-Track Information  

Science Conference Proceedings (OSTI)

With the growing use of tropical cyclone (TC) best-track information for weather and climate applications, it is important to understand the uncertainties that are contained in the TC position and intensity information. Here, an attempt is made to ...

Ryan D. Torn; Chris Snyder

2012-06-01T23:59:59.000Z

422

Designing transit concession contracts to deal with uncertainty  

E-Print Network (OSTI)

This thesis proposes a performance regime structure for public transit concession contracts, designed so incentives to the concessionaire can be effective given significant uncertainty about the future operating conditions. ...

Blakey, Tara Naomi Chin

2006-01-01T23:59:59.000Z

423

Probabilistic Accident Consequence Uncertainty - A Joint CEC/USNRC Study  

Science Conference Proceedings (OSTI)

The joint USNRC/CEC consequence uncertainty study was chartered after the development of two new probabilistic accident consequence codes, MACCS in the U.S. and COSYMA in Europe. Both the USNRC and CEC had a vested interest in expanding the knowledge base of the uncertainty associated with consequence modeling, and teamed up to co-sponsor a consequence uncertainty study. The information acquired from the study was expected to provide understanding of the strengths and weaknesses of current models as well as a basis for direction of future research. This paper looks at the elicitation process implemented in the joint study and discusses some of the uncertainty distributions provided by eight panels of experts from the U.S. and Europe that were convened to provide responses to the elicitation. The phenomenological areas addressed by the expert panels include atmospheric dispersion and deposition, deposited material and external doses, food chain, early health effects, late health effects and internal dosimetry.

Gregory, Julie J.; Harper, Frederick T.

1999-07-28T23:59:59.000Z

424

Uncertainty in Greenhouse Emissions and Costs of Atmospheric Stabilization  

E-Print Network (OSTI)

We explore the uncertainty in projections of emissions, and costs of atmospheric stabilization applying the MIT Emissions Prediction and Policy Analysis model, a computable general equilibrium model of the global economy. ...

Webster, Mort D.

425

Integration of Uncertainty Information into Power System Operations  

Science Conference Proceedings (OSTI)

Contemporary power systems face uncertainties coming from multiple sources, including forecast errors of load, wind and solar generation, uninstructed deviation and forced outage of traditional generators, loss of transmission lines, and others. With increasing amounts of wind and solar generation being integrated into the system, these uncertainties have been growing significantly. It is critical important to build knowledge of major sources of uncertainty, learn how to simulate them, and then incorporate this information into the decision-making processes and power system operations, for better reliability and efficiency. This paper gives a comprehensive view on the sources of uncertainty in power systems, important characteristics, available models, and ways of their integration into system operations. It is primarily based on previous works conducted at the Pacific Northwest National Laboratory (PNNL).

Makarov, Yuri V.; Lu, Shuai; Samaan, Nader A.; Huang, Zhenyu; Subbarao, Krishnappa; Etingov, Pavel V.; Ma, Jian; Hafen, Ryan P.; Diao, Ruisheng; Lu, Ning

2011-10-10T23:59:59.000Z

426

Including model uncertainty in risk-informed decision-making  

E-Print Network (OSTI)

Model uncertainties can have a significant impact on decisions regarding licensing basis changes. We present a methodology to identify basic events in the risk assessment that have the potential to change the decision and ...

Reinert, Joshua M

2005-01-01T23:59:59.000Z

427

Stochastic and Robust Approaches to Optimization Problems under Uncertainty  

Science Conference Proceedings (OSTI)

In the last decade, optimization models under uncertainty have drawn much attention and efficient algorithms have been developed for solving those problems. This article presents the author's recent attempts conducted in collaboration with a number of ...

Masao Fukushima

2007-01-01T23:59:59.000Z

428

Reducing Uncertainty for the DeltaQ Duct Leakage Test  

E-Print Network (OSTI)

the DeltaQ duct Leakage Test”. ASHRAE Transactions (inof a new Duct Leakage Test: DeltaQ. LBNL 47308. Walker, I,Uncertainties in the DeltaQ test for Duct Leakage.

Walker, Iain S.; Sherman, Max H.; Dickerhoff, Darryl J.

2004-01-01T23:59:59.000Z

429

Real options approach to capacity planning under uncertainty  

E-Print Network (OSTI)

This thesis highlights the effectiveness of Real Options Analysis (ROA) in capacity planning decisions for engineering projects subject to uncertainty. This is in contrast to the irreversible decision-making proposed by ...

Mittal, Geetanjali, 1979-

2004-01-01T23:59:59.000Z

430

Estimating Monthly Precipitation Reconstruction Uncertainty Beginning in 1900  

Science Conference Proceedings (OSTI)

Uncertainty estimates are computed for a statistical reconstruction of global monthly precipitation that was developed in an earlier publication. The reconstruction combined the use of spatial correlations with gauge precipitation and correlations ...

Thomas M. Smith; Samuel S. P. Shen; Li Ren; Phillip A. Arkin

2013-06-01T23:59:59.000Z

431

Investment and Upgrade in Distributed Generation under Uncertainty  

E-Print Network (OSTI)

in the natural gas price. Treat- ment of uncertainty viato risk from natural gas price volatility. In particular,exposure to the natural gas price and maximising its cost

Siddiqui, Afzal

2008-01-01T23:59:59.000Z

432

Impact of PV forecasts uncertainty in batteries management in microgrids  

E-Print Network (OSTI)

Impact of PV forecasts uncertainty in batteries management in microgrids Andrea Michiorri Arthur-based battery schedule optimisation in microgrids in presence of network constraints. We examine a specific case

Recanati, Catherine

433

Uncertainties in the Radiative Forcing Due to Sulfate Aerosols  

Science Conference Proceedings (OSTI)

Radiative transfer calculations based on a new sulfate distribution from a chemistry-transport model simulation have been performed. A wide range of sensitivity experiments have been performed to illustrate the large uncertainty in the radiative ...

Gunnar Myhre; Frode Stordal; Tore F. Berglen; Jostein K. Sundet; Ivar S. A. Isaksen

2004-03-01T23:59:59.000Z

434

Quantification of Cloud Microphysical Parameterization Uncertainty Using Radar Reflectivity  

Science Conference Proceedings (OSTI)

Uncertainty in cloud microphysical parameterization—a leading order contribution to numerical weather prediction error—is estimated using a Markov chain Monte Carlo (MCMC) algorithm. An inversion is performed on 10 microphysical parameters using ...

Marcus van Lier-Walqui; Tomislava Vukicevic; Derek J. Posselt

2012-11-01T23:59:59.000Z

435

Ensemble Representation of Uncertainty in Lagrangian Satellite Rainfall Estimates  

Science Conference Proceedings (OSTI)

A new algorithm LSIM (Lagrangian Simulation) has been developed which enables the interpolation uncertainty present in Lagrangian satellite rainfall algorithms such as CMORPH to be characterized using an ensemble product. The new algorithm ...

T. J. Bellerby

436

Plasma Propagation Through Porous Dielectric Sheets  

E-Print Network (OSTI)

Abstract—The propagation of plasmas through porous materials is one extreme example of a packed-bed reactor. Mechanisms for atmospheric-pressure plasmas flowing through porous dielectric films are computationally investigated. Images of this plasma flow are discussed. Index Terms—Photoionization, plasma functionalization. ATMOSPHERIC-PRESSURE plasmas (APPs) in dielectric barrier discharge (DBD) configurations are widely used for remediation of toxic gases. One such configuration is a packed-bed reactor where the plasma flows along the surface of high-dielectric-constant (?) beads where electric fields are intensified by the gradient in ? [1]. Typical DBD plasmas operate in air at atmospheric pressure at a few to tens of kilohertz, having electrode separations of a few millimeters to a centimeter. One extreme example of a packed-bed DBD reactor

Mingmei Wang; John E. Foster; Mark J. Kushner

2011-01-01T23:59:59.000Z

437

Structure of propagators for quantum nondemolition systems  

E-Print Network (OSTI)

In the scheme of a quantum nondemolition (QND) measurement, an observable is measured without perturbing its evolution. In the context of studies of decoherence in quantum computing, we examine the `open' quantum system of a two-level atom, or equivalently, a spin-1/2 system, in interaction with quantum reservoirs of either oscillators or spins, under the QND condition of the Hamiltonian of the system commuting with the system-reservoir interaction. The propagators for these QND Hamiltonians are shown to be connected to the squeezing and rotation operators for the two baths, respectively. Squeezing and rotation being both phase space area-preserving canonical transformations, this brings out an interesting analogy between the energy-preserving QND Hamiltonians and the homogeneous linear canonical transformations.

Subhashish Banerjee; R. Ghosh

2006-11-11T23:59:59.000Z

438

Epidemic Propagation In Overlaid Wireless Networks  

SciTech Connect

Witb tbe emergence of computer worms tbat can spread over air interfaces, wireless ad boc and sensor networks can be vulnerable to node compromises even if the deployed network is not connected to the backbone. Depending on the physical topology of the wireless network, even a single infected node can compromise the whole network. In this work, epidemic (e.g., worm) propagation in a static wireless network is studied, where a number of inCected mobile nodes are injected over the existing network. It is shown that the epidemic spread threshold and size depend on the physical topology of the underlying static wireless network as well as the mobility model employed by the infected mobile nodes. More specifically, results show that in a Cully-connected static wirelessnctwork targeted attacks are more effective, wbereas Cor a random topology random attacks can be sufficient to compromise the whole network.

Yanmaz, Evsen [Los Alamos National Laboratory

2008-01-01T23:59:59.000Z

439

Forecast of total nitrogen in wastewater treatment plants by means techniques of soft computing  

Science Conference Proceedings (OSTI)

Prediction in Wastewater Treatment Plants is an important purpose for decision-making. The complexity of the biological processes happening and, on the other hand, the uncertainty and incompleteness of the real data lead us to treat this problem modelling ... Keywords: environmental modelling, fuzzy systems, genetic algoritms, neural networks, soft computing, total nitrogen, wastewater treatment plant

Narcis Clara

2008-07-01T23:59:59.000Z

440

Uncertainty Representation: Estimating Process Parameters for Forward Price Forecasting  

Science Conference Proceedings (OSTI)

Market prices set the value of electric power assets and contracts, yet forward prices are unavailable for time horizons relevant to most valuations. Price forecasts are inherently uncertain because the drivers of prices are uncertain, but equilibrating market forces also work to reduce the growth of uncertainty over time. Consequently, quantifying the degree of future price uncertainty is difficult, but has tremendous strategic potential for power companies seeking to value real options and invest in fl...

1999-12-10T23:59:59.000Z

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

Uncertainties in the Anti-neutrino Production at Nuclear Reactors  

Science Conference Proceedings (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 {bar {nu}}{sub e} detectors is examined. We discuss reactor-to-reactor correlations between the leading uncertainties, and their relevance to reactor {bar {nu}}{sub e} experiments.

Djurcic, Zelimir; Detwiler, Jason A.; Piepke, Andreas; Foster Jr., Vince R.; Miller, Lester; Gratta, Giorgio

2008-08-06T23:59:59.000Z

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

Uncertainty and sensitivity analysis for long-running computer codes : a critical review  

E-Print Network (OSTI)

This thesis presents a critical review of existing methods for performing probabilistic uncertainty and sensitivity analysis for complex, computationally expensive simulation models. Uncertainty analysis (UA) methods ...

Langewisch, Dustin R

2010-01-01T23:59:59.000Z

444

Statistically based uncertainty analysis for ranking of component importance in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor  

SciTech Connect

The Analytic Hierarchy Process (AHP) has been used to help determine the importance of components and phenomena in thermal-hydraulic safety analyses of nuclear reactors. The AHP results are based, in part on expert opinion. Therefore, it is prudent to evaluate the uncertainty of the AHP ranks of importance. Prior applications have addressed uncertainty with experimental data comparisons and bounding sensitivity calculations. These methods work well when a sufficient experimental data base exists to justify the comparisons. However, in the case of limited or no experimental data the size of the uncertainty is normally made conservatively large. Accordingly, the author has taken another approach, that of performing a statistically based uncertainty analysis. The new work is based on prior evaluations of the importance of components and phenomena in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor (ANSR), a new facility now in the design phase. The uncertainty during large break loss of coolant, and decay heat removal scenarios is estimated by assigning a probability distribution function (pdf) to the potential error in the initial expert estimates of pair-wise importance between the components. Using a Monte Carlo sampling technique, the error pdfs are propagated through the AHP software solutions to determine a pdf of uncertainty in the system wide importance of each component. To enhance the generality of the results, study of one other problem having different number of elements is reported, as are the effects of a larger assumed pdf error in the expert ranks. Validation of the Monte Carlo sample size and repeatability are also documented.

Wilson, G.E.

1992-01-01T23:59:59.000Z

445

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......................................

446

ENERGY CONTENT AND PROPAGATION IN TRANSVERSE SOLAR ATMOSPHERIC WAVES  

SciTech Connect

Recently, a significant amount of transverse wave energy has been estimated propagating along solar atmospheric magnetic fields. However, these estimates have been made with the classic bulk Alfven wave model which assumes a homogeneous plasma. In this paper, the kinetic, magnetic, and total energy densities and the flux of energy are computed for transverse MHD waves in one-dimensional cylindrical flux tube models with a piecewise constant or continuous radial density profile. There are fundamental deviations from the properties for classic bulk Alfven waves. (1) There is no local equipartition between kinetic and magnetic energy. (2) The flux of energy and the velocity of energy transfer have, in addition to a component parallel to the magnetic field, components in the planes normal to the magnetic field. (3) The energy densities and the flux of energy vary spatially, contrary to the case of classic bulk Alfven waves. This last property has the important consequence that the energy flux computed with the well known expression for bulk Alfven waves could overestimate the real flux by a factor in the range 10-50, depending on the flux tube equilibrium properties.

Goossens, M.; Van Doorsselaere, T. [Centre for mathematical Plasma Astrophysics, Mathematics Department, Celestijnenlaan 200B bus 2400, B-3001 Heverlee (Belgium); Soler, R. [Solar Physics Group, Departament de Fisica, Universitat de les Illes Balears, E-07122 Palma de Mallorca (Spain); Verth, G., E-mail: tom.vandoorsselaere@wis.kuleuven.be [Solar Physics and Space Plasma Research Centre (SP2RC), School of Mathematics and Statistics, University of Sheffield, Hounsfield Road, Hicks Building, Sheffield S3 7RH (United Kingdom)

2013-05-10T23:59:59.000Z

447

Polarization dependence of radiowave propagation through Antarctic ice  

E-Print Network (OSTI)

Using a bistatic radar system on the ice surface, we have studied radiofrequency reflections off internal layers in Antarctic ice at the South Pole. In our measurement, the total propagation time of ~ns-duration, vertically broadcast radio signals, as a function of polarization axis in the horizontal plane, provides a direct probe of the geometry-dependence of the ice permittivity to depths of 1--2 km. Previous studies in East Antarctica have interpreted the measured azimuthal dependence of reflected signals as evidence for birefringent-induced interference effects, which are proposed to result from preferred alignment of the crystal orientation fabric (COF) axis. To the extent that COF alignment results from the bulk flow of ice across the Antarctic continent, we would expect a measurable birefringent asymmetry at South Pole, as well. Although we also observe clear dependence of reflected amplitude on polarization angle in our measurements, we do not observe direct evidence for birefringent-induced time-delay effects at the level of 0.1 parts per mille.

Dave Z. Besson

2008-03-30T23:59:59.000Z

448

China Total Cloud Amount Trends  

NLE Websites -- All DOE Office Websites (Extended Search)

Trends in Total Cloud Amount Over China DOI: 10.3334CDIACcli.008 data Data image Graphics Investigator Dale P. Kaiser Carbon Dioxide Information Analysis Center, Environmental...

449

Analysis of inverter models and harmonic propagation. Part II. Harmonic propagation  

SciTech Connect

Part II of a three part study describes the harmonic propagation in the photovoltaic power system consisting of the solar cell array, the inverter, and the ac side of the inverter up to the infinite bus of the utility. Propagation of the harmonics in the utility system are not addressed. Two main problems are analyzed: power in the converter system and harmonics of the current and voltage waveforms of the single-phase, dependent inverter. Relationships between the different components of the converter power - active, reactive and disturbance - are discussed. All formulas necessary for calculating the power components are given, assuming the harmonics of the current and voltage waveforms are known. The theoretical and experimental investigation of the single-phase, dependent inverter is described. The ac and dc terminal voltage of the inverter are analyzed and their harmonics are obtained. These data determine the harmonic propagation on both the dc and ac sides and may be useful for equipment design. Part I of the study (SAND 7040/1) contains a detailed description of the microcomputer based simulator that represents the output characteristics of the five commercially available types of solar cell arrays under different environmental conditions, and Part III (SAND 7040/3) presents an analysis of the transient and steady-state processes of inverter modules.

Slonim, M.A.; Stanek, E.K.

1984-09-01T23:59:59.000Z

450

Dynamic quantization for belief propagation in sparse spaces  

Science Conference Proceedings (OSTI)

Graphical models provide an attractive framework for modeling a variety of problems in computer vision. The advent of powerful inference techniques such as belief propagation (BP) has recently made inference with many of these models tractable. Even ... Keywords: Belief propagation, Deformable templates, Graphical models, Markov random fields, Pruning

James Coughlan; Huiying Shen

2007-04-01T23:59:59.000Z

451

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

452

Visual Scanning Hartmann Optical Tester (VSHOT) Uncertainty Analysis (Milestone Report)  

DOE Green Energy (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

453

Pulse propagation through a dispersive intracavity medium  

E-Print Network (OSTI)

In this paper, we study theoretically the behavior of a pulse as it propagates through an intracavity fast-light medium. The method of using a transfer function to determine a pulse after it passes through a cavity is well known. However, this approach cannot be used to determine the behavior of the pulse inside the cavity. To circumvent this constraint, we use an approach that starts by finding a self-consistent solution for a monochromatic field of infinite spatial and temporal extents, and determine its amplitudes before, inside, and after the cavity. We then construct a Gaussian input pulse by adding a set of these waves, properly phased and weighted, to represent a moving pulse before the cavity. Adding these waves at various time intervals then yields the complete spatial profile everywhere, including before, inside and after the cavity. We first confirm the prediction of this model by analyzing the behavior of a pulse passing through an empty cavity, and comparing the prediction of the output with the ...

Yum, Honam; Shahriar, Selim

2010-01-01T23:59:59.000Z

454

Experimental studies of lower hybrid wave propagation  

SciTech Connect

Experimental measurements of the dispersion and damping of externally excited lower hybrid waves are presented. A multiple-ring slow-wave antenna, having 2$pi$/k/sub z/ = 23 cm, is used to excite these waves in the Princeton L3 or L4 linear devices (B = 0.5 -- 2.8 kG uniform to +- 1 percent for 1.6 m, n approximately 10$sup 10$, T/sub e/ approximately 3-5 eV, T/sub i/ less than or equal to 0.1 eV, He gas, plasma diameter approximately 10 cm). The waves are localized in a spatial wave packet that propagates into the plasma along a conical trajectory which makes a small angle with respect to the confining magnetic field. Measurements of the dependence of wavelength on frequency are in good agreement with the cold plasma dispersion relation. Measured values of the wave damping are in good agreement with Landau damping by the combination of the main body of the electron distribution and a approximately 30 percent high energy (T/sub e/ approximately 15-30 eV) electron tail. (auth)

Bellan, P.; Porkolab, M.

1976-01-01T23:59:59.000Z

455

Adaptive Optimization and Systematic Probing of Infrastructure System Maintenance Policies under Model Uncertainty  

E-Print Network (OSTI)

Maintenance; Optimization; Probabilistic models; Adaptive systems; Uncertainty principles . Introduction Infrastructure management systems

Madanat, S M; Park, Sejung; Kuhn, K D

2006-01-01T23:59:59.000Z

456

Investment and Upgrade in Distributed Generation under Uncertainty  

NLE Websites -- All DOE Office Websites (Extended Search)

Investment and Upgrade in Distributed Generation under Uncertainty Investment and Upgrade in Distributed Generation under Uncertainty Speaker(s): Afzal Siddiqui Karl Maribu Date: September 4, 2008 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Galen Barbose The ongoing deregulation of electricity industries worldwide is providing incentives for microgrids to use small-scale distributed generation (DG) and combined heat and power (CHP) applications via heat exchangers (HXs) to meet local energy loads. Although the electric-only effciency of DG is lower than that of central-station production, relatively high tariff rates and the potential for CHP applications increase the attractiveness of on-site generation. Nevertheless, a microgrid contemplating the installation of gas-fired DG has to be aware of the uncertainty in the

457

Using dual decomposition for solving problems involving data uncertainty |  

NLE Websites -- All DOE Office Websites (Extended Search)

dual decomposition for solving problems involving data uncertainty dual decomposition for solving problems involving data uncertainty August 14, 2013 Tweet EmailPrint Many applications mdash; energy, routing, scheduling, and production planning, for example mdash; involve problems in which some or all of the data may not be known when decisions under uncertainty must be made. In such cases, approximations with stochastic mixed-integer programming models are often used. Two approaches have been suggested to address such problems: dual decomposition (DD) and branch-and-price (BP). Both approaches divide the problem into two or more subproblems, together with linear constraints that enforce agreement between solutions to the different problems through a series of iterations. Unfortunately, both approaches also suffer from lack

458

Microsoft Word - Documentation - Price Forecast Uncertainty.doc  

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

October 2009 October 2009 1 October 2009 Short-Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty 1 Summary It is often noted that energy prices are quite volatile, reflecting market participants' adjustments to new information from physical energy markets and/or markets in energy- related financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the market- clearing process for risk transfer can be used to generate "price bands" around observed futures prices for crude oil, natural gas, and other commodities. These bands provide a quantitative measure of uncertainty regarding the range in which markets expect prices to

459

Modified Phenomena Identification and Ranking Table (PIRT) for Uncertainty Analysis  

SciTech Connect

This paper describes a methodology of characterizing important phenomena, which is also part of a broader research by the authors called 'Modified PIRT'. The methodology provides robust process of phenomena identification and ranking process for more precise quantification of uncertainty. It is a two-step process of identifying and ranking methodology based on thermal-hydraulics (TH) importance as well as uncertainty importance. Analytical Hierarchical Process (AHP) has been used for as a formal approach for TH identification and ranking. Formal uncertainty importance technique is used to estimate the degree of credibility of the TH model(s) used to represent the important phenomena. This part uses subjective justification by evaluating available information and data from experiments, and code predictions. The proposed methodology was demonstrated by developing a PIRT for large break loss of coolant accident LBLOCA for the LOFT integral facility with highest core power (test LB-1). (authors)

Gol-Mohamad, Mohammad P.; Modarres, Mohammad; Mosleh, Ali [University of Maryland, College Park, MD 20742 (United States)

2006-07-01T23:59:59.000Z

460

Uncertainty quantification and validation of combined hydrological and macroeconomic analyses.  

SciTech Connect

Changes in climate can lead to instabilities in physical and economic systems, particularly in regions with marginal resources. Global climate models indicate increasing global mean temperatures over the decades to come and uncertainty in the local to national impacts means perceived risks will drive planning decisions. Agent-based models provide one of the few ways to evaluate the potential changes in behavior in coupled social-physical systems and to quantify and compare risks. The current generation of climate impact analyses provides estimates of the economic cost of climate change for a limited set of climate scenarios that account for a small subset of the dynamics and uncertainties. To better understand the risk to national security, the next generation of risk assessment models must represent global stresses, population vulnerability to those stresses, and the uncertainty in population responses and outcomes that could have a significant impact on U.S. national security.

Hernandez, Jacquelynne; Parks, Mancel Jordan; Jennings, Barbara Joan; Kaplan, Paul Garry; Brown, Theresa Jean; Conrad, Stephen Hamilton

2010-09-01T23:59:59.000Z

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.


461

Statistical uncertainty analysis of radon transport in nonisothermal, unsaturated soils  

Science Conference Proceedings (OSTI)

To accurately predict radon fluxes soils to the atmosphere, we must know more than the radium content of the soil. Radon flux from soil is affected not only by soil properties, but also by meteorological factors such as air pressure and temperature changes at the soil surface, as well as the infiltration of rainwater. Natural variations in meteorological factors and soil properties contribute to uncertainty in subsurface model predictions of radon flux, which, when coupled with a building transport model, will also add uncertainty to predictions of radon concentrations in homes. A statistical uncertainty analysis using our Rn3D finite-element numerical model was conducted to assess the relative importance of these meteorological factors and the soil properties affecting radon transport. 10 refs., 10 figs., 3 tabs.

Holford, D.J.; Owczarski, P.C.; Gee, G.W.; Freeman, H.D.

1990-10-01T23:59:59.000Z

462

Resource allocation using quantification of margins and uncertainty.  

SciTech Connect

There is an increasing need to assess the performance of high consequence systems using a modeling and simulation based approach. Central to this approach are the need to quantify the uncertainties present in the system and to compare the system response to an expected performance measure. At Sandia National Laboratories, this process is referred to as quantification of margins and uncertainties or QMU. Depending on the outcome of the assessment, there might be a need to increase the confidence in the predicted response of a system model; thus a need to understand where resources need to be allocated to increase this confidence. This paper examines the problem of resource allocation done within the context of QMU. An optimization based approach to solving the resource allocation is considered and sources of aleatoric and epistemic uncertainty are included in the calculations.

Mahadevan, Sankaran (Vanderbilt University, Nashville, TN); Urbina, Angel; Paez, Thomas Lee (Thomas Paez Consulting, Durango, CO)

2010-03-01T23:59:59.000Z

463

U.S. Total Exports  

Annual Energy Outlook 2012 (EIA)

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...

464

Optimal Reservoir Management and Well Placement Under Geologic Uncertainty  

E-Print Network (OSTI)

Reservoir management, sometimes referred to as asset management in the context of petroleum reservoirs, has become recognized as an important facet of petroleum reservoir development and production operations. In the first stage of planning field development, the simulation model is calibrated to dynamic data (history matching). One of the aims of the research is to extend the streamline based generalized travel time inversion method for full field models with multimillion cells through the use of grid coarsening. This makes the streamline based inversion suitable for high resolution simulation models with decades long production history and numerous wells by significantly reducing the computational effort. In addition, a novel workflow is proposed to integrate well bottom-hole pressure data during model calibration and the approach is illustrated via application to the CO2 sequestration. In the second stage, field development strategies are optimized. The strategies are primarily focused on rate optimization followed by infill well drilling. A method is proposed to modify the streamline-based rate optimization approach which previously focused on maximizing sweep efficiency by equalizing arrival time of the waterfront to producers, to account for accelerated production for improving the net present value (NPV). Optimum compromise between maximizing sweep efficiency and maximizing NPV can be selected based on a 'trade-off curve.' The proposed method is demonstrated on field scale application considering geological uncertainty. Finally, a novel method for well placement optimization is proposed that relies on streamlines and time of flight to first locate the potential regions of poorly swept and drained oil. Specifically, the proposed approach utilizes a dynamic measure based on the total streamline time of flight combined with static and dynamic parameters to identify "Sweet-Spots" for infill drilling. The "Sweet-Spots" can be either used directly as potential well-placement locations or as starting points during application of a formal optimization technique. The main advantage of the proposed method is its computational efficiency in calculating dynamic measure map. The complete workflow was also demonstrated on a multimillion cell reservoir model of a mature carbonate field with notable success. The infill locations based on dynamic measure map have been verified by subsequent drilling.

Taware, Satyajit Vijay

2012-08-01T23:59:59.000Z

465

Uncertainty evaluation of delayed neutron decay parameters  

E-Print Network (OSTI)

In a nuclear reactor, delayed neutrons play a critical role in sustaining a controllable chain reaction. Delayed neutron’s relative yields and decay constants are very important for modeling reactivity control and have been studied for decades. Researchers have tried different experimental and numerical methods to assess these delayed neutron parameters. The reported parameter values vary widely, much more than the small statistical errors reported with these parameters. Interestingly, the reported parameters fit their individual measurement data well in spite of these differences. This dissertation focuses on evaluation of the errors and methods of delayed neutron relative yields and decay constants for thermal fission of U-235. Various numerical methods used to extract the delayed neutron parameter from the measured data, including Matrix Inverse, Levenberg-Marquardt, and Quasi-Newton methods, were studied extensively using simulated delayed neutron data. This simulated data was Poisson distributed around Keepin’s theoretical data. The extraction methods produced totally different results for the same data set, and some of the above numerical methods could not even find solutions for some data sets. Further investigation found that ill-conditioned matrices in the objective function were the reason for the inconsistent results. To find a reasonable solution with small variation, a regularization parameter was introduced using a numerical method called Ridge Regression. The results from the Ridge Regression method, in terms of goodness of fit to the data, were good and often better than the other methods. Due to the introduction of a regularization number in the algorithm, the fitted result contains a small additional bias, but this method can guarantee convergence no matter how large the coefficient matrix condition number. Both saturation and pulse modes were simulated to focus on different groups. Some of the factors that affect the solution stability were investigated including initial count rate, sample flight time, initial guess values. Finally, because comparing reported delayed neutron parameters among different experiments is useless to determine if their data actually differs, methods are proposed that can be used to compare the delayed neutron data sets.

Wang, Jinkai

2008-12-01T23:59:59.000Z

466

Incorporating uncertainty into electric utility projections and decisions  

Science Conference Proceedings (OSTI)

This paper focuses on how electric utility companies can respond in their decision making to uncertain variables. Here we take a mean- variance type of approach. The mean'' value is an expected cost, on a discounted value basis. We assume that management has risk preferences incorporating a tradeoff between the mean and variance in the utility's net income. Decisions that utilities are faced with can be classified into two types: ex ante and ex post. The ex ante decisions need to be made prior to the uncertainty being revealed and the ex post decision can be postponed until after the uncertainty is revealed. Intuitively, we can say that the ex ante decisions provide a hedge against the uncertainties and the ex post decisions allow the negative outcomes of uncertain variables to be partially mitigated, dampening the losses. An example of an ex post decision is how the system is operated i.e., unit dispatch, and in some cases switching among types of fuels, say with different sulfur contents. For example, if gas prices go up, natural gas combined cycle units are likely to be dispatched at lower capacity factors. If SO{sub 2} emission allowance prices go up, a utility may seek to switch into a lower sulfur coal. Here we assume that regulated electric utilities do have some incentive to lower revenue requirements and hence an incentive to lower the electric rates needed for the utility to break even, thereby earning a fair return on invested capital. This paper presents the general approach first, including applications to capacity expansion and system dispatch. Then a case study is presented focusing on the 1990 Clean Air Act Amendments including SO{sub 2} emissions abatement and banking of allowances under uncertainty. It is concluded that the emission banking decisions should not be made in isolation but rather all the uncertainties in demand, fuel prices, technology performance etc., should be included in the uncertainty analysis affecting emission banking.

Hanson, D.A.

1992-01-01T23:59:59.000Z

467

Incorporating uncertainty into electric utility projections and decisions  

Science Conference Proceedings (OSTI)

This paper focuses on how electric utility companies can respond in their decision making to uncertain variables. Here we take a mean- variance type of approach. The ``mean`` value is an expected cost, on a discounted value basis. We assume that management has risk preferences incorporating a tradeoff between the mean and variance in the utility`s net income. Decisions that utilities are faced with can be classified into two types: ex ante and ex post. The ex ante decisions need to be made prior to the uncertainty being revealed and the ex post decision can be postponed until after the uncertainty is revealed. Intuitively, we can say that the ex ante decisions provide a hedge against the uncertainties and the ex post decisions allow the negative outcomes of uncertain variables to be partially mitigated, dampening the losses. An example of an ex post decision is how the system is operated i.e., unit dispatch, and in some cases switching among types of fuels, say with different sulfur contents. For example, if gas prices go up, natural gas combined cycle units are likely to be dispatched at lower capacity factors. If SO{sub 2} emission allowance prices go up, a utility may seek to switch into a lower sulfur coal. Here we assume that regulated electric utilities do have some incentive to lower revenue requirements and hence an incentive to lower the electric rates needed for the utility to break even, thereby earning a fair return on invested capital. This paper presents the general approach first, including applications to capacity expansion and system dispatch. Then a case study is presented focusing on the 1990 Clean Air Act Amendments including SO{sub 2} emissions abatement and banking of allowances under uncertainty. It is concluded that the emission banking decisions should not be made in isolation but rather all the uncertainties in demand, fuel prices, technology performance etc., should be included in the uncertainty analysis affecting emission banking.

Hanson, D.A.

1992-07-01T23:59:59.000Z

468

Maxwell Equation for the Coupled Spin-Charge Wave Propagation  

SciTech Connect

We show that the dissipationless spin current in the ground state of the Rashba model gives rise to a reactive coupling between the spin and charge propagation, which is formally identical to the coupling between the electric and the magnetic fields in the 2 + 1 dimensional Maxwell equation. This analogy leads to a remarkable prediction that a density packet can spontaneously split into two counter propagation packets, each carrying the opposite spins. In a certain parameter regime, the coupled spin and charge wave propagates like a transverse 'photon'. We propose both optical and purely electronic experiments to detect this effect.

Bernevig, B.Andrei; Yu, Xiaowei; Zhang, Shou-Cheng; /Stanford U., Phys. Dept.

2010-01-15T23:59:59.000Z

469

Estimating uncertainty in thermal-hydraulic codes using the linear variate method  

Science Conference Proceedings (OSTI)

Thermal-hydraulic codes are subject o uncertainties that must be considered in determining whether safety criteria are satisfied in nuclear reactors. Uncertainties correspond to parameters in a thermal-hydraulic model. A thermal-hydraulic model is typically a nonlinear, discontinuous function of the uncertainties. Evaluating the effect of the uncertainties is difficult. This paper describes an efficient Monte Carlo method for determining the effect of the uncertainties.

Kubic, W.L. Jr. (Los Alamos National Laboratory, NM (USA)); White, A.M. (Westinghouse Savannah River Company, Aiken, SC (USA))

1989-11-01T23:59:59.000Z

470

Guideline for the Treatment of Uncertainty in Risk-Informed Applications  

Science Conference Proceedings (OSTI)

In all scientific and engineering endeavors, there exists some level of uncertainty about the outcome. The development and application of a probabilistic risk assessment (PRA) is no exception. The uncertainty in the PRA model and its results manifests itself in several forms, including parametric, modeling, and completeness uncertainty. Various methods exist to both account for uncertainty in the model and evaluate the impact of uncertainty on the outcome of the analysis. However, these methods have gene...

2006-10-09T23:59:59.000Z

471

Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for deposited material and external doses. Volume 1: Main report  

SciTech Connect

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 deposited material and external dose models.

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

1997-12-01T23:59:59.000Z

472

Diabatically Driven Discrete Propagation of Surface Fronts: A Numerical Analysis  

Science Conference Proceedings (OSTI)

Discrete frontal propagation has been identified as a process whereby a surface front discontinuously moves forward, without evidence of frontal passage across a mesoscale region. Numerical simulations are employed to examine the upper-level ...

George H. Bryan; J. Michael Fritsch

2000-07-01T23:59:59.000Z

473

Propagation of Low-Mode Internal Waves through the Ocean  

Science Conference Proceedings (OSTI)

The baroclinic tides play a significant role in the energy budget of the abyssal ocean. Although the basic principles of generation and propagation are known, a clear understanding of these phenomena in the complex ocean environment is only now ...

Luc Rainville; Robert Pinkel

2006-06-01T23:59:59.000Z

474

Freely Propagating Trench Waves on a Beta-Plane  

Science Conference Proceedings (OSTI)

The dispersion relation is derived for trapped freely propagating barotropic long trench waves on a midlatitude ?-plane. It is found that a critical wavenumber kc, which depends on trench orientation and wave frequency, partitions the behavior of ...

Andrew J. Willmott; Arlene A. Bird

1983-09-01T23:59:59.000Z

475

Propagation of Kuroshio Extension Meanders between 143° and 149°E  

Science Conference Proceedings (OSTI)

A two-dimensional array of current- and pressure-recording inverted echo sounders provided synoptic measurements of the upper and deep fluctuations in the Kuroshio Extension between 143° and 149°E with mesoscale resolution. Downstream-propagating ...

Karen L. Tracey; D. Randolph Watts; Kathleen A. Donohue; Hiroshi Ichikawa

2012-04-01T23:59:59.000Z

476

Idealized Mesoscale Convective System Structure and Propagation Using Convective Parameterization  

Science Conference Proceedings (OSTI)

The development and propagation of mesoscale convective systems (MCSs) was examined within the Weather Research and Forecasting (WRF) model using the Kain–Fritsch (KF) cumulus parameterization scheme and a modified version of this scheme. ...

James Correia Jr.; Raymond W. Arritt; Christopher J. Anderson

2008-07-01T23:59:59.000Z

477

Metastability evaluation method by propagation delay distribution measurement  

Science Conference Proceedings (OSTI)

This paper suggests an experimental method for determining metastability properties based on deliberately inducing metastability in edge-triggered flip-flops. It offers the opportunity to analyze the impact of input signals time relationship on the output ... Keywords: MTBF, PLD, VLSI, analytical representation, asynchronous circuits, asynchronous logic, automatic data acquisition, complex architecture microsystems, custom CMOS, data acquisition, delays, edge-triggered flip-flops, failure analysis, fault diagnosis, fault events, flip-flop normal propagation delay, flip-flops, graphical representation, input signals time relationship, integrated circuit reliability, integrated propagation delay density distribution function, latch devices, logic design, logic testing, metastability, output signal timing characteristics, propagation delay density distribution function, propagation delay distribution measurement, reliability analysis, resolution time constant, statistical measurement

B. M. Rogina; B. Vojnovic

1995-11-01T23:59:59.000Z

478

The Influence of Propagating Waves on Cross-Stream Excursions  

Science Conference Proceedings (OSTI)

A kinematic model is developed to examine the relationship between meander propagation and Lagrangian pressure change within a meandering jet. Basically, the model equates changes in pressure along the path of a water parcel with the cross-stream ...

M. Susan Lozier; Timothy J. Bold; Amy S. Bower

1996-09-01T23:59:59.000Z

479

Horizontal and Vertical Structure of Cross-Equatorial Wave Propagation  

Science Conference Proceedings (OSTI)

Observational evidence of interhemispheric wave propagation through the equatorial upper-tropospheric mean westerlies in the eastern Pacific Ocean is found in nine years (1980/81 to 1988/89) of European Centre for Medium-Range Weather Forecasts ...

Robert A. Tomas; Peter J. Webster

1994-06-01T23:59:59.000Z

480

Operation-based update propagation in a mobile file system  

Science Conference Proceedings (OSTI)

In this paper we describe a technique called operation-based update propagation for efficiently transmitting updates to large files that have been modified on a weakly connected client of a distributed file system. In this technique, modifications are ...

Yui-Wah Lee; Kwong-Sak Leung; Mahadev Satyanarayanan

1999-06-01T23:59:59.000Z

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481

Multi-Layer network for influence propagation over microblog  

Science Conference Proceedings (OSTI)

Microblog has become ubiquitous for social networking and information sharing. A few studies on information propagation over microblog reveal that the majority of users like to publish and share the news on microblog. The public opinion over the internet ...

Chao Li; Jun Luo; Joshua Zhexue Huang; Jianping Fan

2012-05-01T23:59:59.000Z

482

Linear Spectral Numerical Model for Internal Gravity Wave Propagation  

Science Conference Proceedings (OSTI)

A three-dimensional linear spectral numerical model is proposed to simulate the propagation of internal gravity wave fluctuations in a stably stratified atmosphere. The model is developed to get first-order estimations of gravity wave ...

J. Marty; F. Dalaudier

2010-05-01T23:59:59.000Z

483

How Much Energy Propagates Vertically in the Equatorial Oceans?  

Science Conference Proceedings (OSTI)

Vertically propagating linear wave calculations using realistic equatorial buoyancy profiles are presented which show the percentage of the downward surface energy flux that reaches the deep equatorial oceans. The pe