Gradient-Enhanced Universal Kriging for Uncertainty Propagation...
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Gradient-Enhanced Universal Kriging for Uncertainty Propagation Citation Details In-Document Search Title: Gradient-Enhanced Universal Kriging for Uncertainty Propagation Authors: ...
Uncertainty Quantification and Propagation in Nuclear Density...
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theoretical tools used to study the properties of heavy and ... of model uncertainties and Bayesian inference methods. ... Country of Publication: United States Language: English ...
Uncertainty Quantification and Propagation in Nuclear Density Functional Theory
Schunck, N; McDonnell, J D; Higdon, D; Sarich, J; Wild, S M
2015-03-17
Nuclear density functional theory (DFT) is one of the main theoretical tools used to study the properties of heavy and superheavy elements, or to describe the structure of nuclei far from stability. While on-going eff orts seek to better root nuclear DFT in the theory of nuclear forces, energy functionals remain semi-phenomenological constructions that depend on a set of parameters adjusted to experimental data in fi nite nuclei. In this paper, we review recent eff orts to quantify the related uncertainties, and propagate them to model predictions. In particular, we cover the topics of parameter estimation for inverse problems, statistical analysis of model uncertainties and Bayesian inference methods. Illustrative examples are taken from the literature.
MONTE-CARLO BURNUP CALCULATION UNCERTAINTY QUANTIFICATION AND PROPAGATION DETERMINATION
Nichols, T.; Sternat, M.; Charlton, W.
2011-05-08
MONTEBURNS is a Monte-Carlo depletion routine utilizing MCNP and ORIGEN 2.2. Uncertainties exist in the MCNP transport calculation, but this information is not passed to the depletion calculation in ORIGEN or saved. To quantify this transport uncertainty and determine how it propagates between burnup steps, a statistical analysis of a multiple repeated depletion runs is performed. The reactor model chosen is the Oak Ridge Research Reactor (ORR) in a single assembly, infinite lattice configuration. This model was burned for a 25.5 day cycle broken down into three steps. The output isotopics as well as effective multiplication factor (k-effective) were tabulated and histograms were created at each burnup step using the Scott Method to determine the bin width. It was expected that the gram quantities and k-effective histograms would produce normally distributed results since they were produced from a Monte-Carlo routine, but some of results do not. The standard deviation at each burnup step was consistent between fission product isotopes as expected, while the uranium isotopes created some unique results. The variation in the quantity of uranium was small enough that, from the reaction rate MCNP tally, round off error occurred producing a set of repeated results with slight variation. Statistical analyses were performed using the {chi}{sup 2} test against a normal distribution for several isotopes and the k-effective results. While the isotopes failed to reject the null hypothesis of being normally distributed, the {chi}{sup 2} statistic grew through the steps in the k-effective test. The null hypothesis was rejected in the later steps. These results suggest, for a high accuracy solution, MCNP cell material quantities less than 100 grams and greater kcode parameters are needed to minimize uncertainty propagation and minimize round off effects.
TOTAL MEASUREMENT UNCERTAINTY IN HOLDUP MEASUREMENTS AT THE PLUTONIUM FINISHING PLANT (PFP)
KEELE, B.D.
2007-07-05
An approach to determine the total measurement uncertainty (TMU) associated with Generalized Geometry Holdup (GGH) [1,2,3] measurements was developed and implemented in 2004 and 2005 [4]. This paper describes a condensed version of the TMU calculational model, including recent developments. Recent modifications to the TMU calculation model include a change in the attenuation uncertainty, clarifying the definition of the forward background uncertainty, reducing conservatism in the random uncertainty by selecting either a propagation of counting statistics or the standard deviation of the mean, and considering uncertainty in the width and height as a part of the self attenuation uncertainty. In addition, a detection limit is calculated for point sources using equations derived from summary equations contained in Chapter 20 of MARLAP [5]. The Defense Nuclear Facilities Safety Board (DNFSB) Recommendation 2007-1 to the Secretary of Energy identified a lack of requirements and a lack of standardization for performing measurements across the U.S. Department of Energy (DOE) complex. The DNFSB also recommended that guidance be developed for a consistent application of uncertainty values. As such, the recent modifications to the TMU calculational model described in this paper have not yet been implemented. The Plutonium Finishing Plant (PFP) is continuing to perform uncertainty calculations as per Reference 4. Publication at this time is so that these concepts can be considered in developing a consensus methodology across the complex.
Díez, C.J.; Cabellos, O.; Martínez, J.S.
2015-01-15
Several approaches have been developed in last decades to tackle nuclear data uncertainty propagation problems of burn-up calculations. One approach proposed was the Hybrid Method, where uncertainties in nuclear data are propagated only on the depletion part of a burn-up problem. Because only depletion is addressed, only one-group cross sections are necessary, and hence, their collapsed one-group uncertainties. This approach has been applied successfully in several advanced reactor systems like EFIT (ADS-like reactor) or ESFR (Sodium fast reactor) to assess uncertainties on the isotopic composition. However, a comparison with using multi-group energy structures was not carried out, and has to be performed in order to analyse the limitations of using one-group uncertainties.
WESTSIK, G.A.
2001-06-06
This report presents the results of an evaluation of the Total Measurement Uncertainty (TMU) for the Canberra manufactured Segmented Gamma Scanner Assay System (SGSAS) as employed at the Hanford Plutonium Finishing Plant (PFP). In this document, TMU embodies the combined uncertainties due to all of the individual random and systematic sources of measurement uncertainty. It includes uncertainties arising from corrections and factors applied to the analysis of transuranic waste to compensate for inhomogeneities and interferences from the waste matrix and radioactive components. These include uncertainty components for any assumptions contained in the calibration of the system or computation of the data. Uncertainties are propagated at 1 sigma. The final total measurement uncertainty value is reported at the 95% confidence level. The SGSAS is a gamma assay system that is used to assay plutonium and uranium waste. The SGSAS system can be used in a stand-alone mode to perform the NDA characterization of a container, particularly for low to medium density (0-2.5 g/cc) container matrices. The SGSAS system provides a full gamma characterization of the container content. This document is an edited version of the Rocky Flats TMU Report for the Can Scan Segment Gamma Scanners, which are in use for the plutonium residues projects at the Rocky Flats plant. The can scan segmented gamma scanners at Rocky Flats are the same design as the PFP SGSAS system and use the same software (with the exception of the plutonium isotopics software). Therefore, all performance characteristics are expected to be similar. Modifications in this document reflect minor differences in the system configuration, container packaging, calibration technique, etc. These results are supported by the Quality Assurance Objective (QAO) counts, safeguards test data, calibration data, etc. for the PFP SGSAS system. Other parts of the TMU analysis utilize various modeling techniques such as Monte Carlo N
Thermal hydraulic limits analysis using statistical propagation of parametric uncertainties
Chiang, K. Y.; Hu, L. W.; Forget, B.
2012-07-01
The MIT Research Reactor (MITR) is evaluating the conversion from highly enriched uranium (HEU) to low enrichment uranium (LEU) fuel. In addition to the fuel element re-design, a reactor power upgraded from 6 MW to 7 MW is proposed in order to maintain the same reactor performance of the HEU core. Previous approach in analyzing the impact of engineering uncertainties on thermal hydraulic limits via the use of engineering hot channel factors (EHCFs) was unable to explicitly quantify the uncertainty and confidence level in reactor parameters. The objective of this study is to develop a methodology for MITR thermal hydraulic limits analysis by statistically combining engineering uncertainties with an aim to eliminate unnecessary conservatism inherent in traditional analyses. This method was employed to analyze the Limiting Safety System Settings (LSSS) for the MITR, which is the avoidance of the onset of nucleate boiling (ONB). Key parameters, such as coolant channel tolerances and heat transfer coefficients, were considered as normal distributions using Oracle Crystal Ball to calculate ONB. The LSSS power is determined with 99.7% confidence level. The LSSS power calculated using this new methodology is 9.1 MW, based on core outlet coolant temperature of 60 deg. C, and primary coolant flow rate of 1800 gpm, compared to 8.3 MW obtained from the analytical method using the EHCFs with same operating conditions. The same methodology was also used to calculate the safety limit (SL) for the MITR, conservatively determined using onset of flow instability (OFI) as the criterion, to verify that adequate safety margin exists between LSSS and SL. The calculated SL is 10.6 MW, which is 1.5 MW higher than LSSS. (authors)
A simplified analysis of uncertainty propagation in inherently controlled ATWS events
Wade, D.C.
1987-01-01
The quasi static approach can be used to provide useful insight concerning the propagation of uncertainties in the inherent response to ATWS events. At issue is how uncertainties in the reactivity coefficients and in the thermal-hydraulics and materials properties propagate to yield uncertainties in the asymptotic temperatures attained upon inherent shutdown. The basic notion to be quantified is that many of the same physical phenomena contribute to both the reactivity increase of power reduction and the reactivity decrease of core temperature rise. Since these reactivities cancel by definition, a good deal of uncertainty cancellation must also occur of necessity. For example, if the Doppler coefficient is overpredicted, too large a positive reactivity insertion is predicted upon power reduction and collapse of the ..delta..T across the fuel pin. However, too large a negative reactivity is also predicted upon the compensating increase in the isothermal core average temperature - which includes the fuel Doppler effect.
SU-E-J-159: Analysis of Total Imaging Uncertainty in Respiratory-Gated Radiotherapy
Suzuki, J; Okuda, T; Sakaino, S; Yokota, N
2015-06-15
Purpose: In respiratory-gated radiotherapy, the gating phase during treatment delivery needs to coincide with the corresponding phase determined during the treatment plan. However, because radiotherapy is performed based on the image obtained for the treatment plan, the time delay, motion artifact, volume effect, and resolution in the images are uncertain. Thus, imaging uncertainty is the most basic factor that affects the localization accuracy. Therefore, these uncertainties should be analyzed. This study aims to analyze the total imaging uncertainty in respiratory-gated radiotherapy. Methods: Two factors of imaging uncertainties related to respiratory-gated radiotherapy were analyzed. First, CT image was used to determine the target volume and 4D treatment planning for the Varian Realtime Position Management (RPM) system. Second, an X-ray image was acquired for image-guided radiotherapy (IGRT) for the BrainLAB ExacTrac system. These factors were measured using a respiratory gating phantom. The conditions applied during phantom operation were as follows: respiratory wave form, sine curve; respiratory cycle, 4 s; phantom target motion amplitude, 10, 20, and 29 mm (which is maximum phantom longitudinal motion). The target and cylindrical marker implanted in the phantom coverage of the CT images was measured and compared with the theoretically calculated coverage from the phantom motion. The theoretical position of the cylindrical marker implanted in the phantom was compared with that acquired from the X-ray image. The total imaging uncertainty was analyzed from these two factors. Results: In the CT image, the uncertainty between the target and cylindrical marker’s actual coverage and the coverage of CT images was 1.19 mm and 2.50mm, respectively. In the Xray image, the uncertainty was 0.39 mm. The total imaging uncertainty from the two factors was 1.62mm. Conclusion: The total imaging uncertainty in respiratory-gated radiotherapy was clinically acceptable. However
Propagation of Isotopic Bias and Uncertainty to Criticality Safety Analyses of PWR Waste Packages
Radulescu, Georgeta
2010-06-01
predicted spent fuel compositions (i.e., determine the penalty in reactivity due to isotopic composition bias and uncertainty) for use in disposal criticality analysis employing burnup credit. The method used in this calculation to propagate the isotopic bias and bias-uncertainty values to k{sub eff} is the Monte Carlo uncertainty sampling method. The development of this report is consistent with 'Test Plan for: Isotopic Validation for Postclosure Criticality of Commercial Spent Nuclear Fuel'. This calculation report has been developed in support of burnup credit activities for the proposed repository at Yucca Mountain, Nevada, and provides a methodology that can be applied to other criticality safety applications employing burnup credit.
CANTALOUB, M.G.
2002-01-02
The Waste Receiving and Processing (WRAP) facility, located on the Hanford Site in southeast Washington, is a key link in the certification of Hanford's transuranic (TRU) waste for shipment to the Waste Isolation Pilot Plant (WIPP). Waste characterization is one of the vital functions performed at WRAP, and nondestructive assay (NDA) measurement of TRU waste containers is one of the methods used for waste characterization. Various programs exist to ensure the validity of waste characterization data; all of these cite the need for clearly defied knowledge of the uncertainties associated with any measurements performed. All measurements have an inherent uncertainty associated with them The combined effect of all uncertainties associated with a measurement is referred to as the Total Measurement Uncertainty (TMU). The NDA measurement uncertainties can be numerous and complex. In addition to system-induced measurement uncertainty, other factors contribute to the TMU, each associated with a particular measurement. The NDA measurements at WRAP are based on processes (radioactive decay and induced fission) which are statistical in nature. As a result, the proper statistical summation of the various uncertainty components is essential. This report examines the contributing factors to NDA measurement uncertainty at WRAP. The significance of each factor to the TMU is analyzed, and a final method is given for determining the TMU for NDA measurements at WRAP. A brief description of the data flow paths for the analytical process is also included in this report. As more data becomes available, and WRAP gains in operational experience, this report will be reviewed semi-annually and updated as necessary.
The Multi-Step CADIS method for shutdown dose rate calculations and uncertainty propagation
Ibrahim, Ahmad M.; Peplow, Douglas E.; Grove, Robert E.; Peterson, Joshua L.; Johnson, Seth R.
2015-12-01
Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final SDDR. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. However, these simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate distribution of radioisotopes causing the SDDR. Biasing the neutron MC calculation using an importance function is not simple becausemore » it is difficult to explicitly express the response function, which depends on subsequent computational steps. Furthermore, the typical SDDR calculations do not consider how uncertainties in MC neutron calculation impact SDDR uncertainty, even though MC neutron calculation uncertainties usually dominate SDDR uncertainty.« less
The Multi-Step CADIS method for shutdown dose rate calculations and uncertainty propagation
Ibrahim, Ahmad M.; Peplow, Douglas E.; Grove, Robert E.; Peterson, Joshua L.; Johnson, Seth R.
2015-12-01
Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final SDDR. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. However, these simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate distribution of radioisotopes causing the SDDR. Biasing the neutron MC calculation using an importance function is not simple because it is difficult to explicitly express the response function, which depends on subsequent computational steps. Furthermore, the typical SDDR calculations do not consider how uncertainties in MC neutron calculation impact SDDR uncertainty, even though MC neutron calculation uncertainties usually dominate SDDR uncertainty.
Calibration and Forward Uncertainty Propagation for Large-eddy Simulations of Engineering Flows
Templeton, Jeremy Alan; Blaylock, Myra L.; Domino, Stefan P.; Hewson, John C.; Kumar, Pritvi Raj; Ling, Julia; Najm, Habib N.; Ruiz, Anthony; Safta, Cosmin; Sargsyan, Khachik; Stewart, Alessia; Wagner, Gregory
2015-09-01
The objective of this work is to investigate the efficacy of using calibration strategies from Uncertainty Quantification (UQ) to determine model coefficients for LES. As the target methods are for engineering LES, uncertainty from numerical aspects of the model must also be quantified. 15 The ultimate goal of this research thread is to generate a cost versus accuracy curve for LES such that the cost could be minimized given an accuracy prescribed by an engineering need. Realization of this goal would enable LES to serve as a predictive simulation tool within the engineering design process.
Error propagation equations for estimating the uncertainty in high-speed wind tunnel test results
Clark, E.L.
1994-07-01
Error propagation equations, based on the Taylor series model, are derived for the nondimensional ratios and coefficients most often encountered in high-speed wind tunnel testing. These include pressure ratio and coefficient, static force and moment coefficients, dynamic stability coefficients, and calibration Mach number. The error equations contain partial derivatives, denoted as sensitivity coefficients, which define the influence of free-steam Mach number, M{infinity}, on various aerodynamic ratios. To facilitate use of the error equations, sensitivity coefficients are derived and evaluated for five fundamental aerodynamic ratios which relate free-steam test conditions to a reference condition.
Helton, Jon Craig; Sallaberry, Cedric M.; Hansen, Clifford W.
2010-10-01
The 2008 performance assessment (PA) for the proposed repository for high-level radioactive waste at Yucca Mountain (YM), Nevada, illustrates the conceptual structure of risk assessments for complex systems. The 2008 YM PA is based on the following three conceptual entities: a probability space that characterizes aleatory uncertainty; a function that predicts consequences for individual elements of the sample space for aleatory uncertainty; and a probability space that characterizes epistemic uncertainty. These entities and their use in the characterization, propagation and analysis of aleatory and epistemic uncertainty are described and illustrated with results from the 2008 YM PA.
Gasoline and Diesel Fuel Update
Product: Total Crude Oil Liquefied Petroleum Gases PropanePropylene Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other ...
U.S. Energy Information Administration (EIA) (indexed site)
Product: Total Crude Oil Liquefied Petroleum Gases PropanePropylene Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel ...
Total..........................................................
U.S. Energy Information Administration (EIA) (indexed site)
0.9 Q Q Q Heat Pump......7.7 0.3 Q Q Steam or Hot Water System......Census Division Total West Energy Information Administration ...
Total..........................................................
U.S. Energy Information Administration (EIA) (indexed site)
0.9 Q Q Q Heat Pump......6.2 3.8 2.4 Steam or Hot Water System......Census Division Total Northeast Energy Information ...
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
Total..........................................................................
U.S. Energy Information Administration (EIA) (indexed site)
5.6 17.7 7.9 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.5 0.3 Q 500 to 999........................................................... 23.8 3.9 2.4 1.5 1,000 to 1,499..................................................... 20.8 4.4 3.2 1.2 1,500 to 1,999..................................................... 15.4 3.5 2.4 1.1 2,000 to 2,499..................................................... 12.2 3.2 2.1 1.1 2,500 to
Total..........................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Rising, M. E.; Prinja, A. K.
2012-07-01
A critical neutron transport problem with random material properties is introduced. The total cross section and the average neutron multiplicity are assumed to be uncertain, characterized by the mean and variance with a log-normal distribution. The average neutron multiplicity and the total cross section are assumed to be uncorrected and the material properties for differing materials are also assumed to be uncorrected. The principal component analysis method is used to decompose the covariance matrix into eigenvalues and eigenvectors and then 'realizations' of the material properties can be computed. A simple Monte Carlo brute force sampling of the decomposed covariance matrix is employed to obtain a benchmark result for each test problem. In order to save computational time and to characterize the moments and probability density function of the multiplication factor the polynomial chaos expansion method is employed along with the stochastic collocation method. A Gauss-Hermite quadrature set is convolved into a multidimensional tensor product quadrature set and is successfully used to compute the polynomial chaos expansion coefficients of the multiplication factor. Finally, for a particular critical fuel pin assembly the appropriate number of random variables and polynomial expansion order are investigated. (authors)
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
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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
Total...................................................................
U.S. Energy Information Administration (EIA) (indexed site)
Floorspace (Square Feet) Total Floorspace 1 Fewer than 500............................................ 3.2 0.4 Q 0.6 1.7 0.4 500 to 999................................................... 23.8 4.8 1.4 4.2 10.2 3.2 1,000 to 1,499............................................. 20.8 10.6 1.8 1.8 4.0 2.6 1,500 to 1,999............................................. 15.4 12.4 1.5 0.5 0.5 0.4 2,000 to 2,499............................................. 12.2 10.7 1.0 0.2 Q Q 2,500 to
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U.S. Energy Information Administration (EIA) (indexed site)
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
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U.S. Energy Information Administration (EIA) (indexed site)
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
Total..........................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
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U.S. Energy Information Administration (EIA) (indexed site)
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
Methodology for characterizing modeling and discretization uncertainties in computational simulation
ALVIN,KENNETH F.; OBERKAMPF,WILLIAM L.; RUTHERFORD,BRIAN M.; DIEGERT,KATHLEEN V.
2000-03-01
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.
Pomp, S.; Al-Adili, A.; Alhassan, E.; Gustavsson, C.; Helgesson, P.; Hellesen, C.; Koning, A.J.; Lantz, M.; Österlund, M.; Rochman, D.; Simutkin, V.; Sjöstrand, H.; Solders, A.
2015-01-15
We describe the research program of the nuclear reactions research group at Uppsala University concerning experimental and theoretical efforts to quantify and reduce nuclear data uncertainties relevant for the nuclear fuel cycle. We briefly describe the Total Monte Carlo (TMC) methodology and how it can be used to study fuel cycle and accident scenarios, and summarize our relevant experimental activities. Input from the latter is to be used to guide the nuclear models and constrain parameter space for TMC. The TMC method relies on the availability of good nuclear models. For this we use the TALYS code which is currently being extended to include the GEF model for the fission channel. We present results from TALYS-1.6 using different versions of GEF with both default and randomized input parameters and compare calculations with experimental data for {sup 234}U(n,f) in the fast energy range. These preliminary studies reveal some systematic differences between experimental data and calculations but give overall good and promising results.
Direct Aerosol Forcing Uncertainty
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
Mccomiskey, Allison
2008-01-15
Understanding sources of uncertainty in aerosol direct radiative forcing (DRF), the difference in a given radiative flux component with and without aerosol, is essential to quantifying changes in Earth's radiation budget. We examine the uncertainty in DRF due to measurement uncertainty in the quantities on which it depends: aerosol optical depth, single scattering albedo, asymmetry parameter, solar geometry, and surface albedo. Direct radiative forcing at the top of the atmosphere and at the surface as well as sensitivities, the changes in DRF in response to unit changes in individual aerosol or surface properties, are calculated at three locations representing distinct aerosol types and radiative environments. The uncertainty in DRF associated with a given property is computed as the product of the sensitivity and typical measurement uncertainty in the respective aerosol or surface property. Sensitivity and uncertainty values permit estimation of total uncertainty in calculated DRF and identification of properties that most limit accuracy in estimating forcing. Total uncertainties in modeled local diurnally averaged forcing range from 0.2 to 1.3 W m-2 (42 to 20%) depending on location (from tropical to polar sites), solar zenith angle, surface reflectance, aerosol type, and aerosol optical depth. The largest contributor to total uncertainty in DRF is usually single scattering albedo; however decreasing measurement uncertainties for any property would increase accuracy in DRF. Comparison of two radiative transfer models suggests the contribution of modeling error is small compared to the total uncertainty although comparable to uncertainty arising from some individual properties.
Efficient uncertainty propagation for network multiphysics systems...
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003691MLTPL00 Beam Propagator for Weather Radars, Modules 1 and 2 http://www.exelisvis.com/ProductsServices/IDL.aspx
Whitepaper on Uncertainty Quantification for MPACT
Williams, Mark L.
2015-12-17
The MPACT code provides the ability to perform high-fidelity deterministic calculations to obtain a wide variety of detailed results for very complex reactor core models. However MPACT currently does not have the capability to propagate the effects of input data uncertainties to provide uncertainties in the calculated results. This white paper discusses a potential method for MPACT uncertainty quantification (UQ) based on stochastic sampling.
Covariance propagation in spectral indices
Griffin, P. J.
2015-01-09
In this study, the dosimetry community has a history of using spectral indices to support neutron spectrum characterization and cross section validation efforts. An important aspect to this type of analysis is the proper consideration of the contribution of the spectrum uncertainty to the total uncertainty in calculated spectral indices (SIs). This study identifies deficiencies in the traditional treatment of the SI uncertainty, provides simple bounds to the spectral component in the SI uncertainty estimates, verifies that these estimates are reflected in actual applications, details a methodology that rigorously captures the spectral contribution to the uncertainty in the SI, andmore » provides quantified examples that demonstrate the importance of the proper treatment the spectral contribution to the uncertainty in the SI.« less
Covariance propagation in spectral indices
Griffin, P. J.
2015-01-09
In this study, the dosimetry community has a history of using spectral indices to support neutron spectrum characterization and cross section validation efforts. An important aspect to this type of analysis is the proper consideration of the contribution of the spectrum uncertainty to the total uncertainty in calculated spectral indices (SIs). This study identifies deficiencies in the traditional treatment of the SI uncertainty, provides simple bounds to the spectral component in the SI uncertainty estimates, verifies that these estimates are reflected in actual applications, details a methodology that rigorously captures the spectral contribution to the uncertainty in the SI, and provides quantified examples that demonstrate the importance of the proper treatment the spectral contribution to the uncertainty in the SI.
Yurko, J. P.; Buongiorno, J.
2012-07-01
Propagating parameter uncertainty for a nuclear reactor system code is a challenging problem due to often non-linear system response to the numerous parameters involved and lengthy computational times; issues that compound when a statistical sampling procedure is adopted, since the code must be run many times. The number of parameters sampled must therefore be limited to as few as possible that still accurately characterize the uncertainty in the system response. A Quantitative Phenomena Identification and Ranking Table (QPIRT) was developed to accomplish this goal. The QPIRT consists of two steps: a 'Top-Down' step focusing on identifying the dominant physical phenomena controlling the system response, and a 'Bottom-Up' step which focuses on determining the correlations from those key physical phenomena that significantly contribute to the response uncertainty. The Top-Down step evaluates phenomena using the governing equations of the system code at nominal parameter values, providing a 'fast' screening step. The Bottom-Up step then analyzes the correlations and models for the phenomena identified from the Top-Down step to find which parameters to sample. The QPIRT, through the Top-Down and Bottom-Up steps thus provides a systematic approach to determining the limited set of physically relevant parameters that influence the uncertainty of the system response. This strategy was demonstrated through an application to the RELAP5-based analysis of a PWR Total Loss of main Feedwater Flow (TLOFW) accident, also known as feed and bleed' scenario, . Ultimately, this work is the first component in a larger task of building a calibrated uncertainty propagation framework. The QPIRT is an essential piece because the uncertainty of those selected parameters will be calibrated to data from both Separate and Integral Effect Tests (SETs and IETs). Therefore the system response uncertainty will incorporate the knowledge gained from the database of past large IETs. (authors)
Experimental uncertainty estimation and statistics for data having interval uncertainty.
Kreinovich, Vladik; Oberkampf, William Louis; Ginzburg, Lev; Ferson, Scott; Hajagos, Janos
2007-05-01
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.
Monte Carlo Solution for Uncertainty Propagation in Particle...
Office of Scientific and Technical Information (OSTI)
the International Conference on Math. and Comp. Methods Applied to Nucl. Sci. and Engg. (M&C 2013) held May 5-9, 2013 in Sun Valley, ID. Research Org: Sandia National Laboratories
Gradient-Enhanced Universal Kriging for Uncertainty Propagation...
Office of Scientific and Technical Information (OSTI)
OSTI Identifier: 1110487 Report Number(s): ANLMCSJA-71590 Journal ID: ISSN 0029-5639 DOE Contract Number: DE-AC02-06CH11357 Resource Type: Journal Article Resource Relation: ...
Sensitivity and Uncertainty Analysis
Summary Notes from 15 November 2007 Generic Technical Issue Discussion on Sensitivity and Uncertainty Analysis and Model Support
RUMINATIONS ON NDA MEASUREMENT UNCERTAINTY COMPARED TO DA UNCERTAINTY
Salaymeh, S.; Ashley, W.; Jeffcoat, R.
2010-06-17
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.
Zettlemoyer, M.D.
1990-01-01
The Air Force Toxic Chemical Dispersion (AFTOX) model is a Gaussian puff dispersion model that predicts plumes, concentrations, and hazard distances of toxic chemical spills. A measurement uncertainty propagation formula derived by Freeman et al. (1986) is used within AFTOX to estimate resulting concentration uncertainties due to the effects of data input uncertainties in wind speed, spill height, emission rate, and the horizontal and vertical Gaussian dispersion parameters, and the results are compared to true uncertainties as estimated by standard deviations computed by Monte Carlo simulations. The measurement uncertainty uncertainty propagation formula was found to overestimate measurement uncertainty in AFTOX-calculated concentrations by at least 350 percent, with overestimates worsening with increasing stability and/or increasing measurement uncertainty.
Uncertainty Analysis for Photovoltaic Degradation Rates (Poster)
Jordan, D.; Kurtz, S.; Hansen, C.
2014-04-01
Dependable and predictable energy production is the key to the long-term success of the PV industry. PV systems show over the lifetime of their exposure a gradual decline that depends on many different factors such as module technology, module type, mounting configuration, climate etc. When degradation rates are determined from continuous data the statistical uncertainty is easily calculated from the regression coefficients. However, total uncertainty that includes measurement uncertainty and instrumentation drift is far more difficult to determine. A Monte Carlo simulation approach was chosen to investigate a comprehensive uncertainty analysis. The most important effect for degradation rates is to avoid instrumentation that changes over time in the field. For instance, a drifting irradiance sensor, which can be achieved through regular calibration, can lead to a substantially erroneous degradation rates. However, the accuracy of the irradiance sensor has negligible impact on degradation rate uncertainty emphasizing that precision (relative accuracy) is more important than absolute accuracy.
U.S. Department of Energy (DOE) all webpages (Extended Search)
Climate Uncertainty The uncertainty in climate change and in its impacts is of great concern to the international community. While the ever-growing body of scientific evidence substantiates present climate change, the driving concern about this issue lies in the consequences it poses to humanity. Policy makers will most likely need to make decisions about climate policy before climate scientists have quantified all relevant uncertainties about the impacts of climate change. Sandia scientists
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 & < Imports -
Uncertainty Quantification of Composite Laminate Damage with the Generalized Information Theory
J. Lucero; F. Hemez; T. Ross; K.Kline; J.Hundhausen; T. Tippetts
2006-05-01
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
Physical Uncertainty Bounds (PUB)
Vaughan, Diane Elizabeth; Preston, Dean L.
2015-03-19
This paper introduces and motivates the need for a new methodology for determining upper bounds on the uncertainties in simulations of engineered systems due to limited fidelity in the composite continuum-level physics models needed to simulate the systems. We show that traditional uncertainty quantification methods provide, at best, a lower bound on this uncertainty. We propose to obtain bounds on the simulation uncertainties by first determining bounds on the physical quantities or processes relevant to system performance. By bounding these physics processes, as opposed to carrying out statistical analyses of the parameter sets of specific physics models or simply switching out the available physics models, one can obtain upper bounds on the uncertainties in simulated quantities of interest.
Photovoltaic System Modeling. Uncertainty and Sensitivity Analyses
Hansen, Clifford W.; Martin, Curtis E.
2015-08-01
We report an uncertainty and sensitivity analysis for modeling AC energy from ph otovoltaic systems . Output from a PV system is predicted by a sequence of models. We quantify u ncertainty i n the output of each model using empirical distribution s of each model's residuals. We propagate uncertainty through the sequence of models by sampli ng these distributions to obtain a n empirical distribution of a PV system's output. We consider models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane - of - array irradiance; (2) estimate effective irradiance; (3) predict cell temperature; (4) estimate DC voltage, current and power ; (5) reduce DC power for losses due to inefficient maximum power point tracking or mismatch among modules; and (6) convert DC to AC power . O ur analysis consider s a notional PV system com prising an array of FirstSolar FS - 387 modules and a 250 kW AC inverter ; we use measured irradiance and weather at Albuquerque, NM. We found the uncertainty in PV syste m output to be relatively small, on the order of 1% for daily energy. We found that unce rtainty in the models for POA irradiance and effective irradiance to be the dominant contributors to uncertainty in predicted daily energy. Our analysis indicates that efforts to reduce the uncertainty in PV system output predictions may yield the greatest improvements by focusing on the POA and effective irradiance models.
U.S. Energy Information Administration (EIA) (indexed site)
Country Total Percent of U.S. total Canada 61,078 1% China 3,323,297 57% Germany 154,800 3% Japan 12,593 0% India 47,192 1% South Korea 251,105 4% All Others 2,008,612 34% Total 5,858,677 100% Table 7 . Photovoltaic module import shipments by country, 2014 (peak kilowatts) Note: All Others includes Cambodia, Czech Republic, Hong Kong, Malaysia, Mexico, Netherlands, Philippines, Singapore, Taiwan and Turkey Source: U.S. Energy Information Administration, Form EIA-63B, 'Annual Photovoltaic
Energy Science and Technology Software Center (OSTI)
2007-01-08
WPP is a massively parallel, 3D, C++, finite-difference elastodynamic wave propagation code. Typical applications for wave propagation with WPP include: evaluation of seismic event scenarios and damage from earthquakes, non-destructive evaluation of materials, underground facility detection, oil and gas exploration, predicting the electro-magnetic fields in accelerators, and acoustic noise generation. For more information, see Users Manual [1].
U.S. Energy Information Administration (EIA) (indexed site)
State Total Percent of U.S. total Alabama 482 0.0% Alaska 81 0.0% Arizona 194,476 3.3% Arkansas 336 0.0% California 3,163,120 53.0% Colorado 47,240 0.8% Connecticut 50,745 0.9% Delaware 6,600 0.1% District of Columbia 751 0.0% Florida 18,593 0.3% Georgia 47,660 0.8% Hawaii 78,329 1.3% Illinois 5,795 0.1% Indiana 37,016 0.6% Iowa 14,281 0.2% Kansas 1,809 0.0% Kentucky 520 0.0% Louisiana 12,147 0.2% Maine 1,296 0.0% Maryland 63,077 1.1% Massachusetts 157,415 2.6% Michigan 4,210 0.1% Minnesota
Fuzzy-probabilistic calculations of water-balance uncertainty
Faybishenko, B.
2009-10-01
Hydrogeological systems are often characterized by imprecise, vague, inconsistent, incomplete, or subjective information, which may limit the application of conventional stochastic methods in predicting hydrogeologic conditions and associated uncertainty. Instead, redictions and uncertainty analysis can be made using uncertain input parameters expressed as probability boxes, intervals, and fuzzy numbers. The objective of this paper is to present the theory for, and a case study as an application of, the fuzzyprobabilistic approach, ombining probability and possibility theory for simulating soil water balance and assessing associated uncertainty in the components of a simple waterbalance equation. The application of this approach is demonstrated using calculations with the RAMAS Risk Calc code, to ssess the propagation of uncertainty in calculating potential evapotranspiration, actual evapotranspiration, and infiltration-in a case study at the Hanford site, Washington, USA. Propagation of uncertainty into the results of water-balance calculations was evaluated by hanging he types of models of uncertainty incorporated into various input parameters. The results of these fuzzy-probabilistic calculations are compared to the conventional Monte Carlo simulation approach and estimates from field observations at the Hanford site.
Measurement uncertainty relations
Busch, Paul; Lahti, Pekka; Werner, Reinhard F.
2014-04-15
Measurement uncertainty relations are quantitative bounds on the errors in an approximate joint measurement of two observables. They can be seen as a generalization of the error/disturbance tradeoff first discussed heuristically by Heisenberg. Here we prove such relations for the case of two canonically conjugate observables like position and momentum, and establish a close connection with the more familiar preparation uncertainty relations constraining the sharpness of the distributions of the two observables in the same state. Both sets of relations are generalized to means of order ? rather than the usual quadratic means, and we show that the optimal constants are the same for preparation and for measurement uncertainty. The constants are determined numerically and compared with some bounds in the literature. In both cases, the near-saturation of the inequalities entails that the state (resp. observable) is uniformly close to a minimizing one.
Strategies for Application of Isotopic Uncertainties in Burnup Credit
Gauld, I.C.
2002-12-23
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
Turinsky, Paul J; Abdel-Khalik, Hany S; Stover, Tracy E
2011-03-31
An optimization technique has been developed to select optimized experimental design specifications to produce data specifically designed to be assimilated to optimize a given reactor concept. Data from the optimized experiment is assimilated to generate posteriori uncertainties on the reactor concept’s core attributes from which the design responses are computed. The reactor concept is then optimized with the new data to realize cost savings by reducing margin. The optimization problem iterates until an optimal experiment is found to maximize the savings. A new generation of innovative nuclear reactor designs, in particular fast neutron spectrum recycle reactors, are being considered for the application of closing the nuclear fuel cycle in the future. Safe and economical design of these reactors will require uncertainty reduction in basic nuclear data which are input to the reactor design. These data uncertainty propagate to design responses which in turn require the reactor designer to incorporate additional safety margin into the design, which often increases the cost of the reactor. Therefore basic nuclear data needs to be improved and this is accomplished through experimentation. Considering the high cost of nuclear experiments, it is desired to have an optimized experiment which will provide the data needed for uncertainty reduction such that a reactor design concept can meet its target accuracies or to allow savings to be realized by reducing the margin required due to uncertainty propagated from basic nuclear data. However, this optimization is coupled to the reactor design itself because with improved data the reactor concept can be re-optimized itself. It is thus desired to find the experiment that gives the best optimized reactor design. Methods are first established to model both the reactor concept and the experiment and to efficiently propagate the basic nuclear data uncertainty through these models to outputs. The representativity of the experiment
Uncertainty quantification in fission cross section measurements at LANSCE
Tovesson, F.
2015-01-09
Neutron-induced fission cross sections have been measured for several isotopes of uranium and plutonium at the Los Alamos Neutron Science Center (LANSCE) over a wide range of incident neutron energies. The total uncertainties in these measurements are in the range 3–5% above 100 keV of incident neutron energy, which results from uncertainties in the target, neutron source, and detector system. The individual sources of uncertainties are assumed to be uncorrelated, however correlation in the cross section across neutron energy bins are considered. The quantification of the uncertainty contributions will be described here.
Extended Forward Sensitivity Analysis for Uncertainty Quantification
Haihua Zhao; Vincent A. Mousseau
2011-09-01
Verification and validation (V&V) are playing more important roles to quantify uncertainties and realize high fidelity simulations in engineering system analyses, such as transients happened in a complex nuclear reactor system. Traditional V&V in the reactor system analysis focused more on the validation part or did not differentiate verification and validation. The traditional approach to uncertainty quantification is based on a 'black box' approach. The simulation tool is treated as an unknown signal generator, a distribution of inputs according to assumed probability density functions is sent in and the distribution of the outputs is measured and correlated back to the original input distribution. The 'black box' method mixes numerical errors with all other uncertainties. It is also not efficient to perform sensitivity analysis. Contrary to the 'black box' method, a more efficient sensitivity approach can take advantage of intimate knowledge of the simulation code. In these types of approaches equations for the propagation of uncertainty are constructed and the sensitivities are directly solved for as variables in the simulation. This paper presents the forward sensitivity analysis as a method to help uncertainty qualification. By including time step and potentially spatial step as special sensitivity parameters, the forward sensitivity method is extended as one method to quantify numerical errors. Note that by integrating local truncation errors over the whole system through the forward sensitivity analysis process, the generated time step and spatial step sensitivity information reflect global numerical errors. The discretization errors can be systematically compared against uncertainties due to other physical parameters. This extension makes the forward sensitivity method a much more powerful tool to help uncertainty qualification. By knowing the relative sensitivity of time and space steps with other interested physical parameters, the simulation is allowed
Calibration Under Uncertainty.
Swiler, Laura Painton; Trucano, Timothy Guy
2005-03-01
This report is a white paper summarizing the literature and different approaches to the problem of calibrating computer model parameters in the face of model uncertainty. Model calibration is often formulated as finding the parameters that minimize the squared difference between the model-computed data (the predicted data) and the actual experimental data. This approach does not allow for explicit treatment of uncertainty or error in the model itself: the model is considered the %22true%22 deterministic representation of reality. While this approach does have utility, it is far from an accurate mathematical treatment of the true model calibration problem in which both the computed data and experimental data have error bars. This year, we examined methods to perform calibration accounting for the error in both the computer model and the data, as well as improving our understanding of its meaning for model predictability. We call this approach Calibration under Uncertainty (CUU). This talk presents our current thinking on CUU. We outline some current approaches in the literature, and discuss the Bayesian approach to CUU in detail.
Sun, Y.; Tong, C.; Trainor-Guitten, W. J.; Lu, C.; Mansoor, K.; Carroll, S. A.
2012-12-20
The risk of CO2 leakage from a deep storage reservoir into a shallow aquifer through a fault is assessed and studied using physics-specific computer models. The hypothetical CO2 geological sequestration system is composed of three subsystems: a deep storage reservoir, a fault in caprock, and a shallow aquifer, which are modeled respectively by considering sub-domain-specific physics. Supercritical CO2 is injected into the reservoir subsystem with uncertain permeabilities of reservoir, caprock, and aquifer, uncertain fault location, and injection rate (as a decision variable). The simulated pressure and CO2/brine saturation are connected to the fault-leakage model as a boundary condition. CO2 andmore » brine fluxes from the fault-leakage model at the fault outlet are then imposed in the aquifer model as a source term. Moreover, uncertainties are propagated from the deep reservoir model, to the fault-leakage model, and eventually to the geochemical model in the shallow aquifer, thus contributing to risk profiles. To quantify the uncertainties and assess leakage-relevant risk, we propose a global sampling-based method to allocate sub-dimensions of uncertain parameters to sub-models. The risk profiles are defined and related to CO2 plume development for pH value and total dissolved solids (TDS) below the EPA's Maximum Contaminant Levels (MCL) for drinking water quality. A global sensitivity analysis is conducted to select the most sensitive parameters to the risk profiles. The resulting uncertainty of pH- and TDS-defined aquifer volume, which is impacted by CO2 and brine leakage, mainly results from the uncertainty of fault permeability. Subsequently, high-resolution, reduced-order models of risk profiles are developed as functions of all the decision variables and uncertain parameters in all three subsystems.« less
Harper, F.T.; Young, M.L.; Miller, L.A.; Hora, S.C.; Lui, C.H.; Goossens, L.H.J.; Cooke, R.M.; Paesler-Sauer, J.; Helton, J.C.
1995-01-01
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.
Entropic uncertainty relations and entanglement
Guehne, Otfried; Lewenstein, Maciej
2004-08-01
We discuss the relationship between entropic uncertainty relations and entanglement. We present two methods for deriving separability criteria in terms of entropic uncertainty relations. In particular, we show how any entropic uncertainty relation on one part of the system results in a separability condition on the composite system. We investigate the resulting criteria using the Tsallis entropy for two and three qubits.
ENHANCED UNCERTAINTY ANALYSIS FOR SRS COMPOSITE ANALYSIS
Smith, F.; Phifer, M.
2011-06-30
The Composite Analysis (CA) performed for the Savannah River Site (SRS) in 2009 (SRS CA 2009) included a simplified uncertainty analysis. The uncertainty analysis in the CA (Smith et al. 2009b) was limited to considering at most five sources in a separate uncertainty calculation performed for each POA. To perform the uncertainty calculations in a reasonable amount of time, the analysis was limited to using 400 realizations, 2,000 years of simulated transport time, and the time steps used for the uncertainty analysis were increased from what was used in the CA base case analysis. As part of the CA maintenance plan, the Savannah River National Laboratory (SRNL) committed to improving the CA uncertainty/sensitivity analysis. The previous uncertainty analysis was constrained by the standard GoldSim licensing which limits the user to running at most four Monte Carlo uncertainty calculations (also called realizations) simultaneously. Some of the limitations on the number of realizations that could be practically run and the simulation time steps were removed by building a cluster of three HP Proliant windows servers with a total of 36 64-bit processors and by licensing the GoldSim DP-Plus distributed processing software. This allowed running as many as 35 realizations simultaneously (one processor is reserved as a master process that controls running the realizations). These enhancements to SRNL computing capabilities made uncertainty analysis: using 1000 realizations, using the time steps employed in the base case CA calculations, with more sources, and simulating radionuclide transport for 10,000 years feasible. In addition, an importance screening analysis was performed to identify the class of stochastic variables that have the most significant impact on model uncertainty. This analysis ran the uncertainty model separately testing the response to variations in the following five sets of model parameters: (a) K{sub d} values (72 parameters for the 36 CA elements in
Geostatistical evaluation of travel time uncertainties
Devary, J.L.
1983-08-01
Data on potentiometric head and hydraulic conductivity, gathered from the Wolfcamp Formation of the Permian System, have exhibited tremendous spatial variability as a result of heterogeneities in the media and the presence of petroleum and natural gas deposits. Geostatistical data analysis and error propagation techniques (kriging and conditional simulation) were applied to determine the effect of potentiometric head uncertainties on radionuclide travel paths and travel times through the Wolfcamp Formation. Blok-average kriging was utilized to remove measurement error from potentiometric head data. The travel time calculations have been enhanced by the use of an inverse technique to determine the relative hydraulic conductivity along travel paths. In this way, the spatial variability of the hydraulic conductivity corresponding to streamline convergence and divergence may be included in the analysis. 22 references, 11 figures, 1 table.
Uncertainty quantification and multiscale mathematics. (Conference...
Office of Scientific and Technical Information (OSTI)
Uncertainty quantification and multiscale mathematics. Citation Details In-Document Search Title: Uncertainty quantification and multiscale mathematics. No abstract prepared. ...
Johnson, J. D.; Oberkampf, William Louis; Helton, Jon Craig (Arizona State University, Tempe, AZ); Storlie, Curtis B. (North Carolina State University, Raleigh, NC)
2006-10-01
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.
Practical uncertainty reduction and quantification in shock physics measurements
Akin, M. C.; Nguyen, J. H.
2015-04-20
We report the development of a simple error analysis sampling method for identifying intersections and inflection points to reduce total uncertainty in experimental data. This technique was used to reduce uncertainties in sound speed measurements by 80% over conventional methods. Here, we focused on its impact on a previously published set of Mo sound speed data and possible implications for phase transition and geophysical studies. However, this technique's application can be extended to a wide range of experimental data.
Uncertainty in Integrated Assessment Scenarios
Mort Webster
2005-10-17
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
Harper, F.T.; Young, M.L.; Miller, L.A.; Hora, S.C.; Lui, C.H.; Goossens, L.H.J.; Cooke, R.M.; Paesler-Sauer, J.; Helton, J.C.
1995-01-01
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 second of a three-volume document describing the project and contains two appendices describing the rationales for the dispersion and deposition data along with short biographies of the 16 experts who participated in the project.
Reconstruction of nonlinear wave propagation
Fleischer, Jason W; Barsi, Christopher; Wan, Wenjie
2013-04-23
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.
Uncertainty and sensitivity analysis for photovoltaic system modeling.
Hansen, Clifford W.; Pohl, Andrew Phillip; Jordan, Dirk
2013-12-01
We report an uncertainty and sensitivity analysis for modeling DC energy from photovoltaic systems. We consider two systems, each comprised of a single module using either crystalline silicon or CdTe cells, and located either at Albuquerque, NM, or Golden, CO. Output from a PV system is predicted by a sequence of models. Uncertainty in the output of each model is quantified by empirical distributions of each model's residuals. We sample these distributions to propagate uncertainty through the sequence of models to obtain an empirical distribution for each PV system's output. We considered models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane-of-array irradiance; (2) estimate effective irradiance from plane-of-array irradiance; (3) predict cell temperature; and (4) estimate DC voltage, current and power. We found that the uncertainty in PV system output to be relatively small, on the order of 1% for daily energy. Four alternative models were considered for the POA irradiance modeling step; we did not find the choice of one of these models to be of great significance. However, we observed that the POA irradiance model introduced a bias of upwards of 5% of daily energy which translates directly to a systematic difference in predicted energy. Sensitivity analyses relate uncertainty in the PV system output to uncertainty arising from each model. We found that the residuals arising from the POA irradiance and the effective irradiance models to be the dominant contributors to residuals for daily energy, for either technology or location considered. This analysis indicates that efforts to reduce the uncertainty in PV system output should focus on improvements to the POA and effective irradiance models.
Sun, Y.; Tong, C.; Trainor-Guitten, W. J.; Lu, C.; Mansoor, K.; Carroll, S. A.
2012-12-20
The risk of CO_{2} leakage from a deep storage reservoir into a shallow aquifer through a fault is assessed and studied using physics-specific computer models. The hypothetical CO_{2} geological sequestration system is composed of three subsystems: a deep storage reservoir, a fault in caprock, and a shallow aquifer, which are modeled respectively by considering sub-domain-specific physics. Supercritical CO_{2} is injected into the reservoir subsystem with uncertain permeabilities of reservoir, caprock, and aquifer, uncertain fault location, and injection rate (as a decision variable). The simulated pressure and CO_{2}/brine saturation are connected to the fault-leakage model as a boundary condition. CO_{2} and brine fluxes from the fault-leakage model at the fault outlet are then imposed in the aquifer model as a source term. Moreover, uncertainties are propagated from the deep reservoir model, to the fault-leakage model, and eventually to the geochemical model in the shallow aquifer, thus contributing to risk profiles. To quantify the uncertainties and assess leakage-relevant risk, we propose a global sampling-based method to allocate sub-dimensions of uncertain parameters to sub-models. The risk profiles are defined and related to CO_{2} plume development for pH value and total dissolved solids (TDS) below the EPA's Maximum Contaminant Levels (MCL) for drinking water quality. A global sensitivity analysis is conducted to select the most sensitive parameters to the risk profiles. The resulting uncertainty of pH- and TDS-defined aquifer volume, which is impacted by CO_{2} and brine leakage, mainly results from the uncertainty of fault permeability. Subsequently, high-resolution, reduced-order models of risk profiles are developed as functions of all the decision variables and uncertain parameters in all three subsystems.
Semiclassical propagation of Wigner functions
Dittrich, T.; Gomez, E. A.; Pachon, L. A.
2010-06-07
We present a comprehensive study of semiclassical phase-space propagation in the Wigner representation, emphasizing numerical applications, in particular as an initial-value representation. Two semiclassical approximation schemes are discussed. The propagator of the Wigner function based on van Vleck's approximation replaces the Liouville propagator by a quantum spot with an oscillatory pattern reflecting the interference between pairs of classical trajectories. Employing phase-space path integration instead, caustics in the quantum spot are resolved in terms of Airy functions. We apply both to two benchmark models of nonlinear molecular potentials, the Morse oscillator and the quartic double well, to test them in standard tasks such as computing autocorrelation functions and propagating coherent states. The performance of semiclassical Wigner propagation is very good even in the presence of marked quantum effects, e.g., in coherent tunneling and in propagating Schroedinger cat states, and of classical chaos in four-dimensional phase space. We suggest options for an effective numerical implementation of our method and for integrating it in Monte-Carlo-Metropolis algorithms suitable for high-dimensional systems.
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...
Reducing Petroleum Despendence in California: Uncertainties About...
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
Petroleum Despendence in California: Uncertainties About Light-Duty Diesel Reducing Petroleum Despendence in California: Uncertainties About Light-Duty Diesel 2002 DEER Conference ...
Uncertainty Analysis Technique for OMEGA Dante Measurements ...
Office of Scientific and Technical Information (OSTI)
Uncertainty Analysis Technique for OMEGA Dante Measurements Citation Details In-Document Search Title: Uncertainty Analysis Technique for OMEGA Dante Measurements You are...
Report: Technical Uncertainty and Risk Reduction
Office of Environmental Management (EM)
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 ...
TRITIUM UNCERTAINTY ANALYSIS FOR SURFACE WATER SAMPLES AT THE SAVANNAH RIVER SITE
Atkinson, R.
2012-07-31
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.
A Probabilistic Framework for Quantifying Mixed Uncertainties in Cyber Attacker Payoffs
Chatterjee, Samrat; Tipireddy, Ramakrishna; Oster, Matthew R.; Halappanavar, Mahantesh
2015-12-28
Quantification and propagation of uncertainties in cyber attacker payoffs is a key aspect within multiplayer, stochastic security games. These payoffs may represent penalties or rewards associated with player actions and are subject to various sources of uncertainty, including: (1) cyber-system state, (2) attacker type, (3) choice of player actions, and (4) cyber-system state transitions over time. Past research has primarily focused on representing defender beliefs about attacker payoffs as point utility estimates. More recently, within the physical security domain, attacker payoff uncertainties have been represented as Uniform and Gaussian probability distributions, and mathematical intervals. For cyber-systems, probability distributions may help address statistical (aleatory) uncertainties where the defender may assume inherent variability or randomness in the factors contributing to the attacker payoffs. However, systematic (epistemic) uncertainties may exist, where the defender may not have sufficient knowledge or there is insufficient information about the attackers payoff generation mechanism. Such epistemic uncertainties are more suitably represented as generalizations of probability boxes. This paper explores the mathematical treatment of such mixed payoff uncertainties. A conditional probabilistic reasoning approach is adopted to organize the dependencies between a cyber-systems state, attacker type, player actions, and state transitions. This also enables the application of probabilistic theories to propagate various uncertainties in the attacker payoffs. An example implementation of this probabilistic framework and resulting attacker payoff distributions are discussed. A goal of this paper is also to highlight this uncertainty quantification problem space to the cyber security research community and encourage further advancements in this area.
,"Total Natural Gas Consumption
U.S. Energy Information Administration (EIA) (indexed site)
Gas Consumption (billion cubic feet)",,,,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...
Statistics, Uncertainty, and Transmitted Variation
Wendelberger, Joanne Roth
2014-11-05
The field of Statistics provides methods for modeling and understanding data and making decisions in the presence of uncertainty. When examining response functions, variation present in the input variables will be transmitted via the response function to the output variables. This phenomenon can potentially have significant impacts on the uncertainty associated with results from subsequent analysis. This presentation will examine the concept of transmitted variation, its impact on designed experiments, and a method for identifying and estimating sources of transmitted variation in certain settings.
Nguyen, J.; Moteabbed, M.; Paganetti, H.
2015-01-15
Purpose: Theoretical dose–response models offer the possibility to assess second cancer induction risks after external beam therapy. The parameters used in these models are determined with limited data from epidemiological studies. Risk estimations are thus associated with considerable uncertainties. This study aims at illustrating uncertainties when predicting the risk for organ-specific second cancers in the primary radiation field illustrated by choosing selected treatment plans for brain cancer patients. Methods: A widely used risk model was considered in this study. The uncertainties of the model parameters were estimated with reported data of second cancer incidences for various organs. Standard error propagation was then subsequently applied to assess the uncertainty in the risk model. Next, second cancer risks of five pediatric patients treated for cancer in the head and neck regions were calculated. For each case, treatment plans for proton and photon therapy were designed to estimate the uncertainties (a) in the lifetime attributable risk (LAR) for a given treatment modality and (b) when comparing risks of two different treatment modalities. Results: Uncertainties in excess of 100% of the risk were found for almost all organs considered. When applied to treatment plans, the calculated LAR values have uncertainties of the same magnitude. A comparison between cancer risks of different treatment modalities, however, does allow statistically significant conclusions. In the studied cases, the patient averaged LAR ratio of proton and photon treatments was 0.35, 0.56, and 0.59 for brain carcinoma, brain sarcoma, and bone sarcoma, respectively. Their corresponding uncertainties were estimated to be potentially below 5%, depending on uncertainties in dosimetry. Conclusions: The uncertainty in the dose–response curve in cancer risk models makes it currently impractical to predict the risk for an individual external beam treatment. On the other hand, the ratio
IAEA CRP on HTGR Uncertainty Analysis: Benchmark Definition and Test Cases
Gerhard Strydom; Frederik Reitsma; Hans Gougar; Bismark Tyobeka; Kostadin Ivanov
2012-11-01
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.
WE-B-19A-01: SRT II: Uncertainties in SRT
Dieterich, S; Schlesinger, D; Geneser, S
2014-06-15
SRS delivery has undergone major technical changes in the last decade, transitioning from predominantly frame-based treatment delivery to imageguided, frameless SRS. It is important for medical physicists working in SRS to understand the magnitude and sources of uncertainty involved in delivering SRS treatments for a multitude of technologies (Gamma Knife, CyberKnife, linac-based SRS and protons). Sources of SRS planning and delivery uncertainty include dose calculation, dose fusion, and intra- and inter-fraction motion. Dose calculations for small fields are particularly difficult because of the lack of electronic equilibrium and greater effect of inhomogeneities within and near the PTV. Going frameless introduces greater setup uncertainties that allows for potentially increased intra- and interfraction motion, The increased use of multiple imaging modalities to determine the tumor volume, necessitates (deformable) image and contour fusion, and the resulting uncertainties introduced in the image registration process further contribute to overall treatment planning uncertainties. Each of these uncertainties must be quantified and their impact on treatment delivery accuracy understood. If necessary, the uncertainties may then be accounted for during treatment planning either through techniques to make the uncertainty explicit, or by the appropriate addition of PTV margins. Further complicating matters, the statistics of 1-5 fraction SRS treatments differ from traditional margin recipes relying on Poisson statistics. In this session, we will discuss uncertainties introduced during each step of the SRS treatment planning and delivery process and present margin recipes to appropriately account for such uncertainties. Learning Objectives: To understand the major contributors to the total delivery uncertainty in SRS for Gamma Knife, CyberKnife, and linac-based SRS. Learn the various uncertainties introduced by image fusion, deformable image registration, and contouring
A Two-Step Approach to Uncertainty Quantification of Core Simulators
Yankov, Artem; Collins, Benjamin; Klein, Markus; Jessee, Matthew A.; Zwermann, Winfried; Velkov, Kiril; Pautz, Andreas; Downar, Thomas
2012-01-01
For the multiple sources of error introduced into the standard computational regime for simulating reactor cores, rigorous uncertainty analysis methods are available primarily to quantify the effects of cross section uncertainties. Two methods for propagating cross section uncertainties through core simulators are the XSUSA statistical approach and the “two-step” method. The XSUSA approach, which is based on the SUSA code package, is fundamentally a stochastic sampling method. Alternatively, the two-step method utilizes generalized perturbation theory in the first step and stochastic sampling in the second step. The consistency of these two methods in quantifying uncertainties in the multiplication factor andmore » in the core power distribution was examined in the framework of phase I-3 of the OECD Uncertainty Analysis in Modeling benchmark. With the Three Mile Island Unit 1 core as a base model for analysis, the XSUSA and two-step methods were applied with certain limitations, and the results were compared to those produced by other stochastic sampling-based codes. Based on the uncertainty analysis results, conclusions were drawn as to the method that is currently more viable for computing uncertainties in burnup and transient calculations.« less
Fuel cycle cost uncertainty from nuclear fuel cycle comparison
Li, J.; McNelis, D.; Yim, M.S.
2013-07-01
This paper examined the uncertainty in fuel cycle cost (FCC) calculation by considering both model and parameter uncertainty. Four different fuel cycle options were compared in the analysis including the once-through cycle (OT), the DUPIC cycle, the MOX cycle and a closed fuel cycle with fast reactors (FR). The model uncertainty was addressed by using three different FCC modeling approaches with and without the time value of money consideration. The relative ratios of FCC in comparison to OT did not change much by using different modeling approaches. This observation was consistent with the results of the sensitivity study for the discount rate. Two different sets of data with uncertainty range of unit costs were used to address the parameter uncertainty of the FCC calculation. The sensitivity study showed that the dominating contributor to the total variance of FCC is the uranium price. In general, the FCC of OT was found to be the lowest followed by FR, MOX, and DUPIC. But depending on the uranium price, the FR cycle was found to have lower FCC over OT. The reprocessing cost was also found to have a major impact on FCC.
ARM - PI Product - Direct Aerosol Forcing Uncertainty
U.S. Department of Energy (DOE) all webpages (Extended Search)
ProductsDirect Aerosol Forcing Uncertainty ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Direct Aerosol Forcing Uncertainty 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 quantification and multiscale mathematics. (Conference...
Office of Scientific and Technical Information (OSTI)
quantification and multiscale mathematics. Citation Details In-Document Search Title: Uncertainty quantification and multiscale mathematics. Authors: Trucano, Timothy Guy ...
Bostelmann, Friederike; Strydom, Gerhard; Reitsma, Frederik; Ivanov, Kostadin
2016-01-11
The quantification of uncertainties in design and safety analysis of reactors is today not only broadly accepted, but in many cases became the preferred way to replace traditional conservative analysis for safety and licensing analysis. The use of a more fundamental methodology is also consistent with the reliable high fidelity physics models and robust, efficient, and accurate codes available today. To facilitate uncertainty analysis applications a comprehensive approach and methodology must be developed and applied, in contrast to the historical approach where sensitivity analysis were performed and uncertainties then determined by a simplified statistical combination of a few important inputmore » parameters. New methodologies are currently under development in the OECD/NEA Light Water Reactor (LWR) Uncertainty Analysis in Best-Estimate Modelling (UAM) benchmark activity. High Temperature Gas-cooled Reactor (HTGR) designs require specific treatment of the double heterogeneous fuel design and large graphite quantities at high temperatures. The IAEA has therefore launched a Coordinated Research Project (CRP) on HTGR Uncertainty Analysis in Modelling (UAM) in 2013 to study uncertainty propagation specifically in the HTGR analysis chain. Two benchmark problems are defined, with the prismatic design represented by the General Atomics (GA) MHTGR-350 and a 250 MW modular pebble bed design similar to the Chinese HTR-PM. Work has started on the first phase and the current CRP status is reported in the paper. A comparison of the Serpent and SCALE/KENO-VI reference Monte Carlo results for Ex. I-1 of the MHTGR-350 design is also included. It was observed that the SCALE/KENO-VI Continuous Energy (CE) k∞ values were 395 pcm (Ex. I-1a) to 803 pcm (Ex. I-1b) higher than the respective Serpent lattice calculations, and that within the set of the SCALE results, the KENO-VI 238 Multi-Group (MG) k∞ values were up to 800 pcm lower than the KENO-VI CE values. The use of the
Size exclusion deep bed filtration: Experimental and modelling uncertainties
Badalyan, Alexander You, Zhenjiang; Aji, Kaiser; Bedrikovetsky, Pavel; Carageorgos, Themis; Zeinijahromi, Abbas
2014-01-15
A detailed uncertainty analysis associated with carboxyl-modified latex particle capture in glass bead-formed porous media enabled verification of the two theoretical stochastic models for prediction of particle retention due to size exclusion. At the beginning of this analysis it is established that size exclusion is a dominant particle capture mechanism in the present study: calculated significant repulsive Derjaguin-Landau-Verwey-Overbeek potential between latex particles and glass beads is an indication of their mutual repulsion, thus, fulfilling the necessary condition for size exclusion. Applying linear uncertainty propagation method in the form of truncated Taylor's series expansion, combined standard uncertainties (CSUs) in normalised suspended particle concentrations are calculated using CSUs in experimentally determined parameters such as: an inlet volumetric flowrate of suspension, particle number in suspensions, particle concentrations in inlet and outlet streams, particle and pore throat size distributions. Weathering of glass beads in high alkaline solutions does not appreciably change particle size distribution, and, therefore, is not considered as an additional contributor to the weighted mean particle radius and corresponded weighted mean standard deviation. Weighted mean particle radius and LogNormal mean pore throat radius are characterised by the highest CSUs among all experimental parameters translating to high CSU in the jamming ratio factor (dimensionless particle size). Normalised suspended particle concentrations calculated via two theoretical models are characterised by higher CSUs than those for experimental data. The model accounting the fraction of inaccessible flow as a function of latex particle radius excellently predicts normalised suspended particle concentrations for the whole range of jamming ratios. The presented uncertainty analysis can be also used for comparison of intra- and inter-laboratory particle size exclusion data.
U.S. Energy Information Administration (EIA) (indexed site)
. Fuel Oil Expenditures by Census Region for Non-Mall Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per...
U.S. Energy Information Administration (EIA) (indexed site)
0. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for Non-Mall Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...
U.S. Energy Information Administration (EIA) (indexed site)
4. Fuel Oil Expenditures by Census Region, 1999" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per Square Foot"...
Gasoline and Diesel Fuel Update
Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...
U.S. Energy Information Administration (EIA) (indexed site)
A. Fuel Oil Expenditures by Census Region for All Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per...
U.S. Energy Information Administration (EIA) (indexed site)
A. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...
Gasoline and Diesel Fuel Update
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...
Gasoline and Diesel Fuel Update
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*...
Energy Science and Technology Software Center (OSTI)
2004-10-21
This is a total energy electronic structure code using Local Density Approximation (LDA) of the density funtional theory. It uses the plane wave as the wave function basis set. It can sue both the norm conserving pseudopotentials and the ultra soft pseudopotentials. It can relax the atomic positions according to the total energy. It is a parallel code using MP1.
Harper, F.T.; Young, M.L.; Miller, L.A.
1995-01-01
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.
Gasoline and Diesel Fuel Update
Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to Egypt ... Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total ...
Scaling properties of proton-nucleus total reaction cross sections
Abu-Ibrahim, Badawy; Kohama, Akihisa
2010-05-15
We study the scaling properties of proton-nucleus total reaction cross sections for stable nuclei and propose an approximate expression in proportion to Z{sup 2/3}sigma{sub pp}{sup total}+N{sup 2/3}sigma{sub pn}{sup total}. Based on this expression, we can derive a relation that enables us to predict a total reaction cross section for any stable nucleus within 10% uncertainty at most, using the empirical value of the total reaction cross section of a given nucleus.
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
Summary 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
Correcting radar range measurements for atmospheric propagation...
Office of Scientific and Technical Information (OSTI)
Title: Correcting radar range measurements for atmospheric propagation effects. Abstract not provided. Authors: Doerry, Armin Walter Publication Date: 2013-12-01 OSTI Identifier: ...
Quench propagation velocity for highly stabilized conductors
Mints, R.G. |; Ogitsu, T. |; Devred, A.
1995-05-01
Quench propagation velocity in conductors having a large amount of stabilizer outside the multifilamentary area is considered. It is shown that the current redistribution process between the multifilamentary area and the stabilizer can strongly effect the quench propagation. A criterion is derived determining the conditions under which the current redistribution process becomes significant, and a model of effective stabilizer area is suggested to describe its influence on the quench propagation velocity. As an illustration, the model is applied to calculate the adiabatic quench propagation velocity for a conductor geometry with a multifilamentary area embedded inside the stabilizer.
An Estimator of Propagation of Cascading Failure
Dobson, Ian; Wierzbicki, Kevin; Carreras, Benjamin A; Lynch, Vickie E; Newman, David E
2006-01-01
The authors suggest a statistical estimator to measure the extent to which failures propagate in cascading failures such as large blackouts.
Gasoline and Diesel Fuel Update
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...
ARM - Measurement - Total carbon
U.S. Department of Energy (DOE) all webpages (Extended Search)
carbon ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total carbon The total concentration of carbon in all its organic and non-organic forms. Categories Atmospheric Carbon, Aerosols Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including
Eslick, John C.; Ng, Brenda; Gao, Qianwen; Tong, Charles H.; Sahinidis, Nikolaos V.; Miller, David C.
2014-12-31
Under the auspices of the U.S. Department of Energy’s Carbon Capture Simulation Initiative (CCSI), a Framework for Optimization and Quantification of Uncertainty and Sensitivity (FOQUS) has been developed. This tool enables carbon capture systems to be rapidly synthesized and rigorously optimized, in an environment that accounts for and propagates uncertainties in parameters and models. FOQUS currently enables (1) the development of surrogate algebraic models utilizing the ALAMO algorithm, which can be used for superstructure optimization to identify optimal process configurations, (2) simulation-based optimization utilizing derivative free optimization (DFO) algorithms with detailed black-box process models, and (3) rigorous uncertainty quantification throughmore » PSUADE. FOQUS utilizes another CCSI technology, the Turbine Science Gateway, to manage the thousands of simulated runs necessary for optimization and UQ. Thus, this computational framework has been demonstrated for the design and analysis of a solid sorbent based carbon capture system.« less
Eslick, John C.; Ng, Brenda; Gao, Qianwen; Tong, Charles H.; Sahinidis, Nikolaos V.; Miller, David C.
2014-12-31
Under the auspices of the U.S. Department of Energys Carbon Capture Simulation Initiative (CCSI), a Framework for Optimization and Quantification of Uncertainty and Sensitivity (FOQUS) has been developed. This tool enables carbon capture systems to be rapidly synthesized and rigorously optimized, in an environment that accounts for and propagates uncertainties in parameters and models. FOQUS currently enables (1) the development of surrogate algebraic models utilizing the ALAMO algorithm, which can be used for superstructure optimization to identify optimal process configurations, (2) simulation-based optimization utilizing derivative free optimization (DFO) algorithms with detailed black-box process models, and (3) rigorous uncertainty quantification through PSUADE. FOQUS utilizes another CCSI technology, the Turbine Science Gateway, to manage the thousands of simulated runs necessary for optimization and UQ. Thus, this computational framework has been demonstrated for the design and analysis of a solid sorbent based carbon capture system.
Survey of sampling-based methods for uncertainty and sensitivity analysis.
Johnson, Jay Dean; Helton, Jon Craig; Sallaberry, Cedric J. PhD.; Storlie, Curt B. (Colorado State University, Fort Collins, CO)
2006-06-01
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.
Uncertainty quantification of a radionuclide release model using an adaptive spectral technique
Gilli, L.; Hoogwerf, C.; Lathouwers, D.; Kloosterman, J. L.
2013-07-01
In this paper we present the application of a non-intrusive spectral techniques we recently developed for the evaluation of the uncertainties associated with a radionuclide migration problem. Spectral techniques can be used to reconstruct stochastic quantities of interest by means of a Fourier-like expansion. Their application to uncertainty propagation problems can be performed by evaluating a set of realizations which are chosen adaptively, in this work the main details about how this is done are presented. The uncertainty quantification problem we are going to deal with was first solved in a recent work where the authors used a spectral technique based on an intrusive approach. In this paper we are going to reproduce the results of this reference work, compare them and discuss the main numerical aspects. (authors)
Capturing the uncertainty in adversary attack simulations.
Darby, John L.; Brooks, Traci N.; Berry, Robert Bruce
2008-09-01
This work provides a comprehensive uncertainty technique to evaluate uncertainty, resulting in a more realistic evaluation of PI, thereby requiring fewer resources to address scenarios and allowing resources to be used across more scenarios. For a given set of dversary resources, two types of uncertainty are associated with PI for a scenario: (1) aleatory (random) uncertainty for detection probabilities and time delays and (2) epistemic (state of knowledge) uncertainty for the adversary resources applied during an attack. Adversary esources consist of attributes (such as equipment and training) and knowledge about the security system; to date, most evaluations have assumed an adversary with very high resources, adding to the conservatism in the evaluation of PI. The aleatory uncertainty in PI is ddressed by assigning probability distributions to detection probabilities and time delays. A numerical sampling technique is used to evaluate PI, addressing the repeated variable dependence in the equation for PI.
Incorporating Forecast Uncertainty in Utility Control Center
Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian
2014-07-09
Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)
3D Elastic Seismic Wave Propagation Code
Energy Science and Technology Software Center (OSTI)
1998-09-23
E3D is capable of simulating seismic wave propagation in a 3D heterogeneous earth. Seismic waves are initiated by earthquake, explosive, and/or other sources. These waves propagate through a 3D geologic model, and are simulated as synthetic seismograms or other graphical output.
Propagation testing multi-cell batteries.
Orendorff, Christopher J.; Lamb, Joshua; Steele, Leigh Anna Marie; Spangler, Scott Wilmer
2014-10-01
Propagation of single point or single cell failures in multi-cell batteries is a significant concern as batteries increase in scale for a variety of civilian and military applications. This report describes the procedure for testing failure propagation along with some representative test results to highlight the potential outcomes for different battery types and designs.
National Nuclear Security Administration (NNSA)
8 Actuals 2009 Actuals 2010 Actuals 2011 Actuals 2012 Actuals 2013 Actuals 2014 Actuals 2015 Actuals Total DOE/NNSA 4,385 4,151 4,240 4,862 5,154 5,476 7,170 7,593 Total non-NNSA 3,925 4,017 4,005 3,821 3,875 3,974 3,826 3765 Total Facility 8,310 8,168 8,245 8,683 9,029 9,450 10,996 11,358 non-NNSA includes DOE offices and Strategic Parternship Projects (SPP) employees NNSA M&O Employee Reporting
Uncertainty quantification for discrimination of nuclear events...
Office of Scientific and Technical Information (OSTI)
comprehensive nuclear-test-ban treaty Title: Uncertainty quantification for discrimination of nuclear events as violations of the comprehensive nuclear-test-ban treaty Authors: ...
Uncertainty Quantification in Climate Modeling - Discovering...
Office of Scientific and Technical Information (OSTI)
in Climate Modeling - Discovering Sparsity and Building Surrogates. Citation Details In-Document Search Title: Uncertainty Quantification in Climate Modeling - Discovering ...
Direct Aerosol Forcing Uncertainty (Dataset) | Data Explorer
Office of Scientific and Technical Information (OSTI)
comparable to uncertainty arising from some individual properties. less Authors: Mccomiskey, Allison Publication Date: 2008-01-15 OSTI Identifier: 1169526 DOE Contract ...
Validation and Uncertainty Characterization for Energy Simulation
Validation and Uncertainty Characterization for Energy Simulation (1530) Philip Haves (LBNL) Co-PI's: Ron Judkoff (NREL), Joshua New (ORNL), Ralph Muehleisen (ANL) BTO Merit ...
From Deterministic Inversion to Uncertainty Quantification: Planning...
Office of Scientific and Technical Information (OSTI)
Glen's Flow Law exponent) Main sources of uncertainty: Problem definition Goal: ... Common y Proposed U: computed depth averaged velocity H: ice thickness basal sliding ...
From Deterministic Inversion to Uncertainty Quantification: Planning...
Office of Scientific and Technical Information (OSTI)
Planning a Long Journey in Ice Sheet Modeling. Citation Details In-Document Search Title: From Deterministic Inversion to Uncertainty Quantification: Planning a Long Journey in ...
Uncertainties in global aerosol simulations: Assessment using...
Office of Scientific and Technical Information (OSTI)
Title: Uncertainties in global aerosol simulations: Assessment using three meteorological data sets Current global aerosol models use different physical and chemical schemes and 4 ...
Uncertainty Quantification for Nuclear Density Functional Theory...
Office of Scientific and Technical Information (OSTI)
Uncertainty Quantification for Nuclear Density Functional Theory and Information Content of New Measurements Citation Details In-Document Search This content will become publicly...
Habte, Aron
2015-06-25
This presentation summarizes uncertainty estimation of radiometric data using the Guide to the Expression of Uncertainty (GUM) method.
Cosmic ray propagation and dark matter in light of the latest AMS-02 data
Jin, Hong-Bo; Wu, Yue-Liang; Zhou, Yu-Feng
2015-09-21
The AMS-02 experiment is measuring the high energy cosmic rays with unprecedented accuracy. We explore the possibility of determining the cosmic-ray propagation models using the AMS-02 data alone. A global Bayesian analysis of the constraints on the cosmic-ray propagation models from the preliminary AMS-02 data on the Boron to Carbon nuclei flux ratio and proton flux is performed, with the assumption that the primary nucleon source is a broken power law in rigidity. The ratio of the diffusion coefficient D{sub 0} to the diffusive halo height Z{sub h} is determined with high accuracy D{sub 0}/Z{sub h}≃2.00±0.07 cm{sup 2}s{sup −1}kpc{sup −1}, and the value of the halo width is found to be Z{sub h}≃3.3 kpc with uncertainty less than 50%. As a consequence, the typical uncertainties in the positron fraction predicted from dark matter (DM) annihilation is reduced to a factor of two, and that in the antiproton flux is about an order of magnitude. Both of them are significantly smaller than that from the analyses prior to AMS-02. Taking into account the uncertainties and correlations in the propagation parameters, we derive conservative upper limits on the cross sections for DM annihilating into various standard model final states from the current PAMELA antiproton data. We also investigate the reconstruction capability of the future high precision AMS-02 antiproton data on the DM properties. The results show that for DM particles lighter than ∼100 GeV and with typical thermal annihilation cross section, the cross section can be well reconstructed with uncertainties about a factor of two for the AMS-02 three-year data taking.
Near IR Scanning Angle Total Internal Reflection Raman Spectroscopy at Smooth Gold Films
McKee, Kristopher; Meyer, Matthew; Smith, Emily
2012-04-13
Total internal reflection (TIR) Raman and reflectivity spectra were collected for nonresonant analytes as a function of incident angle at sapphire or sapphire/smooth 50 nm gold interfaces using 785 nm excitation. For both interfaces, the Raman signal as a function of incident angle is well-modeled by the calculated interfacial mean square electric field (MSEF) relative to the incident field times the thickness of the layer being probed in the Raman measurement (D{sub RS}). The Raman scatter was reproducibly enhanced at the interface containing a gold film relative to the sapphire interface by a factor of 4.34.6 for aqueous pyridine or 2.23.7 for neat nitrobenzene, depending on the analyzed vibrational mode. The mechanism for the increased Raman signal is the enhanced MSEF at incident angles where propagating surface plasmons are excited in the metal film. The background from the TIR prism was reduced by 8995% with the addition of the gold film, and the percent relative uncertainty in peak area was reduced from 15 to 1.7% for the 1347 cm1 mode of nitrobenzene. Single monolayers of benzenethiol (S/N = 6.8) and 4-mercaptopyridine (S/N = 16.5) on gold films were measured by TIR Raman spectroscopy with 785 nm excitation (210 mW) without resonant enhancement in 1 min.
Sensitivity and Uncertainty Analysis Shell
Energy Science and Technology Software Center (OSTI)
1999-04-20
SUNS (Sensitivity and Uncertainty Analysis Shell) is a 32-bit application that runs under Windows 95/98 and Windows NT. It is designed to aid in statistical analyses for a broad range of applications. The class of problems for which SUNS is suitable is generally defined by two requirements: 1. A computer code is developed or acquired that models some processes for which input is uncertain and the user is interested in statistical analysis of the outputmore » of that code. 2. The statistical analysis of interest can be accomplished using the Monte Carlo analysis. The implementation then requires that the user identify which input to the process model is to be manipulated for statistical analysis. With this information, the changes required to loosely couple SUNS with the process model can be completed. SUNS is then used to generate the required statistical sample and the user-supplied process model analyses the sample. The SUNS post processor displays statistical results from any existing file that contains sampled input and output values.« less
Uncertainty analysis in geospatial merit matrix–based hydropower resource assessment
Pasha, M. Fayzul K.; Yeasmin, Dilruba; Saetern, Sen; Yang, Majntxov; Kao, Shih -Chieh; Smith, Brennan T.
2016-03-30
Hydraulic head and mean annual streamflow, two main input parameters in hydropower resource assessment, are not measured at every point along the stream. Translation and interpolation are used to derive these parameters, resulting in uncertainties. This study estimates the uncertainties and their effects on model output parameters: the total potential power and the number of potential locations (stream-reach). These parameters are quantified through Monte Carlo Simulation (MCS) linking with a geospatial merit matrix based hydropower resource assessment (GMM-HRA) Model. The methodology is applied to flat, mild, and steep terrains. Results show that the uncertainty associated with the hydraulic head ismore » within 20% for mild and steep terrains, and the uncertainty associated with streamflow is around 16% for all three terrains. Output uncertainty increases as input uncertainty increases. However, output uncertainty is around 10% to 20% of the input uncertainty, demonstrating the robustness of the GMM-HRA model. Hydraulic head is more sensitive to output parameters in steep terrain than in flat and mild terrains. Furthermore, mean annual streamflow is more sensitive to output parameters in flat terrain.« less
Estimating the uncertainty in underresolved nonlinear dynamics
Chorin, Alelxandre; Hald, Ole
2013-06-12
The Mori-Zwanzig formalism of statistical mechanics is used to estimate the uncertainty caused by underresolution in the solution of a nonlinear dynamical system. A general approach is outlined and applied to a simple example. The noise term that describes the uncertainty turns out to be neither Markovian nor Gaussian. It is argued that this is the general situation.
A High-Performance Embedded Hybrid Methodology for Uncertainty Quantification With Applications
Iaccarino, Gianluca
2014-04-01
Multiphysics processes modeled by a system of unsteady di erential equations are natu- rally suited for partitioned (modular) solution strategies. We consider such a model where probabilistic uncertainties are present in each module of the system and represented as a set of random input parameters. A straightforward approach in quantifying uncertainties in the predicted solution would be to sample all the input parameters into a single set, and treat the full system as a black-box. Although this method is easily parallelizable and requires minimal modi cations to deterministic solver, it is blind to the modular structure of the underlying multiphysical model. On the other hand, using spectral representations polynomial chaos expansions (PCE) can provide richer structural information regarding the dynamics of these uncertainties as they propagate from the inputs to the predicted output, but can be prohibitively expensive to implement in the high-dimensional global space of un- certain parameters. Therefore, we investigated hybrid methodologies wherein each module has the exibility of using sampling or PCE based methods of capturing local uncertainties while maintaining accuracy in the global uncertainty analysis. For the latter case, we use a conditional PCE model which mitigates the curse of dimension associated with intru- sive Galerkin or semi-intrusive Pseudospectral methods. After formalizing the theoretical framework, we demonstrate our proposed method using a numerical viscous ow simulation and benchmark the performance against a solely Monte-Carlo method and solely spectral method.
Perko, Z.; Gilli, L.; Lathouwers, D.; Kloosterman, J. L.
2013-07-01
Uncertainty quantification plays an increasingly important role in the nuclear community, especially with the rise of Best Estimate Plus Uncertainty methodologies. Sensitivity analysis, surrogate models, Monte Carlo sampling and several other techniques can be used to propagate input uncertainties. In recent years however polynomial chaos expansion has become a popular alternative providing high accuracy at affordable computational cost. This paper presents such polynomial chaos (PC) methods using adaptive sparse grids and adaptive basis set construction, together with an application to a Gas Cooled Fast Reactor transient. Comparison is made between a new sparse grid algorithm and the traditionally used technique proposed by Gerstner. An adaptive basis construction method is also introduced and is proved to be advantageous both from an accuracy and a computational point of view. As a demonstration the uncertainty quantification of a 50% loss of flow transient in the GFR2400 Gas Cooled Fast Reactor design was performed using the CATHARE code system. The results are compared to direct Monte Carlo sampling and show the superior convergence and high accuracy of the polynomial chaos expansion. Since PC techniques are easy to implement, they can offer an attractive alternative to traditional techniques for the uncertainty quantification of large scale problems. (authors)
CALiPER Exploratory Study: Accounting for Uncertainty in Lumen Measurements
Bergman, Rolf; Paget, Maria L.; Richman, Eric E.
2011-03-31
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
National Nuclear Security Administration (NNSA)
76 Females Male Female Male Female Male Female Male Female Male Female 27 24 86 134 65 24 192 171 1189 423 PAY PLAN SES 96 EX 4 EJ/EK 60 EN 05 39 EN 04 159 EN 03 21 EN 00 8 NN (Engineering) 398 NQ (Prof/Tech/Admin) 1165 NU (Tech/Admin Support) 54 NV (Nuc Mat Courier) 325 GS 15 3 GS 14 1 GS 13 1 GS 10 1 Total includes 2318 permanent and 17 temporary employees. DIVERSITY 2335 1559 66.8% American Indian Alaska Native African American Asian American Pacific Islander Hispanic White 33.2% National
Numerical uncertainty in computational engineering and physics
Hemez, Francois M
2009-01-01
Obtaining a solution that approximates ordinary or partial differential equations on a computational mesh or grid does not necessarily mean that the solution is accurate or even 'correct'. Unfortunately assessing the quality of discrete solutions by questioning the role played by spatial and temporal discretizations generally comes as a distant third to test-analysis comparison and model calibration. This publication is contributed to raise awareness of the fact that discrete solutions introduce numerical uncertainty. This uncertainty may, in some cases, overwhelm in complexity and magnitude other sources of uncertainty that include experimental variability, parametric uncertainty and modeling assumptions. The concepts of consistency, convergence and truncation error are overviewed to explain the articulation between the exact solution of continuous equations, the solution of modified equations and discrete solutions computed by a code. The current state-of-the-practice of code and solution verification activities is discussed. An example in the discipline of hydro-dynamics illustrates the significant effect that meshing can have on the quality of code predictions. A simple method is proposed to derive bounds of solution uncertainty in cases where the exact solution of the continuous equations, or its modified equations, is unknown. It is argued that numerical uncertainty originating from mesh discretization should always be quantified and accounted for in the overall uncertainty 'budget' that supports decision-making for applications in computational physics and engineering.
A flexible uncertainty quantification method for linearly coupled multi-physics systems
Chen, Xiao Ng, Brenda; Sun, Yunwei; Tong, Charles
2013-09-01
Highlights: We propose a modularly hybrid UQ methodology suitable for independent development of module-based multi-physics simulation. Our algorithmic framework allows for each module to have its own UQ method (either intrusive or non-intrusive). Information from each module is combined systematically to propagate global uncertainty. Our proposed approach can allow for easy swapping of new methods for any modules without the need to address incompatibilities. We demonstrate the proposed framework on a practical application involving a multi-species reactive transport model. -- Abstract: This paper presents a novel approach to building an integrated uncertainty quantification (UQ) methodology suitable for modern-day component-based approach for multi-physics simulation development. Our hybrid UQ methodology supports independent development of the most suitable UQ method, intrusive or non-intrusive, for each physics module by providing an algorithmic framework to couple these stochastic modules for propagating global uncertainties. We address algorithmic and computational issues associated with the construction of this hybrid framework. We demonstrate the utility of such a framework on a practical application involving a linearly coupled multi-species reactive transport model.
Total aerosol effect: forcing or radiative flux perturbation?
Lohmann, Ulrike; Storelvmo, Trude; Jones, Andy; Rotstayn, Leon; Menon, Surabi; Quaas, Johannes; Ekman, Annica; Koch, Dorothy; Ruedy, Reto
2009-09-25
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.
Fracture Propagation, Fluid Flow, and Geomechanics of Water-Based...
Office of Scientific and Technical Information (OSTI)
Conference: Fracture Propagation, Fluid Flow, and Geomechanics of Water-Based Hydraulic ... Title: Fracture Propagation, Fluid Flow, and Geomechanics of Water-Based Hydraulic ...
Characterization of Heat-Wave Propagation through Laser-Driven...
Office of Scientific and Technical Information (OSTI)
Characterization of Heat-Wave Propagation through Laser-Driven Ti-Doped Underdense Plasma Citation Details In-Document Search Title: Characterization of Heat-Wave Propagation...
Supersonic Heat Wave Propagation in Laser-Produced Underdense...
Office of Scientific and Technical Information (OSTI)
Supersonic Heat Wave Propagation in Laser-Produced Underdense Plasma for Efficient X-Ray Generation Citation Details In-Document Search Title: Supersonic Heat Wave Propagation in...
Fracture Propagation, Fluid Flow, and Geomechanics of Water-Based...
Office of Scientific and Technical Information (OSTI)
Conference: Fracture Propagation, Fluid Flow, and Geomechanics of Water-Based Hydraulic ... Citation Details In-Document Search Title: Fracture Propagation, Fluid Flow, and ...
Equivalent Continuum Modeling for Shock Wave Propagation in Jointed...
Office of Scientific and Technical Information (OSTI)
Equivalent Continuum Modeling for Shock Wave Propagation in Jointed Media Citation Details In-Document Search Title: Equivalent Continuum Modeling for Shock Wave Propagation in ...
Problems with propagation and time evolution in f ( T ) gravity...
Office of Scientific and Technical Information (OSTI)
Problems with propagation and time evolution in f ( T ) gravity Citation Details In-Document Search Title: Problems with propagation and time evolution in f ( T ) gravity Authors: ...
Experimental X-ray characterization of Gekko XII laser propagation...
Office of Scientific and Technical Information (OSTI)
Experimental X-ray characterization of Gekko XII laser propagation through very low ... Title: Experimental X-ray characterization of Gekko XII laser propagation through very low ...
Uncommon Deformation Mechanisms during Fatigue-Crack Propagation...
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Uncommon Deformation Mechanisms during Fatigue-Crack Propagation in Nanocrystalline Alloys Prev Next Title: Uncommon Deformation Mechanisms during Fatigue-Crack Propagation ...
The Role of Uncertainty Quantification for Reactor Physics
Salvatores, Massimo; Palmiotti, Giuseppe; Aliberti, G.
2015-01-01
The quantification of uncertainties is a crucial step in design. The comparison of a-priori uncertainties with the target accuracies, allows to define needs and priorities for uncertainty reduction. In view of their impact, the uncertainty analysis requires a reliability assessment of the uncertainty data used. The choice of the appropriate approach and the consistency of different approaches are discussed.
Time elements for enhanced performance of the Dromo orbit propagator
Baù, Giulio; Bombardelli, Claudio E-mail: claudio.bombardelli@upm.es
2014-09-01
We propose two time elements for the orbit propagator named Dromo. One is linear and the other constant with respect to the independent variable, which coincides with the osculating true anomaly in the Keplerian motion. They are defined from a generalized Kepler's equation written for negative values of the total energy and, unlike the few existing time elements of this kind, are free of singularities. To our knowledge it is the first time that a constant time element is associated with a second-order Sundman time transformation. Numerical tests to assess the performance of the Dromo method equipped with a time element show the remarkable improvement in accuracy for the perturbed bounded motion around the Earth compared to the case in which the physical time is a state variable. Moreover, the method is competitive with and even better than other efficient sets of elements. Finally, we also derive a time element for a null and positive total energy.
An uncertainty principle for unimodular quantum groups
Crann, Jason; Kalantar, Mehrdad E-mail: mkalanta@math.carleton.ca
2014-08-15
We present a generalization of Hirschman's entropic uncertainty principle for locally compact Abelian groups to unimodular locally compact quantum groups. As a corollary, we strengthen a well-known uncertainty principle for compact groups, and generalize the relation to compact quantum groups of Kac type. We also establish the complementarity of finite-dimensional quantum group algebras. In the non-unimodular setting, we obtain an uncertainty relation for arbitrary locally compact groups using the relative entropy with respect to the Haar weight as the measure of uncertainty. We also show that when restricted to q-traces of discrete quantum groups, the relative entropy with respect to the Haar weight reduces to the canonical entropy of the random walk generated by the state.
Reducing Petroleum Despendence in California: Uncertainties About
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
Light-Duty Diesel | Department of Energy Petroleum Despendence in California: Uncertainties About Light-Duty Diesel Reducing Petroleum Despendence in California: Uncertainties About Light-Duty Diesel 2002 DEER Conference Presentation: Center for Energy Efficiency and Renewable Technologies 2002_deer_phillips.pdf (62.04 KB) More Documents & Publications Diesel Use in California Future Potential of Hybrid and Diesel Powertrains in the U.S. Light-Duty Vehicle Market Dumping Dirty Diesels:
Cost Analysis: Technology, Competitiveness, Market Uncertainty | Department
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
of Energy Technology to Market » Cost Analysis: Technology, Competitiveness, Market Uncertainty Cost Analysis: Technology, Competitiveness, Market Uncertainty As a basis for strategic planning, competitiveness analysis, funding metrics and targets, SunShot supports analysis teams at national laboratories to assess technology costs, location-specific competitive advantages, policy impacts on system financing, and to perform detailed levelized cost of energy (LCOE) analyses. This shows the
Propagation of data error and parametric sensitivity in computable...
Office of Scientific and Technical Information (OSTI)
assess how these forms of uncertainty impact the conclusions that can be drawn from the model simulations. We find greater sensitivity to uncertainty in the elasticity of ...
Addressing Uncertainties in Design Inputs: A Case Study of Probabilist...
Office of Environmental Management (EM)
Addressing Uncertainties in Design Inputs: A Case Study of Probabilistic Settlement Evaluations for Soft Zone Collapse at SWPF Addressing Uncertainties in Design Inputs: A Case ...
Computational Fluid Dynamics & Large-Scale Uncertainty Quantification...
U.S. Department of Energy (DOE) all webpages (Extended Search)
... (CFD) simulations and uncertainty analyses. The project developed new mathematical uncertainty quantification techniques and applied them, in combination with high-fidelity CFD ...
Analysis of the Uncertainty in Wind Measurements from the Atmospheric...
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Analysis of the Uncertainty in Wind Measurements from the Atmospheric Radiation ... Citation Details In-Document Search Title: Analysis of the Uncertainty in Wind ...
Improvements of Nuclear Data and Its Uncertainties by Theoretical...
Office of Scientific and Technical Information (OSTI)
Improvements of Nuclear Data and Its Uncertainties by Theoretical Modeling Citation Details In-Document Search Title: Improvements of Nuclear Data and Its Uncertainties by ...
Early solar mass loss, opacity uncertainties, and the solar abundance...
Office of Scientific and Technical Information (OSTI)
Early solar mass loss, opacity uncertainties, and the solar abundance problem Citation Details In-Document Search Title: Early solar mass loss, opacity uncertainties, and the solar ...
Analysis and Reduction of Chemical Models under Uncertainty ...
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Analysis and Reduction of Chemical Models under Uncertainty Citation Details In-Document Search Title: Analysis and Reduction of Chemical Models under Uncertainty Abstract not ...
Quantification of initial-data uncertainty on a shock-accelerated gas cylinder
Tritschler, V. K. Avdonin, A.; Hickel, S.; Hu, X. Y.; Adams, N. A.
2014-02-15
We quantify initial-data uncertainties on a shock accelerated heavy-gas cylinder by two-dimensional well-resolved direct numerical simulations. A high-resolution compressible multicomponent flow simulation model is coupled with a polynomial chaos expansion to propagate the initial-data uncertainties to the output quantities of interest. The initial flow configuration follows previous experimental and numerical works of the shock accelerated heavy-gas cylinder. We investigate three main initial-data uncertainties, (i) shock Mach number, (ii) contamination of SF{sub 6} with acetone, and (iii) initial deviations of the heavy-gas region from a perfect cylindrical shape. The impact of initial-data uncertainties on the mixing process is examined. The results suggest that the mixing process is highly sensitive to input variations of shock Mach number and acetone contamination. Additionally, our results indicate that the measured shock Mach number in the experiment of Tomkins et al. [An experimental investigation of mixing mechanisms in shock-accelerated flow, J. Fluid. Mech. 611, 131 (2008)] and the estimated contamination of the SF{sub 6} region with acetone [S. K. Shankar, S. Kawai, and S. K. Lele, Two-dimensional viscous flow simulation of a shock accelerated heavy gas cylinder, Phys. Fluids 23, 024102 (2011)] exhibit deviations from those that lead to best agreement between our simulations and the experiment in terms of overall flow evolution.
Laser propagation in underdense plasmas: Scaling arguments
Garrison, J.C.
1993-05-01
The propagation of an intense laser beam in the underdense plasma is modelled by treating the plasma as a relativistic, zero temperature, charged fluid. For paraxial propagation and a sufficiently underdense plasma ({omega}p/{omega} {much_lt} 1), a multiple-scales technique is used to expand the exact equations in powers of the small parameter {theta} {equivalent_to} {omega}p/{omega}. The zeroth order equations are used in a critical examination of previous work on this problem, and to derive a scaling law for the threshold power required for cavitation.
Light propagation in the South Pole ice
Williams, Dawn; Collaboration: IceCube Collaboration
2014-11-18
The IceCube Neutrino Observatory is located in the ice near the geographic South Pole. Particle showers from neutrino interactions in the ice produce light which is detected by IceCube modules, and the amount and pattern of deposited light are used to reconstruct the properties of the incident neutrino. Since light is scattered and absorbed by ice between the neutrino interaction vertex and the sensor, IceCube event reconstruction depends on understanding the propagation of light through the ice. This paper presents the current status of modeling light propagation in South Pole ice, including the recent observation of an azimuthal anisotropy in the scattering.
Determination of Total Petroleum Hydrocarbons (TPH) Using Total Carbon Analysis
Ekechukwu, A.A.
2002-05-10
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.
Strydom, Gerhard; Bostelmann, Friederike; Ivanov, Kostadin
2014-10-01
required confidence level. In order to address uncertainty propagation in analysis and methods in the HTGR community the IAEA initiated a Coordinated Research Project (CRP) on the HTGR Uncertainty Analysis in Modelling (UAM) that officially started in 2013. Although this project focuses specifically on the peculiarities of HTGR designs and its simulation requirements, many lessons can be learned from the LWR community and the significant progress already made towards a consistent methodology uncertainty analysis. In the case of LWRs the NRC has already in 1988 amended 10 CFR 50.46 to allow best-estimate (plus uncertainties) calculations of emergency core cooling system performance. The Nuclear Energy Agency (NEA) of the Organization for Economic Co-operation and Development (OECD) also established an Expert Group on "Uncertainty Analysis in Modelling" which finally led to the definition of the "Benchmark for Uncertainty Analysis in Modelling (UAM) for Design, Operation and Safety Analysis of LWRs". The CRP on HTGR UAM will follow as far as possible the on-going OECD Light Water Reactor UAM benchmark activity.
Model development and data uncertainty integration
Swinhoe, Martyn Thomas
2015-12-02
The effect of data uncertainties is discussed, with the epithermal neutron multiplicity counter as an illustrative example. Simulation using MCNP6, cross section perturbations and correlations are addressed, along with the effect of the ^{240}Pu spontaneous fission neutron spectrum, the effect of P(ν) for ^{240}Pu spontaneous fission, and the effect of spontaneous fission and (α,n) intensity. The effect of nuclear data is the product of the initial uncertainty and the sensitivity -- both need to be estimated. In conclusion, a multi-parameter variation method has been demonstrated, the most significant parameters are the basic emission rates of spontaneous fission and (α,n) processes, and uncertainties and important data depend on the analysis technique chosen.
Detonation propagation in a high loss configuration
Jackson, Scott I; Shepherd, Joseph E
2009-01-01
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.
The various manifestations of collisionless dissipation in wave propagation
Benisti, Didier; Morice, Olivier; Gremillet, Laurent
2012-06-15
The propagation of an electrostatic wave packet inside a collisionless and initially Maxwellian plasma is always dissipative because of the irreversible acceleration of the electrons by the wave. Then, in the linear regime, the wave packet is Landau damped, so that in the reference frame moving at the group velocity, the wave amplitude decays exponentially with time. In the nonlinear regime, once phase mixing has occurred and when the electron motion is nearly adiabatic, the damping rate is strongly reduced compared to the Landau one, so that the wave amplitude remains nearly constant along the characteristics. Yet, we show here that the electrons are still globally accelerated by the wave packet, and in one dimension, this leads to a non local amplitude dependence of the group velocity. As a result, a freely propagating wave packet would shrink, and therefore, so would its total energy. In more than one dimension, not only does the magnitude of the group velocity nonlinearly vary, but also its direction. In the weakly nonlinear regime, when the collisionless damping rate is still significant compared to its linear value, the group velocity is directed towards the outside of the wave packet and tends to increase its transverse extent, while the opposite is true once the wave is essentially undamped. The impact of the nonlinear variation of the group velocity on the transverse size of the wave packet is quantified, and compared to that induced by the self-focussing due to wave front bowing.
U.S. Energy Information Administration (EIA) (indexed site)
Barbados Total To Brazil Freeport, TX Sabine Pass, LA Total to Canada Eastport, ID Calais, ME Detroit, MI Marysville, MI Port Huron, MI Crosby, ND Portal, ND Sault St. Marie, MI St. Clair, MI Noyes, MN Warroad, MN Babb, MT Havre, MT Port of Morgan, MT Sherwood, ND Pittsburg, NH Buffalo, NY 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 Egypt Freeport, TX Total to India
Total Eolica | Open Energy Information
Open Energy Information (Open El) [EERE & EIA]
Eolica Jump to: navigation, search Name: Total Eolica Place: Spain Product: Project developer References: Total Eolica1 This article is a stub. You can help OpenEI by expanding...
Coping with uncertainties of mercury regulation
Reich, K.
2006-09-15
The thermometer is rising as coal-fired plants cope with the uncertainties of mercury regulation. The paper deals with a diagnosis and a suggested cure. It describes the state of mercury emission rules in the different US states, many of which had laws or rules in place before the Clean Air Mercury Rule (CAMR) was promulgated.
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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
Total............................................................
U.S. Energy Information Administration (EIA) (indexed site)
Total..............................................................
U.S. Energy Information Administration (EIA) (indexed site)
,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
Total...............................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total...............................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total...............................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total...............................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total.................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total.................................................................
U.S. Energy Information Administration (EIA) (indexed site)
14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Space Heating Equipment........ 1.2 N Q Q 0.2 0.4 0.2 0.2 Q Have Main Space Heating Equipment........... 109.8 14.7 7.4 12.4 12.2 18.5 18.3 17.1 9.2 Use Main Space Heating Equipment............. 109.1 14.6 7.3 12.4 12.2 18.2 18.2 17.1 9.1 Have Equipment But Do Not Use It............... 0.8 Q Q Q Q 0.3 Q N Q Main Heating Fuel and Equipment Natural Gas................................................... 58.2 9.2 4.9 7.8 7.1 8.8 8.4 7.8 4.2 Central
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
Total...................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total...................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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 37.8 3.4 2.2 7.0 3.1 With a Heat Pump....................................... 12.3 9.7 0.6 0.5 1.0 0.6 Window/Wall Units.......................................... 28.9 14.9 2.3 3.5 6.0 2.1 1 Unit........................................................... 14.5 6.6 1.0 1.6 4.2 1.2 2
Total.......................................................................
U.S. Energy Information Administration (EIA) (indexed site)
0.6 15.1 5.5 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.9 5.3 1.6 Use a Personal Computer................................ 75.6 13.7 9.8 3.9 Number of Desktop PCs 1.................................................................. 50.3 9.3 6.8 2.5 2.................................................................. 16.2 2.9 1.9 1.0 3 or More..................................................... 9.0 1.5 1.1 0.4 Number of Laptop PCs
Total.......................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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 Number of Desktop PCs 1.................................................................. 50.3 11.9 8.4 3.4 2.................................................................. 16.2 3.5 2.2 1.3 3 or More..................................................... 9.0 2.1 1.5 0.6 Number of Laptop PCs
Total.......................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total........................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total........................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total........................................................................
U.S. Energy Information Administration (EIA) (indexed site)
0.7 21.7 6.9 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q N Q Have Main Space Heating Equipment.................. 109.8 40.3 21.4 6.9 12.0 Use Main Space Heating Equipment.................... 109.1 40.1 21.2 6.9 12.0 Have Equipment But Do Not Use It...................... 0.8 Q Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 13.6 5.6 2.3 5.7 Central Warm-Air Furnace................................ 44.7 11.0 4.4
Total........................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total...........................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total...........................................................................
U.S. Energy Information Administration (EIA) (indexed site)
5.6 17.7 7.9 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 Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat
Total...........................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total.............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 17.3 32.1 10.5 Without a Heat
Total.............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total.............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total.............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total.............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total.............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total.............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total.............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total..............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total..............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
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 Number of Desktop PCs 1......................................................................... 50.3 3.1 3.4 3.4 5.4 2......................................................................... 16.2 0.7 1.1 1.2 2.2 3 or More............................................................ 9.0 0.3
Total..............................................................................
U.S. Energy Information Administration (EIA) (indexed site)
7.1 19.0 22.7 22.3 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 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 25.8 10.9 16.6 12.5
Total....................................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total....................................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total....................................................................................
U.S. Energy Information Administration (EIA) (indexed site)
Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.0 1.6 0.3 1.1 2 Times A Day.............................................................. 24.6 8.3 4.2 1.3 2.7 Once a Day................................................................... 42.3 15.0 8.1 2.7 4.2 A Few Times Each Week............................................. 27.2 10.9 6.0 1.8 3.1 About Once a Week..................................................... 3.9
Total....................................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total....................................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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
Total....................................................................................
U.S. Energy Information Administration (EIA) (indexed site)
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.....................................................
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
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
Total..........................................................
U.S. Energy Information Administration (EIA) (indexed site)
... Basements Basement in Single-Family Homes and Apartments in 2-4 Unit Buildings ... Attics Attic in Single-Family Homes and Apartments in 2-4 Unit Buildings ...
U.S. Energy Information Administration (EIA) (indexed site)
... Climate region 3 Very coldCold 31,898 30,469 28,057 28,228 21,019 30,542 25,067 Mixed-humid 27,873 26,716 24,044 26,365 21,026 27,096 22,812 Mixed-dryHot-dry 12,037 10,484 7,628 ...
Total..........................................................
Air-Conditioning Equipment 1, 2 Central System......Central Air-Conditioning...... 65.9 1.1 6.4 6.4 ...
Total..........................................................
Income Relative to Poverty Line Below 100 Percent......1.3 1.2 0.8 0.4 1. Below 150 percent of poverty line or 60 percent of median State ...
Total..........................................................
U.S. Department of Energy (DOE) all webpages (Extended Search)
... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More 60,000 to 79,999 ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More 60,000 to 79,999 ...
Total..........................................................
U.S. Department of Energy (DOE) all webpages (Extended Search)
... Table HC7.4 Space Heating Characteristics by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More Space Heating ...
Total..........................................................
Gasoline and Diesel Fuel Update
... Table HC7.7 Air-Conditioning Usage Indicators by Household Income, 2005 Below Poverty Line ... Table HC7.7 Air-Conditioning Usage Indicators by Household Income, 2005 Below Poverty Line ...
Total..........................................................
... Living Space Characteristics Below Poverty Line Eligible for Federal Assistance 1 Million ... Living Space Characteristics Below Poverty Line Eligible for Federal Assistance 1 Million ...
Total..........................................................
... Table HC7.12 Home Electronics Usage Indicators by Household Income, 2005 Below Poverty ... Table HC7.12 Home Electronics Usage Indicators by Household Income, 2005 Below Poverty ...
Total..........................................................
... Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 40,000 to 59,999 60,000 to 79,999 ...
U.S. Energy Information Administration (EIA) (indexed site)
1,001 to 5,000 2,777 8,041 10,232 2.9 786 56 5,001 to 10,000 1,229 8,900 9,225 7.2 965 62 10,001 to 25,000 884 14,105 14,189 16.0 994 65 25,001 to 50,000 332 11,917 11,327 35.9 1,052 72 50,001 to 100,000 199 13,918 12,345 69.9 1,127 80 100,001 to 200,000 90 12,415 11,310 137.9 1,098 89 200,001 to 500,000 38 10,724 10,356 284.2 1,035 99 Over 500,000 8 7,074 9,196 885.0 769 117 Principal building activity Education 389 12,239 10,885 31.5 1,124 53 Food sales 177 1,252 1,172 7.1 1,067 121 Food
U.S. Energy Information Administration (EIA) (indexed site)
1,001 to 5,000 2,777 8,041 10,232 2.9 786 56 5,001 to 10,000 1,229 8,900 9,225 7.2 965 62 10,001 to 25,000 884 14,105 14,189 16.0 994 65 25,001 to 50,000 332 11,917 11,327 35.9 1,052 72 50,001 to 100,000 199 13,918 12,345 69.9 1,127 80 100,001 to 200,000 90 12,415 11,310 137.9 1,098 89 200,001 to 500,000 38 10,724 10,356 284.2 1,035 99 Over 500,000 8 7,074 9,196 885.0 769 117 Principal building activity Education 389 12,239 10,885 31.5 1,124 53 Food sales 177 1,252 1,172 7.1 1,067 121 Food
U.S. Energy Information Administration (EIA) (indexed site)
1,001 to 5,000 2,777 8,041 10,232 2.9 786 56 5,001 to 10,000 1,229 8,900 9,225 7.2 965 62 10,001 to 25,000 884 14,105 14,189 16.0 994 65 25,001 to 50,000 332 11,917 11,327 35.9 1,052 72 50,001 to 100,000 199 13,918 12,345 69.9 1,127 80 100,001 to 200,000 90 12,415 11,310 137.9 1,098 89 200,001 to 500,000 38 10,724 10,356 284.2 1,035 99 Over 500,000 8 7,074 9,196 885.0 769 117 Principal building activity Education 389 12,239 10,885 31.5 1,124 53 Food sales 177 1,252 1,172 7.1 1,067 121 Food
U.S. Energy Information Administration (EIA) (indexed site)
Median square feet per building (thousand) Median square feet per worker Median operating hours per week Median age of buildings (years) All buildings 5,557 87,093 88,182 5.0 1,029 50 32 Building floorspace (square feet) 1,001 to 5,000 2,777 8,041 10,232 2.8 821 49 37 5,001 to 10,000 1,229 8,900 9,225 7.0 1,167 50 31 10,001 to 25,000 884 14,105 14,189 15.0 1,444 56 32 25,001 to 50,000 332 11,917 11,327 35.0 1,461 60 29 50,001 to 100,000 199 13,918 12,345 67.0 1,442 60 26 100,001 to 200,000 90
Total..........................................................
U.S. Energy Information Administration (EIA) (indexed site)
... Housing Units (millions) UrbanRural Location (as Self-Reported) Living Space ... Housing Units (millions) UrbanRural Location (as Self-Reported) Living Space ...
Total..........................................................
U.S. Energy Information Administration (EIA) (indexed site)
... Housing Units (millions) UrbanRural Location (as Self-Reported) City Town Suburbs Rural ... Housing Units (millions) UrbanRural Location (as Self-Reported) City Town Suburbs Rural ...
Total..........................................................
Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 ...
Total..........................................................
Gasoline and Diesel Fuel Update
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 ...
Total..........................................................
U.S. Energy Information Administration (EIA) (indexed site)
... Per Household Member Average Square Feet Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC1.2.2 ...
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 ...
Total..........................................................
U.S. Energy Information Administration (EIA) (indexed site)
... 41.8 2,603 2,199 1,654 941 795 598 1-Car Garage...... 9.5 2,064 1,664 1,039 775 624 390 2-Car Garage......
Total..........................................................
... Average Square Feet per Apartment in a -- Apartments (millions) Major Outside Wall Construction Siding (Aluminum, Vinyl, Steel)...... 35.3 3.5 1,286 1,090 325 852 786 461 ...
Total..........................................................
U.S. Energy Information Administration (EIA) (indexed site)
... Type of Renter-Occupied Housing Unit Housing Units (millions) Single-Family Units ... At Home Behavior Home Used for Business Yes......
Total..........................................................
U.S. Energy Information Administration (EIA) (indexed site)
... Type of Owner-Occupied Housing Unit U.S. Housing Units (millions) Single-Family Units ... At Home Behavior Home Used for Business Yes......
Total..........................................................
U.S. Energy Information Administration (EIA) (indexed site)
... Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table ... At Home Behavior Home Used for Business Yes......
Method and apparatus for charged particle propagation
Hershcovitch, A.
1996-11-26
A method and apparatus are provided for propagating charged particles from a vacuum to a higher pressure region. A generator includes an evacuated chamber having a gun for discharging a beam of charged particles such as an electron beam or ion beam. The beam is discharged through a beam exit in the chamber into a higher pressure region. A plasma interface is disposed at the beam exit and includes a plasma channel for bounding a plasma maintainable between a cathode and an anode disposed at opposite ends thereof. The plasma channel is coaxially aligned with the beam exit for propagating the beam from the chamber, through the plasma, and into the higher pressure region. The plasma is effective for pumping down the beam exit for preventing pressure increase in the chamber and provides magnetic focusing of the beam discharged into the higher pressure region 24. 7 figs.
Crack growth and propagation in metallic alloys
Morrey, W.C.; Wille, L.T.
1996-12-01
Using large-scale molecular dynamics simulation on a massively parallel computer, the authors have studied the initiation of cracking in a Monel-like alloy of Cu-Ni. In a low temperature 2D sample, fracture from a notch starts at a little beyond 2.5% critical strain when the propagation direction is perpendicular to a cleavage plane. The authors discuss a method of characterizing crack tip position using a measure of area around the crack tip.
Donaire, M.
2011-02-15
We offer a unified approach to several phenomena related to the electromagnetic vacuum of a complex medium made of point electric dipoles. To this aim, we apply the linear response theory to the computation of the polarization field propagator and study the spectrum of vacuum fluctuations. The physical distinction among the local density of states which enter the spectra of light propagation, total dipole emission, coherent emission, total vacuum energy, and Schwinger-bulk energy is made clear. Analytical expressions for the spectrum of dipole emission and for the vacuum energy are derived. Their respective relations with the spectrum of external light and with the Schwinger-bulk energy are found. The light spectrum and the Schwinger-bulk energy are determined by the Dyson propagator. The emission spectrum and the total vacuum energy are determined by the polarization propagator. An exact relationship of proportionality between both propagators is found in terms of local field factors. A study of the nature of stimulated emission from a single dipole is carried out. Regarding coherent emission, it contains two components. A direct one which is transferred radiatively and directly from the emitter into the medium and whose spectrum is that of external light. And an indirect one which is radiated by induced dipoles. The induction is mediated by one (and only one) local field factor. Regarding the vacuum energy, we find that in addition to the Schwinger-bulk energy the vacuum energy of an effective medium contains local field contributions proportional to the resonant frequency and to the spectral line width.
Uncertainty in BWR power during ATWS events
Diamond, D.J.
1986-01-01
A study was undertaken to improve our understanding of BWR conditions following the closure of main steam isolation valves and the failure of reactor trip. Of particular interest was the power during the period when the core had reached a quasi-equilibrium condition with a natural circulation flow rate determined by the water level in the downcomer. Insights into the uncertainity in the calculation of this power with sophisticated computer codes were quantified using a simple model which relates power to the principal thermal-hydraulic variables and reactivity coefficients; the latter representing the link between the thermal-hydraulics and the neutronics. Assumptions regarding the uncertainty in these variables and coefficients were then used to determine the uncertainty in power.
On solar geoengineering and climate uncertainty
MacMartin, Douglas; Kravitz, Benjamin S.; Rasch, Philip J.
2015-09-03
Uncertainty in the climate system response has been raised as a concern regarding solar geoengineering. Here we show that model projections of regional climate change outcomes may have greater agreement under solar geoengineering than with CO2 alone. We explore the effects of geoengineering on one source of climate system uncertainty by evaluating the inter-model spread across 12 climate models participating in the Geoengineering Model Intercomparison project (GeoMIP). The model spread in regional temperature and precipitation changes is reduced with CO2 and a solar reduction, in comparison to the case with increased CO2 alone. That is, the intermodel spread in predictions of climate change and the model spread in the response to solar geoengineering are not additive but rather partially cancel. Furthermore, differences in efficacy explain most of the differences between models in their temperature response to an increase in CO2 that is offset by a solar reduction. These conclusions are important for clarifying geoengineering risks.
McDonnell, J. D.; Schunck, N.; Higdon, D.; Sarich, J.; Wild, S. M.; Nazarewicz, W.
2015-03-24
Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squares optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. In addition, the example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.
McDonnell, J. D.; Schunck, N.; Higdon, D.; Sarich, J.; Wild, S. M.; Nazarewicz, W.
2015-03-24
Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squares optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. As a result, the example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.
Salloum, Maher N.; Gharagozloo, Patricia E.
2013-10-01
Metal particle beds have recently become a major technique for hydrogen storage. In order to extract hydrogen from such beds, it is crucial to understand the decomposition kinetics of the metal hydride. We are interested in obtaining a a better understanding of the uranium hydride (UH3) decomposition kinetics. We first developed an empirical model by fitting data compiled from different experimental studies in the literature and quantified the uncertainty resulting from the scattered data. We found that the decomposition time range predicted by the obtained kinetics was in a good agreement with published experimental results. Secondly, we developed a physics based mathematical model to simulate the rate of hydrogen diffusion in a hydride particle during the decomposition. We used this model to simulate the decomposition of the particles for temperatures ranging from 300K to 1000K while propagating parametric uncertainty and evaluated the kinetics from the results. We compared the kinetics parameters derived from the empirical and physics based models and found that the uncertainty in the kinetics predicted by the physics based model covers the scattered experimental data. Finally, we used the physics-based kinetics parameters to simulate the effects of boundary resistances and powder morphological changes during decomposition in a continuum level model. We found that the species change within the bed occurring during the decomposition accelerates the hydrogen flow by increasing the bed permeability, while the pressure buildup and the thermal barrier forming at the wall significantly impede the hydrogen extraction.
McDonnell, J. D.; Schunck, N.; Higdon, D.; Sarich, J.; Wild, S. M.; Nazarewicz, W.
2015-03-24
Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squaresmore » optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. In addition, the example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.« less
Al-Hashimi, M.H. Wiese, U.-J.
2009-12-15
We consider wave packets of free particles with a general energy-momentum dispersion relation E(p). The spreading of the wave packet is determined by the velocity v={partial_derivative}{sub p}E. The position-velocity uncertainty relation {delta}x{delta}v{>=}1/2 |<{partial_derivative}{sub p}{sup 2}E>| is saturated by minimal uncertainty wave packets {phi}(p)=Aexp(-{alpha}E(p)+{beta}p). In addition to the standard minimal Gaussian wave packets corresponding to the non-relativistic dispersion relation E(p)=p{sup 2}/2m, analytic calculations are presented for the spreading of wave packets with minimal position-velocity uncertainty product for the lattice dispersion relation E(p)=-cos(pa)/ma{sup 2} as well as for the relativistic dispersion relation E(p)={radical}(p{sup 2}+m{sup 2}). The boost properties of moving relativistic wave packets as well as the propagation of wave packets in an expanding Universe are also discussed.
Quantifying uncertainty in stable isotope mixing models
Davis, Paul; Syme, James; Heikoop, Jeffrey; Fessenden-Rahn, Julianna; Perkins, George; Newman, Brent; Chrystal, Abbey E.; Hagerty, Shannon B.
2015-05-19
Mixing models are powerful tools for identifying biogeochemical sources and determining mixing fractions in a sample. However, identification of actual source contributors is often not simple, and source compositions typically vary or even overlap, significantly increasing model uncertainty in calculated mixing fractions. This study compares three probabilistic methods, SIAR [Parnell et al., 2010] a pure Monte Carlo technique (PMC), and Stable Isotope Reference Source (SIRS) mixing model, a new technique that estimates mixing in systems with more than three sources and/or uncertain source compositions. In this paper, we use nitrate stable isotope examples (δ15N and δ18O) but all methods testedmore » are applicable to other tracers. In Phase I of a three-phase blind test, we compared methods for a set of six-source nitrate problems. PMC was unable to find solutions for two of the target water samples. The Bayesian method, SIAR, experienced anchoring problems, and SIRS calculated mixing fractions that most closely approximated the known mixing fractions. For that reason, SIRS was the only approach used in the next phase of testing. In Phase II, the problem was broadened where any subset of the six sources could be a possible solution to the mixing problem. Results showed a high rate of Type I errors where solutions included sources that were not contributing to the sample. In Phase III some sources were eliminated based on assumed site knowledge and assumed nitrate concentrations, substantially reduced mixing fraction uncertainties and lowered the Type I error rate. These results demonstrate that valuable insights into stable isotope mixing problems result from probabilistic mixing model approaches like SIRS. The results also emphasize the importance of identifying a minimal set of potential sources and quantifying uncertainties in source isotopic composition as well as demonstrating the value of additional information in reducing the uncertainty in calculated
Uncertainty estimates for derivatives and intercepts
Clark, E.L.
1994-09-01
Straight line least squares fits of experimental data are widely used in the analysis of test results to provide derivatives and intercepts. A method for evaluating the uncertainty in these parameters is described. The method utilizes conventional least squares results and is applicable to experiments where the independent variable is controlled, but not necessarily free of error. A Monte Carlo verification of the method is given.
Quantifying uncertainty in stable isotope mixing models
Davis, Paul; Syme, James; Heikoop, Jeffrey; Fessenden-Rahn, Julianna; Perkins, George; Newman, Brent; Chrystal, Abbey E.; Hagerty, Shannon B.
2015-05-19
Mixing models are powerful tools for identifying biogeochemical sources and determining mixing fractions in a sample. However, identification of actual source contributors is often not simple, and source compositions typically vary or even overlap, significantly increasing model uncertainty in calculated mixing fractions. This study compares three probabilistic methods, SIAR [Parnell et al., 2010] a pure Monte Carlo technique (PMC), and Stable Isotope Reference Source (SIRS) mixing model, a new technique that estimates mixing in systems with more than three sources and/or uncertain source compositions. In this paper, we use nitrate stable isotope examples (?^{15}N and ?^{18}O) but all methods tested are applicable to other tracers. In Phase I of a three-phase blind test, we compared methods for a set of six-source nitrate problems. PMC was unable to find solutions for two of the target water samples. The Bayesian method, SIAR, experienced anchoring problems, and SIRS calculated mixing fractions that most closely approximated the known mixing fractions. For that reason, SIRS was the only approach used in the next phase of testing. In Phase II, the problem was broadened where any subset of the six sources could be a possible solution to the mixing problem. Results showed a high rate of Type I errors where solutions included sources that were not contributing to the sample. In Phase III some sources were eliminated based on assumed site knowledge and assumed nitrate concentrations, substantially reduced mixing fraction uncertainties and lowered the Type I error rate. These results demonstrate that valuable insights into stable isotope mixing problems result from probabilistic mixing model approaches like SIRS. The results also emphasize the importance of identifying a minimal set of potential sources and quantifying uncertainties in source isotopic composition as well as demonstrating the value of additional information in reducing the
Quantifying uncertainty in stable isotope mixing models
Davis, Paul; Syme, James; Heikoop, Jeffrey; Fessenden-Rahn, Julianna; Perkins, George; Newman, Brent; Chrystal, Abbey E.; Hagerty, Shannon B.
2015-05-19
Mixing models are powerful tools for identifying biogeochemical sources and determining mixing fractions in a sample. However, identification of actual source contributors is often not simple, and source compositions typically vary or even overlap, significantly increasing model uncertainty in calculated mixing fractions. This study compares three probabilistic methods, SIAR [Parnell et al., 2010] a pure Monte Carlo technique (PMC), and Stable Isotope Reference Source (SIRS) mixing model, a new technique that estimates mixing in systems with more than three sources and/or uncertain source compositions. In this paper, we use nitrate stable isotope examples (δ^{15}N and δ^{18}O) but all methods tested are applicable to other tracers. In Phase I of a three-phase blind test, we compared methods for a set of six-source nitrate problems. PMC was unable to find solutions for two of the target water samples. The Bayesian method, SIAR, experienced anchoring problems, and SIRS calculated mixing fractions that most closely approximated the known mixing fractions. For that reason, SIRS was the only approach used in the next phase of testing. In Phase II, the problem was broadened where any subset of the six sources could be a possible solution to the mixing problem. Results showed a high rate of Type I errors where solutions included sources that were not contributing to the sample. In Phase III some sources were eliminated based on assumed site knowledge and assumed nitrate concentrations, substantially reduced mixing fraction uncertainties and lowered the Type I error rate. These results demonstrate that valuable insights into stable isotope mixing problems result from probabilistic mixing model approaches like SIRS. The results also emphasize the importance of identifying a minimal set of potential sources and quantifying uncertainties in source isotopic composition as well as demonstrating the value of additional information in reducing the
Interpolation Uncertainties Across the ARM SGP Area
U.S. Department of Energy (DOE) all webpages (Extended Search)
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
Uncertainties in risk assessment at USDOE facilities
Hamilton, L.D.; Holtzman, S.; Meinhold, A.F.; Morris, S.C.; Rowe, M.D.
1994-01-01
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.
Representation of analysis results involving aleatory and epistemic uncertainty.
Johnson, Jay Dean; Helton, Jon Craig; Oberkampf, William Louis; Sallaberry, Cedric J.
2008-08-01
Procedures are described for the representation of results in analyses that involve both aleatory uncertainty and epistemic uncertainty, with aleatory uncertainty deriving from an inherent randomness in the behavior of the system under study and epistemic uncertainty deriving from a lack of knowledge about the appropriate values to use for quantities that are assumed to have fixed but poorly known values in the context of a specific study. Aleatory uncertainty is usually represented with probability and leads to cumulative distribution functions (CDFs) or complementary cumulative distribution functions (CCDFs) for analysis results of interest. Several mathematical structures are available for the representation of epistemic uncertainty, including interval analysis, possibility theory, evidence theory and probability theory. In the presence of epistemic uncertainty, there is not a single CDF or CCDF for a given analysis result. Rather, there is a family of CDFs and a corresponding family of CCDFs that derive from epistemic uncertainty and have an uncertainty structure that derives from the particular uncertainty structure (i.e., interval analysis, possibility theory, evidence theory, probability theory) used to represent epistemic uncertainty. Graphical formats for the representation of epistemic uncertainty in families of CDFs and CCDFs are investigated and presented for the indicated characterizations of epistemic uncertainty.
Uncertainty Analysis for a Virtual Flow Meter Using an Air-Handling Unit Chilled Water Valve
Song, Li; Wang, Gang; Brambley, Michael R.
2013-04-28
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.
An Empirical Study of Infrasonic Propagation
J. Paul Mutschlecner; Rodney W. Whitaker; Lawrence H. Auer
1999-10-01
Observations of atmospheric nuclear tests carried out at the Nevada Test Site from 1951 to 1958 provided data for an empirical investigation of how infrasonic signals are propagated to distances of about 250 km. Those observations and the analysis documented in this report involved signal amplitudes and average velocities and included three classes of signals: stratospheric, thermospheric, and tropospheric/surface. The authors' analysis showed that stratospheric winds have a dominant effect upon stratospheric signal amplitudes. The report outlines a method for normalizing stratospheric signal amplitudes for the effects of upper atmospheric winds and presents equations for predicting or normalizing amplitude and average velocity for the three types of signals.
October 16, 2014 Webinar - Decisional Analysis under Uncertainty |
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
Department of Energy 6, 2014 Webinar - Decisional Analysis under Uncertainty October 16, 2014 Webinar - Decisional Analysis under Uncertainty Webinar - October 16, 2014, 11 am - 12:40 pm EDT: Dr. Paul Black (Neptune, Inc), Decisional Analysis under Uncertainty Agenda - October 16, 2014 - P&RA CoP Webinar (59.42 KB) Presentation - Decision Making under Uncertainty: Introduction to Structured Decision Analysis for Performance Assessments (4.02 MB) More Documents & Publications Status
Brown, J.; Goossens, L.H.J.; Kraan, B.C.P.
1997-06-01
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.
HPC Analytics Support. Requirements for Uncertainty Quantification Benchmarks
Paulson, Patrick R.; Purohit, Sumit; Rodriguez, Luke R.
2015-05-01
This report outlines techniques for extending benchmark generation products so they support uncertainty quantification by benchmarked systems. We describe how uncertainty quantification requirements can be presented to candidate analytical tools supporting SPARQL. We describe benchmark data sets for evaluating uncertainty quantification, as well as an approach for using our benchmark generator to produce data sets for generating benchmark data sets.
Entropic uncertainty relations in multidimensional position and momentum spaces
Huang Yichen
2011-05-15
Commutator-based entropic uncertainty relations in multidimensional position and momentum spaces are derived, twofold generalizing previous entropic uncertainty relations for one-mode states. They provide optimal lower bounds and imply the multidimensional variance-based uncertainty principle. The article concludes with an open conjecture.
Neutrino emission in the jet propagation process
Xiao, D.; Dai, Z. G.
2014-07-20
Relativistic jets are universal in long-duration gamma-ray burst (GRB) models. Before breaking out, they must propagate in the progenitor envelope along with a forward shock and a reverse shock forming at the jet head. Both electrons and protons will be accelerated by the shocks. High-energy neutrinos could be produced by these protons interacting with stellar materials and electron-radiating photons. The jet will probably be collimated, which may have a strong effect on the final neutrino flux. Under the assumption of a power-law stellar-envelope density profile ??r {sup ?} with index ?, we calculate the neutrino emission flux by these shocks for low-luminosity GRBs (LL-GRBs) and ultra-long GRBs (UL-GRBs) in different collimation regimes, using the jet propagation framework developed by Bromberg et al. We find that LL-GRBs and UL-GRBs are capable of producing detectable high-energy neutrinos up to ?PeV, from which the final neutrino spectrum can be obtained. Further, we conclude that a larger ? corresponds to greater neutrino flux at the high-energy end (?PeV) and to higher maximum neutrino energy as well. However, such differences are so small that it is not promising for us to be able to distinguish these in observations, given the energy resolution we have now.
Method and apparatus for charged particle propagation
Hershcovitch, Ady
1996-11-26
A method and apparatus are provided for propagating charged particles from a vacuum to a higher pressure region. A generator 14,14b includes an evacuated chamber 16a,b having a gun 18,18b for discharging a beam of charged particles such as an electron beam 12 or ion beam 12b. The beam 12,12b is discharged through a beam exit 22 in the chamber 16a,b into a higher pressure region 24. A plasma interface 34 is disposed at the beam exit 22 and includes a plasma channel 38 for bounding a plasma 40 maintainable between a cathode 42 and an anode 44 disposed at opposite ends thereof. The plasma channel 38 is coaxially aligned with the beam exit 22 for propagating the beam 12,12b from the chamber 16a,b, through the plasma 40, and into the higher pressure region 24. The plasma 40 is effective for pumping down the beam exit 22 for preventing pressure increase in the chamber 16a,b, and provides magnetic focusing of the beam 12,12b discharged into the higher pressure region 24.
Characteristics RSE Column Factor: Total
U.S. Energy Information Administration (EIA) (indexed site)
and 1994 Vehicle Characteristics RSE Column Factor: Total 1993 Family Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factor: Less than 5,000 5,000...
ARM - Measurement - Total cloud water
U.S. Department of Energy (DOE) all webpages (Extended Search)
cloud water ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total cloud water The total concentration (mass/vol) of ice and liquid water particles in a cloud; this includes condensed water content (CWC). Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a
Tutorial examples for uncertainty quantification methods.
De Bord, Sarah
2015-08-01
This report details the work accomplished during my 2015 SULI summer internship at Sandia National Laboratories in Livermore, CA. During this internship, I worked on multiple tasks with the common goal of making uncertainty quantification (UQ) methods more accessible to the general scientific community. As part of my work, I created a comprehensive numerical integration example to incorporate into the user manual of a UQ software package. Further, I developed examples involving heat transfer through a window to incorporate into tutorial lectures that serve as an introduction to UQ methods.
Microsoft Word - Price Uncertainty Supplement .docx
Gasoline and Diesel Fuel Update
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
Microsoft Word - Price Uncertainty Supplement.doc
Gasoline and Diesel Fuel Update
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
Microsoft Word - Price Uncertainty Supplement.doc
Gasoline and Diesel Fuel Update
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 2010 or about $1 per barrel above the prior month's average, and close to the $77 per barrel projected in last month's Outlook. EIA projects WTI prices will average about $80 per barrel over the second half of this year and rise to $85 by the end of next year (West Texas Intermediate Crude Oil Price Chart). Energy price
Microsoft Word - Price Uncertainty Supplement.doc
Gasoline and Diesel Fuel Update
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
Microsoft Word - Price Uncertainty Supplement.doc
Gasoline and Diesel Fuel Update
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
Microsoft Word - Price Uncertainty Supplement.doc
Gasoline and Diesel Fuel Update
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
Microsoft Word - Price Uncertainty Supplement.doc
Gasoline and Diesel Fuel Update
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,
Microsoft Word - Price Uncertainty Supplement.doc
Gasoline and Diesel Fuel Update
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
Microsoft Word - Price Uncertainty Supplement.doc
Gasoline and Diesel Fuel Update
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
Microsoft Word - Price Uncertainty Supplement.doc
Gasoline and Diesel Fuel Update
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
Haihua Zhao; Vincent A. Mousseau; Nam T. Dinh
2010-10-01
Code Scaling, Applicability, and Uncertainty (CSAU) methodology was developed in late 1980s by US NRC to systematically quantify reactor simulation uncertainty. Basing on CSAU methodology, Best Estimate Plus Uncertainty (BEPU) methods have been developed and widely used for new reactor designs and existing LWRs power uprate. In spite of these successes, several aspects of CSAU have been criticized for further improvement: i.e., (1) subjective judgement in PIRT process; (2) high cost due to heavily relying large experimental database, needing many experts man-years work, and very high computational overhead; (3) mixing numerical errors with other uncertainties; (4) grid dependence and same numerical grids for both scaled experiments and real plants applications; (5) user effects; Although large amount of efforts have been used to improve CSAU methodology, the above issues still exist. With the effort to develop next generation safety analysis codes, new opportunities appear to take advantage of new numerical methods, better physical models, and modern uncertainty qualification methods. Forward sensitivity analysis (FSA) directly solves the PDEs for parameter sensitivities (defined as the differential of physical solution with respective to any constant parameter). When the parameter sensitivities are available in a new advanced system analysis code, CSAU could be significantly improved: (1) Quantifying numerical errors: New codes which are totally implicit and with higher order accuracy can run much faster with numerical errors quantified by FSA. (2) Quantitative PIRT (Q-PIRT) to reduce subjective judgement and improving efficiency: treat numerical errors as special sensitivities against other physical uncertainties; only parameters having large uncertainty effects on design criterions are considered. (3) Greatly reducing computational costs for uncertainty qualification by (a) choosing optimized time steps and spatial sizes; (b) using gradient information
SWEPP PAN assay system uncertainty analysis: Passive mode measurements of graphite waste
Blackwood, L.G.; Harker, Y.D.; Meachum, T.R.; Yoon, Woo Y.
1997-07-01
The Idaho National Engineering and Environmental Laboratory is being used as a temporary storage facility for transuranic waste generated by the U.S. Nuclear Weapons program at the Rocky Flats Plant (RFP) in Golden, Colorado. Currently, there is a large effort in progress to prepare to ship this waste to the Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico. In order to meet the TRU Waste Characterization Quality Assurance Program Plan nondestructive assay compliance requirements and quality assurance objectives, it is necessary to determine the total uncertainty of the radioassay results produced by the Stored Waste Examination Pilot Plant (SWEPP) Passive Active Neutron (PAN) radioassay system. To this end a modified statistical sampling and verification approach has been developed to determine the total uncertainty of a PAN measurement. In this approach the total performance of the PAN nondestructive assay system is simulated using computer models of the assay system and the resultant output is compared with the known input to assess the total uncertainty. This paper is one of a series of reports quantifying the results of the uncertainty analysis of the PAN system measurements for specific waste types and measurement modes. In particular this report covers passive mode measurements of weapons grade plutonium-contaminated graphite molds contained in 208 liter drums (waste code 300). The validity of the simulation approach is verified by comparing simulated output against results from measurements using known plutonium sources and a surrogate graphite waste form drum. For actual graphite waste form conditions, a set of 50 cases covering a statistical sampling of the conditions exhibited in graphite wastes was compiled using a Latin hypercube statistical sampling approach.
Adaptive strategies for materials design using uncertainties
Balachandran, Prasanna V.; Xue, Dezhen; Theiler, James; Hogden, John; Lookman, Turab
2016-01-21
Here, we compare several adaptive design strategies using a data set of 223 M2AX family of compounds for which the elastic properties [bulk (B), shear (G), and Young’s (E) modulus] have been computed using density functional theory. The design strategies are decomposed into an iterative loop with two main steps: machine learning is used to train a regressor that predicts elastic properties in terms of elementary orbital radii of the individual components of the materials; and a selector uses these predictions and their uncertainties to choose the next material to investigate. The ultimate goal is to obtain a material withmore » desired elastic properties in as few iterations as possible. We examine how the choice of data set size, regressor and selector impact the design. We find that selectors that use information about the prediction uncertainty outperform those that don’t. Our work is a step in illustrating how adaptive design tools can guide the search for new materials with desired properties.« less
Uncertainty Budget Analysis for Dimensional Inspection Processes (U)
Valdez, Lucas M.
2012-07-26
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.
Digital reverse propagation in focusing Kerr media
Goy, Alexandre; Psaltis, Demetri
2011-03-15
Lenses allow the formation of clear images in homogeneous linear media. Holography is an alternative imaging method, but its use is limited to cases in which it provides an advantage, such as three-dimensional imaging. In nonlinear media, lenses no longer work. The light produces intensity-dependent aberrations. The reverse propagation method used in digital holography to form images from recorded holograms works even in Kerr media [M. Tsang, D. Psaltis, and F. G. Omenetto, Opt. Lett. 28, 1873 (2003).]. The principle has been experimentally demonstrated recently in defocusing media [C. Barsi, W.Wan, and J.W. Fleischer, Nat. Photonics 3, 211 (2009).]. Here, we report experimental results in focusing media.
Estimating Failure Propagation in Models of Cascading Blackouts
Dobson, Ian [University of Wisconsin, Madison; Carreras, Benjamin A [ORNL; Lynch, Vickie E [ORNL; Nkei, Bertrand [ORNL; Newman, David E [University of Alaska
2005-09-01
We compare and test statistical estimates of failure propagation in data from versions of a probabilistic model of loading-dependent cascading failure and a power systems blackout model of cascading transmission line overloads. The comparisons suggest mechanisms affecting failure propagation and are an initial step towards monitoring failure propagation from practical system data. Approximations to the probabilistic model describe the forms of probability distributions of cascade sizes.
Complete LQG propagator. II. Asymptotic behavior of the vertex
Alesci, Emanuele; Rovelli, Carlo
2008-02-15
In a previous article we have shown that there are difficulties in obtaining the correct graviton propagator from the loop-quantum-gravity dynamics defined by the Barrett-Crane vertex amplitude. Here we show that a vertex amplitude that depends nontrivially on the intertwiners can yield the correct propagator. We give an explicit example of asymptotic behavior of a vertex amplitude that gives the correct full graviton propagator in the large distance limit.
Survey and Evaluate Uncertainty Quantification Methodologies
Lin, Guang; Engel, David W.; Eslinger, Paul W.
2012-02-01
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
Wave Energy Converter Effects on Nearshore Wave Propagation
U.S. Department of Energy (DOE) all webpages (Extended Search)
Energy Converter Effects on Nearshore Wave Propagation Jesse Roberts 1 , Grace Chang *2 , Craig Jones *3 Sandia National Laboratories 1515 Eubank SE, Albuquerque, NM 87123 USA 1...
Experimental X-ray characterization of Gekko XII laser propagation...
Office of Scientific and Technical Information (OSTI)
Experimental X-ray characterization of Gekko XII laser propagation through very low ... Citation Details In-Document Search Title: Experimental X-ray characterization of Gekko ...
Wave Propagation and Dispersion in Elasto-Plastic Microstructured...
Office of Scientific and Technical Information (OSTI)
Title: Wave Propagation and Dispersion in Elasto-Plastic Microstructured Materials. Abstract not provided. Authors: Dingreville, Remi Philippe Michel ; Robbins, Joshua ; Voth, ...
Supersonic Heat Wave Propagation in Laser-Produced Underdense...
Office of Scientific and Technical Information (OSTI)
Conference: Supersonic Heat Wave Propagation in Laser-Produced Underdense Plasma for Efficient X-Ray Generation Citation Details In-Document Search Title: Supersonic Heat Wave...
The Interplay Between Surface Hydrogen and Defect Propagation...
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The Interplay Between Surface Hydrogen and Defect Propagation in Si Nanowire Kinking Superstructures Citation Details In-Document Search Title: The Interplay Between Surface ...
Wave propagation in anisotropic elastic materials and curvilinear...
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Journal Article: Wave propagation in anisotropic elastic materials and curvilinear coordinates using a summation-by-parts finite difference method Citation Details In-Document...
Wave propagation in anisotropic elastic materials and curvilinear...
Office of Scientific and Technical Information (OSTI)
Wave propagation in anisotropic elastic materials and curvilinear coordinates using a summation-by-parts finite difference method Citation Details In-Document Search Title: Wave...
CATEGORY Total Procurement Total Small Business Small Disadvantaged
National Nuclear Security Administration (NNSA)
CATEGORY Total Procurement Total Small Business Small Disadvantaged Business Woman Owned Small Business HubZone Small Business Veteran-Owned Small Business Service Disabled Veteran Owned Small Business FY 2013 Dollars Accomplished $1,049,087,940 $562,676,028 $136,485,766 $106,515,229 $12,080,258 $63,473,852 $28,080,960 FY 2013 % Accomplishment 54.40% 13.00% 10.20% 1.20% 6.60% 2.70% FY 2014 Dollars Accomplished $868,961,755 $443,711,175 $92,478,522 $88,633,031 $29,867,820 $43,719,452 $26,826,374
Radiotherapy Dose Fractionation under Parameter Uncertainty
Davison, Matt; Kim, Daero; Keller, Harald
2011-11-30
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.
Intrinsic Uncertainties in Modeling Complex Systems.
Cooper, Curtis S; Bramson, Aaron L.; Ames, Arlo L.
2014-09-01
Models are built to understand and predict the behaviors of both natural and artificial systems. Because it is always necessary to abstract away aspects of any non-trivial system being modeled, we know models can potentially leave out important, even critical elements. This reality of the modeling enterprise forces us to consider the prospective impacts of those effects completely left out of a model - either intentionally or unconsidered. Insensitivity to new structure is an indication of diminishing returns. In this work, we represent a hypothetical unknown effect on a validated model as a finite perturba- tion whose amplitude is constrained within a control region. We find robustly that without further constraints, no meaningful bounds can be placed on the amplitude of a perturbation outside of the control region. Thus, forecasting into unsampled regions is a very risky proposition. We also present inherent difficulties with proper time discretization of models and representing in- herently discrete quantities. We point out potentially worrisome uncertainties, arising from math- ematical formulation alone, which modelers can inadvertently introduce into models of complex systems. Acknowledgements This work has been funded under early-career LDRD project %23170979, entitled %22Quantify- ing Confidence in Complex Systems Models Having Structural Uncertainties%22, which ran from 04/2013 to 09/2014. We wish to express our gratitude to the many researchers at Sandia who con- tributed ideas to this work, as well as feedback on the manuscript. In particular, we would like to mention George Barr, Alexander Outkin, Walt Beyeler, Eric Vugrin, and Laura Swiler for provid- ing invaluable advice and guidance through the course of the project. We would also like to thank Steven Kleban, Amanda Gonzales, Trevor Manzanares, and Sarah Burwell for their assistance in managing project tasks and resources.
ENERGY CONTENT AND PROPAGATION IN TRANSVERSE SOLAR ATMOSPHERIC WAVES
Goossens, M.; Van Doorsselaere, T.; Soler, R.; Verth, G.
2013-05-10
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.
Maximum-likelihood fitting of data dominated by Poisson statistical uncertainties
Stoneking, M.R.; Den Hartog, D.J.
1996-06-01
The fitting of data by {chi}{sup 2}-minimization is valid only when the uncertainties in the data are normally distributed. When analyzing spectroscopic or particle counting data at very low signal level (e.g., a Thomson scattering diagnostic), the uncertainties are distributed with a Poisson distribution. The authors have developed a maximum-likelihood method for fitting data that correctly treats the Poisson statistical character of the uncertainties. This method maximizes the total probability that the observed data are drawn from the assumed fit function using the Poisson probability function to determine the probability for each data point. The algorithm also returns uncertainty estimates for the fit parameters. They compare this method with a {chi}{sup 2}-minimization routine applied to both simulated and real data. Differences in the returned fits are greater at low signal level (less than {approximately}20 counts per measurement). the maximum-likelihood method is found to be more accurate and robust, returning a narrower distribution of values for the fit parameters with fewer outliers.
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
0 New Hampshire - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle ...
Helton, J.C.; Johnson, J.D.; Rollstin, J.A.; Shiver, A.W.; Sprung, J.L.
1995-01-01
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.
Total Number of Operable Refineries
U.S. Energy Information Administration (EIA) (indexed site)
Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge
Total Estimated Contract Cost: Performance Period Total Fee Paid
Office of Environmental Management (EM)
Performance Period Total Fee Paid FY2008 $134,832 FY2009 $142,578 FY2010 $299,878 FY2011 $169,878 Cumulative Fee Paid $747,166 Contract Period: September 2007 - October 2012 $31,885,815 C/P/E Environmental Services, LLC DE-AM09-05SR22405/DE-AT30-07CC60011/SL14 Contractor: Contract Number: Contract Type: Cost Plus Award Fee $357,223 $597,797 $894,699 EM Contractor Fee Site: Stanford Linear Accelerator Center (SLAC) Contract Name: SLAC Environmental Remediation December 2012 $1,516,646 Fee
Entanglement criteria via concave-function uncertainty relations
Huang Yichen
2010-07-15
A general theorem as a necessary condition for the separability of quantum states in both finite and infinite dimensional systems, based on concave-function uncertainty relations, is derived. Two special cases of the general theorem are stronger than two known entanglement criteria based on the Shannon entropic uncertainty relation and the Landau-Pollak uncertainty relation, respectively; other special cases are able to detect entanglement where some famous entanglement criteria fail.
Results for Phase I of the IAEA Coordinated Research Program on HTGR Uncertainties
Strydom, Gerhard; Bostelmann, Friederike; Yoon, Su Jong
2015-01-01
The quantification of uncertainties in design and safety analysis of reactors is today not only broadly accepted, but in many cases became the preferred way to replace traditional conservative analysis for safety and licensing analysis. The use of a more fundamental methodology is also consistent with the reliable high fidelity physics models and robust, efficient, and accurate codes available today. To facilitate uncertainty analysis applications a comprehensive approach and methodology must be developed and applied. High Temperature Gas-cooled Reactors (HTGR) has its own peculiarities, coated particle design, large graphite quantities, different materials and high temperatures that also require other simulation requirements. The IAEA has therefore launched a Coordinated Research Project (CRP) on the HTGR Uncertainty Analysis in Modeling (UAM) in 2013 to study uncertainty propagation specifically in the HTGR analysis chain. Two benchmark problems are defined, with the prismatic design represented by the General Atomics (GA) MHTGR-350 and a 250 MW modular pebble bed design similar to the HTR-PM (INET, China). This report summarizes the contributions of the HTGR Methods Simulation group at Idaho National Laboratory (INL) up to this point of the CRP. The activities at INL have been focused so far on creating the problem specifications for the prismatic design, as well as providing reference solutions for the exercises defined for Phase I. An overview is provided of the HTGR UAM objectives and scope, and the detailed specifications for Exercises I-1, I-2, I-3 and I-4 are also included here for completeness. The main focus of the report is the compilation and discussion of reference results for Phase I (i.e. for input parameters at their nominal or best-estimate values), which is defined as the first step of the uncertainty quantification process. These reference results can be used by other CRP participants for comparison with other codes or their own reference
Improvements to Nuclear Data and Its Uncertainties by Theoretical...
Office of Scientific and Technical Information (OSTI)
data evaluation process much more accurately, and lead to a new generation of uncertainty quantification files. ... of AFCI. While in the past the design, construction and operation of ...
Improvements of Nuclear Data and Its Uncertainties by Theoretical...
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Improvements of Nuclear Data and Its Uncertainties by Theoretical Modeling Talou, Patrick Los Alamos National Laboratory; Nazarewicz, Witold University of Tennessee, Knoxville,...
A density-matching approach for optimization under uncertainty...
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A density-matching approach for optimization under uncertainty Citation Details ... Journal Name: Computer Methods in Applied Mechanics and Engineering Additional Journal ...
Early solar mass loss, opacity uncertainties, and the solar abundance...
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Early solar mass loss, opacity uncertainties, and the solar abundance problem Citation ... Visit OSTI to utilize additional information resources in energy science and technology. A ...
Estimation of uncertainty for contour method residual stress measurements
Olson, Mitchell D.; DeWald, Adrian T.; Prime, Michael B.; Hill, Michael R.
2014-12-03
This paper describes a methodology for the estimation of measurement uncertainty for the contour method, where the contour method is an experimental technique for measuring a two-dimensional map of residual stress over a plane. Random error sources including the error arising from noise in displacement measurements and the smoothing of the displacement surfaces are accounted for in the uncertainty analysis. The output is a two-dimensional, spatially varying uncertainty estimate such that every point on the cross-section where residual stress is determined has a corresponding uncertainty value. Both numerical and physical experiments are reported, which are used to support the usefulness of the proposed uncertainty estimator. The uncertainty estimator shows the contour method to have larger uncertainty near the perimeter of the measurement plane. For the experiments, which were performed on a quenched aluminum bar with a cross section of 51 76 mm, the estimated uncertainty was approximately 5 MPa (?/E = 7 10??) over the majority of the cross-section, with localized areas of higher uncertainty, up to 10 MPa (?/E = 14 10??).
Uncertainty quantification of US Southwest climate from IPCC...
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Title: Uncertainty quantification of US Southwest climate from IPCC projections. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) made extensive ...
Measurement uncertainty analysis techniques applied to PV performance measurements
Wells, C.
1992-10-01
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.
Uncertainties in Air Exchange using Continuous-Injection, Long...
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people to minimize experimental costs. In this article we will conduct a first-principles error analysis to estimate the uncertainties and then compare that analysis to CILTS...
Estimation of uncertainty for contour method residual stress measurements
Olson, Mitchell D.; DeWald, Adrian T.; Prime, Michael B.; Hill, Michael R.
2014-12-03
This paper describes a methodology for the estimation of measurement uncertainty for the contour method, where the contour method is an experimental technique for measuring a two-dimensional map of residual stress over a plane. Random error sources including the error arising from noise in displacement measurements and the smoothing of the displacement surfaces are accounted for in the uncertainty analysis. The output is a two-dimensional, spatially varying uncertainty estimate such that every point on the cross-section where residual stress is determined has a corresponding uncertainty value. Both numerical and physical experiments are reported, which are used to support the usefulness of the proposed uncertainty estimator. The uncertainty estimator shows the contour method to have larger uncertainty near the perimeter of the measurement plane. For the experiments, which were performed on a quenched aluminum bar with a cross section of 51 × 76 mm, the estimated uncertainty was approximately 5 MPa (σ/E = 7 · 10⁻⁵) over the majority of the cross-section, with localized areas of higher uncertainty, up to 10 MPa (σ/E = 14 · 10⁻⁵).
Estimation of uncertainty for contour method residual stress measurements
Olson, Mitchell D.; DeWald, Adrian T.; Prime, Michael B.; Hill, Michael R.
2014-12-03
This paper describes a methodology for the estimation of measurement uncertainty for the contour method, where the contour method is an experimental technique for measuring a two-dimensional map of residual stress over a plane. Random error sources including the error arising from noise in displacement measurements and the smoothing of the displacement surfaces are accounted for in the uncertainty analysis. The output is a two-dimensional, spatially varying uncertainty estimate such that every point on the cross-section where residual stress is determined has a corresponding uncertainty value. Both numerical and physical experiments are reported, which are used to support the usefulnessmore » of the proposed uncertainty estimator. The uncertainty estimator shows the contour method to have larger uncertainty near the perimeter of the measurement plane. For the experiments, which were performed on a quenched aluminum bar with a cross section of 51 × 76 mm, the estimated uncertainty was approximately 5 MPa (σ/E = 7 · 10⁻⁵) over the majority of the cross-section, with localized areas of higher uncertainty, up to 10 MPa (σ/E = 14 · 10⁻⁵).« less
Characterizing Uncertainty for Regional Climate Change Mitigation and Adaptation Decisions
Unwin, Stephen D.; Moss, Richard H.; Rice, Jennie S.; Scott, Michael J.
2011-09-30
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.
Estimation and Uncertainty Analysis of Impacts of Future Heat...
Office of Scientific and Technical Information (OSTI)
However, the estimation of excess mortality attributable to future heat waves is subject to large uncertainties, which have not been examined under the latest greenhouse gas ...
Comparison of Uncertainty of Two Precipitation Prediction Models...
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Prediction Models at Los Alamos National Lab Technical Area 54 Citation Details In-Document Search Title: Comparison of Uncertainty of Two Precipitation Prediction Models ...
Variable Grid Method for Visualizing Uncertainty Associated with...
U.S. Department of Energy (DOE) all webpages (Extended Search)
interpretation. In general, NETL's VGM applies a grid system where the size of the cell represents the uncertainty associated with the original point data sources or their...
Output-Based Error Estimation and Adaptation for Uncertainty...
U.S. Department of Energy (DOE) all webpages (Extended Search)
Output-Based Error Estimation and Adaptation for Uncertainty Quantification Isaac M. Asher and Krzysztof J. Fidkowski University of Michigan US National Congress on Computational...
A Unified Approach for Reporting ARM Measurement Uncertainties...
U.S. Department of Energy (DOE) all webpages (Extended Search)
0 A Unified Approach for Reporting ARM Measurement Uncertainties Technical Report E Campos DL Sisterson October 2015 DISCLAIMER This report was prepared as an account of work ...
Uncertainty Estimates for SIRS, SKYRAD, & GNDRAD Data and Reprocessing...
Office of Scientific and Technical Information (OSTI)
Title: Uncertainty Estimates for SIRS, SKYRAD, & GNDRAD Data and Reprocessing the Pyrgeometer Data (Presentation) The National Renewable Energy Laboratory (NREL) and the ...
Effect of Resolution on Propagating Detonation Wave
Menikoff, Ralph
2014-07-10
Simulations of the cylinder test are used to illustrate the effect of mesh resolution on a propagating detonation wave. For this study we use the xRage code with the SURF burn model for PBX 9501. The adaptive mesh capability of xRage is used to vary the resolution of the reaction zone. We focus on two key properties: the detonation speed and the cylinder wall velocity. The latter is related to the release isentrope behind the detonation wave. As the reaction zone is refined (2 to 15 cells for cell size of 62 to 8?m), both the detonation speed and final wall velocity change by a small amount; less than 1 per cent. The detonation speed decreases with coarser resolution. Even when the reaction zone is grossly under-resolved (cell size twice the reaction-zone width of the burn model) the wall velocity is within a per cent and the detonation speed is low by only 2 per cent.
Propagation studies of metastable intermolecular composites (MIC).
Son, S. F.; Busse, J. R.; Asay, B. W.; Peterson, P. D.; Mang, J. T.; Bockmon, B.; Pantoya, M.
2002-01-01
Thermite materials are attractive energetic materials because the reactions are highly exothermic, have high energy densities, and high temperatures of combustion. However, the application of thermite materials has been limited because of the relative slow release of energy compared to other energetic materials. Engineered nano-scale composite energetic materials, such as Al/MoO{sub 3}, show promise for additional energetic material applications because they can react very rapidly. The composite material studied in this work consists of tailored, ultra-fine grain (30-200 nm diameter) aluminum particles that dramatically increase energy release rates of these thermite materials. These reactant clusters of fuel and oxidizer particles are in nearly atomic scale proximity to each other but are constrained from reaction until triggered. Despite the growing importance of nano-scale energetic materials, even the most basic combustion characteristics of these materials have not been thoroughly studied. This paper reports initial studies of the ignition and combustion of metastable intermolecular composites (MIC) materials. The goals were lo obtain an improved understanding of flame propagation mechanisms and combustion behaviors associated with nano-structured energetic materials. Information on issues such as reaction rate and behavior as a function of composition (mixture ratio), initial static charge, and particle size are essential and will allow scientists to design applications incorporating the benefits of these compounds. The materials have been characterized, specifically focusing on particle size, shape, distribution and morphology.
Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M.; Harrison, J.D.; Harper, F.T.; Hora, S.C.
1998-04-01
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.
Haskin, F.E.; Harper, F.T.; Goossens, L.H.J.; Kraan, B.C.P.
1997-12-01
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.
Burr, Tom; Croft, Stephen; Jarman, Kenneth D.
2015-09-05
The various methods of nondestructive assay (NDA) of special nuclear material (SNM) have applications in nuclear nonproliferation, including detection and identification of illicit SNM at border crossings, and quantifying SNM at nuclear facilities for safeguards. No assay method is complete without “error bars,” which provide one way of expressing confidence in the assay result. Consequently, NDA specialists typically quantify total uncertainty in terms of “random” and “systematic” components, and then specify error bars for the total mass estimate in multiple items. Uncertainty quantification (UQ) for NDA has always been important, but it is recognized that greater rigor is needed and achievable using modern statistical methods. To this end, we describe the extent to which the guideline for expressing uncertainty in measurements (GUM) can be used for NDA. Also, we propose improvements over GUM for NDA by illustrating UQ challenges that it does not address, including calibration with errors in predictors, model error, and item-specific biases. A case study is presented using low-resolution NaI spectra and applying the enrichment meter principle to estimate the U-235 mass in an item. The case study illustrates how to update the current American Society for Testing and Materials guide for application of the enrichment meter principle using gamma spectra from a NaI detector.
Burr, Tom; Croft, Stephen; Jarman, Kenneth D.
2015-09-05
The various methods of nondestructive assay (NDA) of special nuclear material (SNM) have applications in nuclear nonproliferation, including detection and identification of illicit SNM at border crossings, and quantifying SNM at nuclear facilities for safeguards. No assay method is complete without “error bars,” which provide one way of expressing confidence in the assay result. Consequently, NDA specialists typically quantify total uncertainty in terms of “random” and “systematic” components, and then specify error bars for the total mass estimate in multiple items. Uncertainty quantification (UQ) for NDA has always been important, but it is recognized that greater rigor is needed andmore » achievable using modern statistical methods. To this end, we describe the extent to which the guideline for expressing uncertainty in measurements (GUM) can be used for NDA. Also, we propose improvements over GUM for NDA by illustrating UQ challenges that it does not address, including calibration with errors in predictors, model error, and item-specific biases. A case study is presented using low-resolution NaI spectra and applying the enrichment meter principle to estimate the U-235 mass in an item. The case study illustrates how to update the current American Society for Testing and Materials guide for application of the enrichment meter principle using gamma spectra from a NaI detector.« less
Yang, Xianjin; Chen, Xiao; Carrigan, Charles R.; Ramirez, Abelardo L.
2014-06-03
A parametric bootstrap approach is presented for uncertainty quantification (UQ) of CO₂ saturation derived from electrical resistance tomography (ERT) data collected at the Cranfield, Mississippi (USA) carbon sequestration site. There are many sources of uncertainty in ERT-derived CO₂ saturation, but we focus on how the ERT observation errors propagate to the estimated CO₂ saturation in a nonlinear inversion process. Our UQ approach consists of three steps. We first estimated the observational errors from a large number of reciprocal ERT measurements. The second step was to invert the pre-injection baseline data and the resulting resistivity tomograph was used as the priormore » information for nonlinear inversion of time-lapse data. We assigned a 3% random noise to the baseline model. Finally, we used a parametric bootstrap method to obtain bootstrap CO₂ saturation samples by deterministically solving a nonlinear inverse problem many times with resampled data and resampled baseline models. Then the mean and standard deviation of CO₂ saturation were calculated from the bootstrap samples. We found that the maximum standard deviation of CO₂ saturation was around 6% with a corresponding maximum saturation of 30% for a data set collected 100 days after injection began. There was no apparent spatial correlation between the mean and standard deviation of CO₂ saturation but the standard deviation values increased with time as the saturation increased. The uncertainty in CO₂ saturation also depends on the ERT reciprocal error threshold used to identify and remove noisy data and inversion constraints such as temporal roughness. Five hundred realizations requiring 3.5 h on a single 12-core node were needed for the nonlinear Monte Carlo inversion to arrive at stationary variances while the Markov Chain Monte Carlo (MCMC) stochastic inverse approach may expend days for a global search. This indicates that UQ of 2D or 3D ERT inverse problems can be performed
Yang, Xianjin; Chen, Xiao; Carrigan, Charles R.; Ramirez, Abelardo L.
2014-06-03
A parametric bootstrap approach is presented for uncertainty quantification (UQ) of CO₂ saturation derived from electrical resistance tomography (ERT) data collected at the Cranfield, Mississippi (USA) carbon sequestration site. There are many sources of uncertainty in ERT-derived CO₂ saturation, but we focus on how the ERT observation errors propagate to the estimated CO₂ saturation in a nonlinear inversion process. Our UQ approach consists of three steps. We first estimated the observational errors from a large number of reciprocal ERT measurements. The second step was to invert the pre-injection baseline data and the resulting resistivity tomograph was used as the prior information for nonlinear inversion of time-lapse data. We assigned a 3% random noise to the baseline model. Finally, we used a parametric bootstrap method to obtain bootstrap CO₂ saturation samples by deterministically solving a nonlinear inverse problem many times with resampled data and resampled baseline models. Then the mean and standard deviation of CO₂ saturation were calculated from the bootstrap samples. We found that the maximum standard deviation of CO₂ saturation was around 6% with a corresponding maximum saturation of 30% for a data set collected 100 days after injection began. There was no apparent spatial correlation between the mean and standard deviation of CO₂ saturation but the standard deviation values increased with time as the saturation increased. The uncertainty in CO₂ saturation also depends on the ERT reciprocal error threshold used to identify and remove noisy data and inversion constraints such as temporal roughness. Five hundred realizations requiring 3.5 h on a single 12-core node were needed for the nonlinear Monte Carlo inversion to arrive at stationary variances while the Markov Chain Monte Carlo (MCMC) stochastic inverse approach may expend days for a global search. This indicates that UQ of 2D or 3D ERT inverse problems can be performed on a
Kallinderis, Yannis; Vitsas, Panagiotis A.; Menounou, Penelope
2012-07-15
A low-order flow/acoustics interaction method for the prediction of sound propagation and diffraction in unsteady subsonic compressible flow using adaptive 3-D hybrid grids is investigated. The total field is decomposed into the flow field described by the Euler equations, and the acoustics part described by the Nonlinear Perturbation Equations. The method is shown capable of predicting monopole sound propagation, while employment of acoustics-guided adapted grid refinement improves the accuracy of capturing the acoustic field. Interaction of sound with solid boundaries is also examined in terms of reflection, and diffraction. Sound propagation through an unsteady flow field is examined using static and dynamic flow/acoustics coupling demonstrating the importance of the latter.
Design Storm for Total Retention.pdf
U.S. Department of Energy (DOE) all webpages (Extended Search)
Title: Design Storm for "Total Retention" under Individual Permit, Poster, Individual ... International. Environmental Programs Design Storm for "Total Retention" under ...
U.S. Energy Information Administration (EIA) (indexed site)
St. Clair, MI International Falls, MN Noyes, MN Warroad, MN Babb, MT Havre, MT Port of Del Bonita, MT Port of Morgan, MT Sweetgrass, MT Whitlash, MT Portal, ND Sherwood, ND Pittsburg, NH Champlain, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Highgate Springs, VT North Troy, VT U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Alamo, TX El Paso, TX Galvan Ranch, TX Hidalgo, TX McAllen, TX Penitas, TX LNG Imports from Algeria Cove Point, MD Everett, MA Lake
Cardoso, Goncalo; Stadler, Michael; Bozchalui, Mohammed C.; Sharma, Ratnesh; Marnay, Chris; Barbosa-Povoa, Ana; Ferrao, Paulo
2013-12-06
The large scale penetration of electric vehicles (EVs) will introduce technical challenges to the distribution grid, but also carries the potential for vehicle-to-grid services. Namely, if available in large enough numbers, EVs can be used as a distributed energy resource (DER) and their presence can influence optimal DER investment and scheduling decisions in microgrids. In this work, a novel EV fleet aggregator model is introduced in a stochastic formulation of DER-CAM [1], an optimization tool used to address DER investment and scheduling problems. This is used to assess the impact of EV interconnections on optimal DER solutions considering uncertainty in EV driving schedules. Optimization results indicate that EVs can have a significant impact on DER investments, particularly if considering short payback periods. Furthermore, results suggest that uncertainty in driving schedules carries little significance to total energy costs, which is corroborated by results obtained using the stochastic formulation of the problem.
Quantifying and Reducing Curve-Fitting Uncertainty in Isc: Preprint
Campanelli, Mark; Duck, Benjamin; Emery, Keith
2015-09-28
Current-voltage (I-V) curve measurements of photovoltaic (PV) devices are used to determine performance parameters and to establish traceable calibration chains. Measurement standards specify localized curve fitting methods, e.g., straight-line interpolation/extrapolation of the I-V curve points near short-circuit current, Isc. By considering such fits as statistical linear regressions, uncertainties in the performance parameters are readily quantified. However, the legitimacy of such a computed uncertainty requires that the model be a valid (local) representation of the I-V curve and that the noise be sufficiently well characterized. Using more data points often has the advantage of lowering the uncertainty. However, more data points can make the uncertainty in the fit arbitrarily small, and this fit uncertainty misses the dominant residual uncertainty due to so-called model discrepancy. Using objective Bayesian linear regression for straight-line fits for Isc, we investigate an evidence-based method to automatically choose data windows of I-V points with reduced model discrepancy. We also investigate noise effects. Uncertainties, aligned with the Guide to the Expression of Uncertainty in Measurement (GUM), are quantified throughout.
Avoiding climate change uncertainties in Strategic Environmental Assessment
Larsen, Sanne Vammen; Krnv, Lone; Driscoll, Patrick
2013-11-15
This article is concerned with how Strategic Environmental Assessment (SEA) practice handles climate change uncertainties within the Danish planning system. First, a hypothetical model is set up for how uncertainty is handled and not handled in decision-making. The model incorporates the strategies reduction and resilience, denying, ignoring and postponing. Second, 151 Danish SEAs are analysed with a focus on the extent to which climate change uncertainties are acknowledged and presented, and the empirical findings are discussed in relation to the model. The findings indicate that despite incentives to do so, climate change uncertainties were systematically avoided or downplayed in all but 5 of the 151 SEAs that were reviewed. Finally, two possible explanatory mechanisms are proposed to explain this: conflict avoidance and a need to quantify uncertainty.
Total Imports of Residual Fuel
U.S. Energy Information Administration (EIA) (indexed site)
Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S. Total 9,010 5,030 8,596 6,340 4,707 8,092 1936-2016 PAD District 1 3,127 2,664 2,694 1,250 1,327 2,980 1981-2016 Connecticut 1995-2015 Delaware 280 1995-2016 Florida 858 649 800 200 531 499 1995-2016 Georgia 210 262 149 106 1995-2016 Maine 1995-2015 Maryland 84 1995-2016 Massachusetts 1995-2015 New Hampshire 1995-2015 New Jersey 1,283 843 1,073 734 355 1,984 1995-2016 New York 234 824 210 196 175 1995-2016 North Carolina 1995-2011
Total quality management implementation guidelines
Not Available
1993-12-01
These Guidelines were designed by the Energy Quality Council to help managers and supervisors in the Department of Energy Complex bring Total Quality Management to their organizations. Because the Department is composed of a rich mixture of diverse organizations, each with its own distinctive culture and quality history, these Guidelines are intended to be adapted by users to meet the particular needs of their organizations. For example, for organizations that are well along on their quality journeys and may already have achieved quality results, these Guidelines will provide a consistent methodology and terminology reference to foster their alignment with the overall Energy quality initiative. For organizations that are just beginning their quality journeys, these Guidelines will serve as a startup manual on quality principles applied in the Energy context.
Total Imports of Residual Fuel
U.S. Energy Information Administration (EIA) (indexed site)
2010 2011 2012 2013 2014 2015 View History U.S. Total 133,646 119,888 93,672 82,173 63,294 68,265 1936-2015 PAD District 1 88,999 79,188 59,594 33,566 30,944 33,789 1981-2015 Connecticut 220 129 1995-2015 Delaware 748 1,704 510 1,604 2,479 1995-2015 Florida 15,713 11,654 10,589 8,331 5,055 7,013 1995-2015 Georgia 5,648 7,668 6,370 4,038 2,037 1,629 1995-2015 Maine 1,304 651 419 75 317 135 1995-2015 Maryland 3,638 1,779 1,238 433 938 539 1995-2015 Massachusetts 123 50 78 542 88 1995-2015 New
Total Adjusted Sales of Kerosene
U.S. Energy Information Administration (EIA) (indexed site)
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 2009 2010 2011 2012 2013 2014 View History U.S. 269,010 305,508 187,656 81,102 79,674 137,928 1984-2014 East Coast (PADD 1) 198,762 237,397 142,189 63,075 61,327 106,995 1984-2014 New England (PADD 1A) 56,661 53,363 38,448 15,983 15,991 27,500 1984-2014 Connecticut 8,800 7,437
Total quality management program planning
Thornton, P.T.; Spence, K.
1994-05-01
As government funding grows scarce, competition between the national laboratories is increasing dramatically. In this era of tougher competition, there is no for resistance to change. There must instead be a uniform commitment to improving the overall quality of our products (research and technology) and an increased focus on our customers` needs. There has been an ongoing effort to bring the principles of total quality management (TQM) to all Energy Systems employees to help them better prepare for future changes while responding to the pressures on federal budgets. The need exists for instituting a vigorous program of education and training to an understanding of the techniques needed to improve and initiate a change in organizational culture. The TQM facilitator is responsible for educating the work force on the benefits of self-managed work teams, designing a program of instruction for implementation, and thus getting TQM off the ground at the worker and first-line supervisory levels so that the benefits can flow back up. This program plan presents a conceptual model for TQM in the form of a hot air balloon. In this model, there are numerous factors which can individually and collectively impede the progress of TQM within the division and the Laboratory. When these factors are addressed and corrected, the benefits of TQM become more visible. As this occurs, it is hoped that workers and management alike will grasp the ``total quality`` concept as an acceptable agent for change and continual improvement. TQM can then rise to the occasion and take its rightful place as an integral and valid step in the Laboratory`s formula for survival.
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)
2010-07-01
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.
Propagation of nonlinearly generated harmonic spin waves in microscopic stripes
Rousseau, O.; Yamada, M.; Miura, K.; Ogawa, S.; Otani, Y.
2014-02-07
We report on the experimental study of the propagation of nonlinearly generated harmonic spin waves in microscopic CoFeB stripes. Using an all electrical technique with coplanar waveguides, we find that two kinds of spin waves can be generated by nonlinear frequency multiplication. One has a non-uniform spatial geometry and thus requires appropriate detector geometry to be identified. The other corresponds to the resonant fundamental propagative spin waves and can be efficiently excited by double- or triple-frequency harmonics with any geometry. Nonlinear excited spin waves are particularly efficient in providing an electrical signal arising from spin wave propagation.
Uncertainties in compliance with harmonic current distortion limits in electric power systems
Gruzs, T.M. )
1991-07-01
The harmonic distortion of any repetitive voltage or current waveform is typically described by the quantity total harmonic distortion (THD). With the proliferation of nonlinear loads, such as static power converters, there has been increasing concern over the generation of harmonic currents and the effects of these currents on the power system. Proposals have been made to limit harmonic currents in power systems using the total harmonic distortion of the current as the criterion. This criterion, although it may be necessary, can be ambiguous and lead to compliance uncertainties. In this paper a discussion is presented on several of the practical problems by applying total harmonic current distortion limits to industrial and commercial power systems.
Accounting for Global Climate Model Projection Uncertainty in Modern Statistical Downscaling
Johannesson, G
2010-03-17
configuring and running a regional climate model (RCM) nested within a given GCM projection (i.e., the GCM provides bounder conditions for the RCM). On the other hand, statistical downscaling aims at establishing a statistical relationship between observed local/regional climate variables of interest and synoptic (GCM-scale) climate predictors. The resulting empirical relationship is then applied to future GCM projections. A comparison of the pros and cons of dynamical versus statistical downscaling is outside the scope of this effort, but has been extensively studied and the reader is referred to Wilby et al. (1998); Murphy (1999); Wood et al. (2004); Benestad et al. (2007); Fowler et al. (2007), and references within those. The scope of this effort is to study methodology, a statistical framework, to propagate and account for GCM uncertainty in regional statistical downscaling assessment. In particular, we will explore how to leverage an ensemble of GCM projections to quantify the impact of the GCM uncertainty in such an assessment. There are three main component to this effort: (1) gather the necessary climate-related data for a regional SDS study, including multiple GCM projections, (2) carry out SDS, and (3) assess the uncertainty. The first step is carried out using tools written in the Python programming language, while analysis tools were developed in the statistical programming language R; see Figure 1.
Grid and basis adaptive polynomial chaos techniques for sensitivity and uncertainty analysis
Perk, Zoltn Gilli, Luca Lathouwers, Danny Kloosterman, Jan Leen
2014-03-01
The demand for accurate and computationally affordable sensitivity and uncertainty techniques is constantly on the rise and has become especially pressing in the nuclear field with the shift to Best Estimate Plus Uncertainty methodologies in the licensing of nuclear installations. Besides traditional, already well developed methods such as first order perturbation theory or Monte Carlo sampling Polynomial Chaos Expansion (PCE) has been given a growing emphasis in recent years due to its simple application and good performance. This paper presents new developments of the research done at TU Delft on such Polynomial Chaos (PC) techniques. Our work is focused on the Non-Intrusive Spectral Projection (NISP) approach and adaptive methods for building the PCE of responses of interest. Recent efforts resulted in a new adaptive sparse grid algorithm designed for estimating the PC coefficients. The algorithm is based on Gerstner's procedure for calculating multi-dimensional integrals but proves to be computationally significantly cheaper, while at the same it retains a similar accuracy as the original method. More importantly the issue of basis adaptivity has been investigated and two techniques have been implemented for constructing the sparse PCE of quantities of interest. Not using the traditional full PC basis set leads to further reduction in computational time since the high order grids necessary for accurately estimating the near zero expansion coefficients of polynomial basis vectors not needed in the PCE can be excluded from the calculation. Moreover the sparse PC representation of the response is easier to handle when used for sensitivity analysis or uncertainty propagation due to the smaller number of basis vectors. The developed grid and basis adaptive methods have been implemented in Matlab as the Fully Adaptive Non-Intrusive Spectral Projection (FANISP) algorithm and were tested on four analytical problems. These show consistent good performance both in
Total-derivative supersymmetry breaking
Haba, Naoyuki; Uekusa, Nobuhiro
2010-05-15
On an interval compactification in supersymmetric theory, boundary conditions for bulk fields must be treated carefully. If they are taken arbitrarily following the requirement that a theory is supersymmetric, the conditions could give redundant constraints on the theory. We construct a supersymmetric action integral on an interval by introducing brane interactions with which total-derivative terms under the supersymmetry transformation become zero due to a cancellation. The variational principle leads equations of motion and also boundary conditions for bulk fields, which determine boundary values of bulk fields. By estimating mass spectrum, spontaneous supersymmetry breaking in this simple setup can be realized in a new framework. This supersymmetry breaking does not induce a massless R axion, which is favorable for phenomenology. It is worth noting that fermions in hyper-multiplet, gauge bosons, and the fifth-dimensional component of gauge bosons can have zero-modes (while the other components are all massive as Kaluza-Klein modes), which fits the gauge-Higgs unification scenarios.
Wave propagation and dispersion in a nonlinear microstructured...
Office of Scientific and Technical Information (OSTI)
Citation Details In-Document Search Title: Wave propagation ... 1106985 Report Number(s): SAND2013-6966J 463826 DOE Contract Number: AC04-94AL85000 Resource Type: Journal Article ...
Helton, J.C.; Johnson, J.D.; Rollstin, J.A.; Shiver, A.W.; Sprung, J.L.
1995-01-01
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.
Electrically heated particulate filter propagation support methods and systems
Gonze, Eugene V [Pinckney, MI; Ament, Frank [Troy, MI
2011-06-07
A control system that controls regeneration of a particulate filter is provided. The system generally includes a regeneration module that controls current to the particulate filter to initiate combustion of particulate matter in the particulate filter. A propagation module estimates a propagation status of the combustion of the particulate matter based on a combustion temperature. A temperature adjustment module controls the combustion temperature by selectively increasing a temperature of exhaust that passes through the particulate filter.
Voltage modulation of propagating spin waves in Fe
Nawaoka, Kohei; Shiota, Yoichi; Miwa, Shinji; Tamura, Eiiti; Tomita, Hiroyuki; Mizuochi, Norikazu; Shinjo, Teruya; Suzuki, Yoshishige
2015-05-07
The effect of a voltage application on propagating spin waves in single-crystalline 5?nm-Fe layer was investigated. Two micro-sized antennas were employed to excite and detect the propagating spin waves. The voltage effect was characterized using AC lock-in technique. As a result, the resonant field of the magnetostatic surface wave in the Fe was clearly modulated by the voltage application. The modulation is attributed to the voltage induced magnetic anisotropy change in ferromagnetic metals.
Circular polarization of obliquely propagating whistler wave magnetic field
Bellan, P. M.
2013-08-15
The circular polarization of the magnetic field of obliquely propagating whistler waves is derived using a basis set associated with the wave partial differential equation. The wave energy is mainly magnetic and the wave propagation consists of this magnetic energy sloshing back and forth between two orthogonal components of magnetic field in quadrature. The wave electric field energy is small compared to the magnetic field energy.
Measurement uncertainty analysis techniques applied to PV performance measurements
Wells, C.
1992-10-01
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.
On the propagation of a coupled saturation and pressure front
Vasco, D. W.
2010-12-01
Using an asymptotic technique, valid for a medium with smoothly varying heterogeneity, I derive an expression for the velocity of a propagating, coupled saturation and pressure front. Due to the nonlinearity of the governing equations, the velocity of the propagating front depends upon the magnitude of the saturation and pressure changes across the front in addition to the properties of the medium. Thus, the expression must be evaluated in conjunction with numerical reservoir simulation. The propagation of the two-phase front is governed by the background saturation distribution, the saturation-dependent component of the fluid mobility, the porosity, the permeability, the capillary pressure function, the medium compressibility, and the ratio of the slopes of the relative permeability curves. Numerical simulation of water injection into a porous layer saturated with a nonaqueous phase liquid indicates that two modes of propagation are important. The fastest mode of propagation is a pressure-dominated disturbance that travels through the saturated layer. This is followed, much later, by a coupled mode with a large saturation change. These two modes are also observed in a simulation using a heterogeneous porous layer. A comparison between the propagation times estimated from the results of the numerical simulation and predictions from the asymptotic expression indicates overall agreement.
Total Space Heating Water Heating Cook-
Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing...
Total Space Heating Water Heating Cook-
Gasoline and Diesel Fuel Update
Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,870 1,276...
Total Space Heating Water Heating Cook-
Gasoline and Diesel Fuel Update
Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All...
Total Space Heating Water Heating Cook-
Gasoline and Diesel Fuel Update
Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,602 1,397...
Total Space Heating Water Heating Cook-
Gasoline and Diesel Fuel Update
Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings ... 2,037...
,"West Virginia Natural Gas Total Consumption (MMcf)"
U.S. Energy Information Administration (EIA) (indexed site)
Data for" ,"Data 1","West Virginia Natural Gas Total Consumption ... AM" "Back to Contents","Data 1: West Virginia Natural Gas Total Consumption (MMcf)" ...
,"Total Crude Oil and Petroleum Products Exports"
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Data for" ,"Data 1","Total Crude Oil and Petroleum Products ... "Back to Contents","Data 1: Total Crude Oil and Petroleum Products Exports" ...
,"New Mexico Natural Gas Total Consumption (MMcf)"
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Data for" ,"Data 1","New Mexico Natural Gas Total Consumption ... AM" "Back to Contents","Data 1: New Mexico Natural Gas Total Consumption (MMcf)" ...
,"North Dakota Natural Gas Total Consumption (MMcf)"
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Data for" ,"Data 1","North Dakota Natural Gas Total Consumption ... 9:10:34 AM" "Back to Contents","Data 1: North Dakota Natural Gas Total Consumption ...
,"North Carolina Natural Gas Total Consumption (MMcf)"
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Data for" ,"Data 1","North Carolina Natural Gas Total Consumption ... 9:10:33 AM" "Back to Contents","Data 1: North Carolina Natural Gas Total Consumption ...
Calibration and Measurement Uncertainty Estimation of Radiometric Data: Preprint
Habte, A.; Sengupta, M.; Reda, I.; Andreas, A.; Konings, J.
2014-11-01
Evaluating the performance of photovoltaic cells, modules, and arrays that form large solar deployments relies on accurate measurements of the available solar resource. Therefore, determining the accuracy of these solar radiation measurements provides a better understanding of investment risks. This paper provides guidelines and recommended procedures for estimating the uncertainty in calibrations and measurements by radiometers using methods that follow the International Bureau of Weights and Measures Guide to the Expression of Uncertainty (GUM). Standardized analysis based on these procedures ensures that the uncertainty quoted is well documented.
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.
2013-10-01
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.
Integration of Uncertainty Information into Power System Operations
Makarov, Yuri V.; Lu, Shuai; Samaan, Nader A.; Huang, Zhenyu; Subbarao, Krishnappa; Etingov, Pavel V.; Ma, Jian; Hafen, Ryan P.; Diao, Ruisheng; Lu, Ning
2011-10-10
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).
Probabilistic Accident Consequence Uncertainty - A Joint CEC/USNRC Study
Gregory, Julie J.; Harper, Frederick T.
1999-07-28
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.
Dasymetric Modeling and Uncertainty (Journal Article) | SciTech...
Office of Scientific and Technical Information (OSTI)
Journal Article: Dasymetric Modeling and Uncertainty Citation Details In-Document Search ... DOE Contract Number: DE-AC05-00OR22725 Resource Type: Journal Article Resource Relation: ...
Risk Analysis and Decision-Making Under Uncertainty: A Strategy...
Office of Environmental Management (EM)
Uncertainty Analysis and Parameter Estimation Since 2002 To view all the P&RA CoP ... Update of Hydrogen from Biomass - Determination of the Delivered Cost of Hydrogen: ...
Uncertainty analysis of multi-rate kinetics of uranium desorption...
Office of Scientific and Technical Information (OSTI)
in the multi-rate model to simualte U(VI) desorption; 3) however, long-term prediction and its uncertainty may be significantly biased by the lognormal assumption for the ...
Problem Solving Environment for Uncertainty Analysis and Design Exploration
Energy Science and Technology Software Center (OSTI)
2011-10-26
PSUADE is an software system that is used to study the releationships between the inputs and outputs of gerneral simulation models for the purpose of performing uncertainty and sensitivity analyses on simulation models.
Gerhard Strydom; Su-Jong Yoon
2014-04-01
Computational Fluid Dynamics (CFD) evaluation of homogeneous and heterogeneous fuel models was performed as part of the Phase I calculations of the International Atomic Energy Agency (IAEA) Coordinate Research Program (CRP) on High Temperature Reactor (HTR) Uncertainties in Modeling (UAM). This study was focused on the nominal localized stand-alone fuel thermal response, as defined in Ex. I-3 and I-4 of the HTR UAM. The aim of the stand-alone thermal unit-cell simulation is to isolate the effect of material and boundary input uncertainties on a very simplified problem, before propagation of these uncertainties are performed in subsequent coupled neutronics/thermal fluids phases on the benchmark. In many of the previous studies for high temperature gas cooled reactors, the volume-averaged homogeneous mixture model of a single fuel compact has been applied. In the homogeneous model, the Tristructural Isotropic (TRISO) fuel particles in the fuel compact were not modeled directly and an effective thermal conductivity was employed for the thermo-physical properties of the fuel compact. On the contrary, in the heterogeneous model, the uranium carbide (UCO), inner and outer pyrolytic carbon (IPyC/OPyC) and silicon carbide (SiC) layers of the TRISO fuel particles are explicitly modeled. The fuel compact is modeled as a heterogeneous mixture of TRISO fuel kernels embedded in H-451 matrix graphite. In this study, a steady-state and transient CFD simulations were performed with both homogeneous and heterogeneous models to compare the thermal characteristics. The nominal values of the input parameters are used for this CFD analysis. In a future study, the effects of input uncertainties in the material properties and boundary parameters will be investigated and reported.
" Level: National Data and Regional Totals...
U.S. Energy Information Administration (EIA) (indexed site)
... by" "petroleum refineries, rather than purchased ... ,,"Total United States" ,"RSE Column ... 324,"Petroleum and Coal ...
Gas Exploration Software for Reducing Uncertainty in Gas Concentration
U.S. Department of Energy (DOE) all webpages (Extended Search)
Estimates - Energy Innovation Portal Energy Analysis Energy Analysis Find More Like This Return to Search Gas Exploration Software for Reducing Uncertainty in Gas Concentration Estimates Lawrence Berkeley National Laboratory Contact LBL About This Technology Technology Marketing SummaryEstimating reservoir parameters for gas exploration from geophysical data is subject to a large degree of uncertainty. Seismic imaging techniques, such as seismic amplitude versus angle (AVA) analysis, can
Improvements of Nuclear Data and Its Uncertainties by Theoretical Modeling
Office of Scientific and Technical Information (OSTI)
(Technical Report) | SciTech Connect Technical Report: Improvements of Nuclear Data and Its Uncertainties by Theoretical Modeling Citation Details In-Document Search Title: Improvements of Nuclear Data and Its Uncertainties by Theoretical Modeling Authors: Talou, Patrick [1] ; Nazarewicz, Witold [2] ; Prinja, Anil [3] ; Danon, Yaron [4] + Show Author Affiliations Los Alamos National Laboratory University of Tennessee, Knoxville, TN 37996, USA University of New Mexico, USA Rensselaer
PROJECT PROFILE: Reducing PV Performance Uncertainty by Accurately
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
Quantifying the "PV Resource" | Department of Energy Reducing PV Performance Uncertainty by Accurately Quantifying the "PV Resource" PROJECT PROFILE: Reducing PV Performance Uncertainty by Accurately Quantifying the "PV Resource" Funding Opportunity: SuNLaMP SunShot Subprogram: Photovoltaics Location: National Renewable Energy Laboratory, Golden, CO Amount Awarded: $2,500,000 The procedures used today for prediction of the solar resource available to
Direct Aerosol Forcing: Sensitivity to Uncertainty in Measurements of
U.S. Department of Energy (DOE) all webpages (Extended Search)
Aerosol Optical and Situational Properties Direct Aerosol Forcing: Sensitivity to Uncertainty in Measurements of Aerosol Optical and Situational Properties McComiskey, Allison CIRES / NOAA Schwartz, Stephen Brookhaven National Laboratory Ricchiazzi, Paul University of California, Santa Barbara Lewis, Ernie Brookhaven National Laboratory Michalsky, Joseph DOC/NOAA/OAR/ESRL/GMD Ogren, John NOAA/CMDL Category: Radiation Understanding sources of uncertainty in estimating aerosol direct radiative
Microsoft Word - Documentation - Price Forecast Uncertainty.doc
U.S. Energy Information Administration (EIA) (indexed site)
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
Uncertainties in the Anti-neutrino Production at Nuclear Reactors
Djurcic, Zelimir; Detwiler, Jason A.; Piepke, Andreas; Foster Jr., Vince R.; Miller, Lester; Gratta, Giorgio
2008-08-06
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.
Quantifying Uncertainty in Computer Predictions | netl.doe.gov
U.S. Department of Energy (DOE) all webpages (Extended Search)
Quantifying Uncertainty in Computer Predictions Quantifying Uncertainty in Computer Model Predictions The U.S. Department of Energy has great interest in technologies that will lead to reducing the CO2 emissions of fossil-fuel-burning power plants. Advanced energy technologies such as Integrated Gasification Combined Cycle (IGCC) and Carbon Capture and Storage (CCS) can potentially lead to the clean and efficient use of fossil fuels to power our nation. The development of new energy
Analysis of the Uncertainty in Wind Measurements from the Atmospheric
Office of Scientific and Technical Information (OSTI)
Radiation Measurement Doppler Lidar during XPIA: Field Campaign Report (Program Document) | SciTech Connect Program Document: Analysis of the Uncertainty in Wind Measurements from the Atmospheric Radiation Measurement Doppler Lidar during XPIA: Field Campaign Report Citation Details In-Document Search Title: Analysis of the Uncertainty in Wind Measurements from the Atmospheric Radiation Measurement Doppler Lidar during XPIA: Field Campaign Report In March and April of 2015, the ARM Doppler
Determining Best Estimates and Uncertainties in Cloud Microphysical
Office of Scientific and Technical Information (OSTI)
Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions (Technical Report) | SciTech Connect Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions Citation Details In-Document Search Title: Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for
Lab RFP: Validation and Uncertainty Characterization | Department of Energy
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
Validation and Uncertainty Characterization Lab RFP: Validation and Uncertainty Characterization LBNL's FLEXLAB test facility, which includes four test cells each split into two half-cells to enable side-by-side comparative experiments. The cells have one active, reconfigurable facade, and individual, reconfigurable single-zone HVAC systems. The cell facing the camera sits on 270 degree turntable. Photo credit: LBNL. Bottom: ORNL's two-story flexible research platform test building. The building
How incorporating more data reduces uncertainty in recovery predictions
Campozana, F.P.; Lake, L.W.; Sepehrnoori, K.
1997-08-01
From the discovery to the abandonment of a petroleum reservoir, there are many decisions that involve economic risks because of uncertainty in the production forecast. This uncertainty may be quantified by performing stochastic reservoir modeling (SRM); however, it is not practical to apply SRM every time the model is updated to account for new data. This paper suggests a novel procedure to estimate reservoir uncertainty (and its reduction) as a function of the amount and type of data used in the reservoir modeling. Two types of data are analyzed: conditioning data and well-test data. However, the same procedure can be applied to any other data type. Three performance parameters are suggested to quantify uncertainty. SRM is performed for the following typical stages: discovery, primary production, secondary production, and infill drilling. From those results, a set of curves is generated that can be used to estimate (1) the uncertainty for any other situation and (2) the uncertainty reduction caused by the introduction of new wells (with and without well-test data) into the description.
Uncertainty Estimation Improves Energy Measurement and Verification Procedures
Walter, Travis; Price, Phillip N.; Sohn, Michael D.
2014-05-14
Implementing energy conservation measures in buildings can reduce energy costs and environmental impacts, but such measures cost money to implement so intelligent investment strategies require the ability to quantify the energy savings by comparing actual energy used to how much energy would have been used in absence of the conservation measures (known as the baseline energy use). Methods exist for predicting baseline energy use, but a limitation of most statistical methods reported in the literature is inadequate quantification of the uncertainty in baseline energy use predictions. However, estimation of uncertainty is essential for weighing the risks of investing in retrofits. Most commercial buildings have, or soon will have, electricity meters capable of providing data at short time intervals. These data provide new opportunities to quantify uncertainty in baseline predictions, and to do so after shorter measurement durations than are traditionally used. In this paper, we show that uncertainty estimation provides greater measurement and verification (M&V) information and helps to overcome some of the difficulties with deciding how much data is needed to develop baseline models and to confirm energy savings. We also show that cross-validation is an effective method for computing uncertainty. In so doing, we extend a simple regression-based method of predicting energy use using short-interval meter data. We demonstrate the methods by predicting energy use in 17 real commercial buildings. We discuss the benefits of uncertainty estimates which can provide actionable decision making information for investing in energy conservation measures.
Uncertainty in Simulating Wheat Yields Under Climate Change
Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J.W.; Hatfield, Jerry; Ruane, Alex; Boote, K. J.; Thorburn, Peter; Rotter, R.P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P.K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, AJ; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, Robert; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, Roberto C.; Kersebaum, K.C.; Mueller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.O.; Olesen, JE; Osborne, T.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stockle, Claudio O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Williams, J.R.; Wolf, J.
2013-09-01
Anticipating the impacts of climate change on crop yields is critical for assessing future food security. Process-based crop simulation models are the most commonly used tools in such assessments1,2. Analysis of uncertainties in future greenhouse gas emissions and their impacts on future climate change has been increasingly described in the literature3,4 while assessments of the uncertainty in crop responses to climate change are very rare. Systematic and objective comparisons across impact studies is difficult, and thus has not been fully realized5. Here we present the largest coordinated and standardized crop model intercomparison for climate change impacts on wheat production to date. We found that several individual crop models are able to reproduce measured grain yields under current diverse environments, particularly if sufficient details are provided to execute them. However, simulated climate change impacts can vary across models due to differences in model structures and algorithms. The crop-model component of uncertainty in climate change impact assessments was considerably larger than the climate-model component from Global Climate Models (GCMs). Model responses to high temperatures and temperature-by-CO2 interactions are identified as major sources of simulated impact uncertainties. Significant reductions in impact uncertainties through model improvements in these areas and improved quantification of uncertainty through multi-model ensembles are urgently needed for a more reliable translation of climate change scenarios into agricultural impacts in order to develop adaptation strategies and aid policymaking.
LCOE Uncertainty Analysis for Hydropower using Monte Carlo Simulations
Chalise, Dol Raj; O'Connor, Patrick W; DeNeale, Scott T; Uria Martinez, Rocio; Kao, Shih-Chieh
2015-01-01
Levelized Cost of Energy (LCOE) is an important metric to evaluate the cost and performance of electricity production generation alternatives, and combined with other measures, can be used to assess the economics of future hydropower development. Multiple assumptions on input parameters are required to calculate the LCOE, which each contain some level of uncertainty, in turn affecting the accuracy of LCOE results. This paper explores these uncertainties, their sources, and ultimately the level of variability they introduce at the screening level of project evaluation for non-powered dams (NPDs) across the U.S. Owing to site-specific differences in site design, the LCOE for hydropower varies significantly from project to project unlike technologies with more standardized configurations such as wind and gas. Therefore, to assess the impact of LCOE input uncertainty on the economics of U.S. hydropower resources, these uncertainties must be modeled across the population of potential opportunities. To demonstrate the impact of uncertainty, resource data from a recent nationwide non-powered dam (NPD) resource assessment (Hadjerioua et al., 2012) and screening-level predictive cost equations (O Connor et al., 2015) are used to quantify and evaluate uncertainties in project capital and operations & maintenance costs, and generation potential at broad scale. LCOE dependence on financial assumptions is also evaluated on a sensitivity basis to explore ownership/investment implications on project economics for the U.S. hydropower fleet. The results indicate that the LCOE for U.S. NPDs varies substantially. The LCOE estimates for the potential NPD projects of capacity greater than 1 MW range from 40 to 182 $/MWh, with average of 106 $/MWh. 4,000 MW could be developed through projects with individual LCOE values below 100 $/MWh. The results also indicate that typically 90 % of LCOE uncertainty can be attributed to uncertainties in capital costs and energy production; however
Covariant energymomentum and an uncertainty principle for general relativity
Cooperstock, F.I.; Dupre, M.J.
2013-12-15
We introduce a naturally-defined totally invariant spacetime energy expression for general relativity incorporating the contribution from gravity. The extension links seamlessly to the action integral for the gravitational field. The demand that the general expression for arbitrary systems reduces to the Tolman integral in the case of stationary bounded distributions, leads to the matter-localized Ricci integral for energymomentum in support of the energy localization hypothesis. The role of the observer is addressed and as an extension of the special relativistic case, the field of observers comoving with the matter is seen to compute the intrinsic global energy of a system. The new localized energy supports the Bonnor claim that the Szekeres collapsing dust solutions are energy-conserving. It is suggested that in the extreme of strong gravity, the Heisenberg Uncertainty Principle be generalized in terms of spacetime energymomentum. -- Highlights: We present a totally invariant spacetime energy expression for general relativity incorporating the contribution from gravity. Demand for the general expression to reduce to the Tolman integral for stationary systems supports the Ricci integral as energymomentum. Localized energy via the Ricci integral is consistent with the energy localization hypothesis. New localized energy supports the Bonnor claim that the Szekeres collapsing dust solutions are energy-conserving. Suggest the Heisenberg Uncertainty Principle be generalized in terms of spacetime energymomentum in strong gravity extreme.
Hydropower generation management under uncertainty via scenario analysis and parallel computation
Escudero, L.F.; Garcia, C.; Fuente, J.L. de la; Prieto, F.J.
1996-05-01
The authors present a modeling framework for the robust solution of hydroelectric power management problems with uncertainty in the values of the water inflows and outflows. A deterministic treatment of the problem provides unsatisfactory results, except for very short time horizons. The authors describe a model based on scenario analysis that allows a satisfactory treatment of uncertainty in the model data for medium and long-term planning problems. Their approach results in a huge model with a network submodel per scenario plus coupling constraints. The size of the problem and the structure of the constraints are adequate for the use of decomposition techniques and parallel computation tools. The authors present computational results for both sequential and parallel implementation versions of the codes, running on a cluster of workstations. The codes have been tested on data obtained from the reservoir network of Iberdrola, a power utility owning 50% of the total installed hydroelectric capacity of Spain, and generating 40% of the total energy demand.
Hydropower generation management under uncertainty via scenario analysis and parallel computation
Escudero, L.F.; Garcia, C.; Fuente, J.L. de la; Prieto, F.J.
1995-12-31
The authors present a modeling framework for the robust solution of hydroelectric power management problems and uncertainty in the values of the water inflows and outflows. A deterministic treatment of the problem provides unsatisfactory results, except for very short time horizons. The authors describe a model based on scenario analysis that allows a satisfactory treatment of uncertainty in the model data for medium and long-term planning problems. This approach results in a huge model with a network submodel per scenario plus coupling constraints. The size of the problem and the structure of the constraints are adequate for the use of decomposition techniques and parallel computation tools. The authors present computational results for both sequential and parallel implementation versions of the codes, running on a cluster of workstations. The code have been tested on data obtained from the reservoir network of Iberdrola, a power utility owning 50% of the total installed hydroelectric capacity of Spain, and generating 40% of the total energy demand.
Habte, A.; Sengupta, M.; Reda, I.
2015-03-01
Radiometric data with known and traceable uncertainty is essential for climate change studies to better understand cloud radiation interactions and the earth radiation budget. Further, adopting a known and traceable method of estimating uncertainty with respect to SI ensures that the uncertainty quoted for radiometric measurements can be compared based on documented methods of derivation.Therefore, statements about the overall measurement uncertainty can only be made on an individual basis, taking all relevant factors into account. This poster provides guidelines and recommended procedures for estimating the uncertainty in calibrations and measurements from radiometers. The approach follows the Guide to the Expression of Uncertainty in Measurement (GUM). derivation.Therefore, statements about the overall measurement uncertainty can only be made on an individual basis, taking all relevant factors into account. This poster provides guidelines and recommended procedures for estimating the uncertainty in calibrations and measurements from radiometers. The approach follows the Guide to the Expression of Uncertainty in Measurement (GUM).
Experimental study of thermodynamics propagation fatigue crack in metals
Vshivkov, A. Iziumova, A. Plekhov, O.
2015-10-27
This work is devoted to the development of an experimental method for studying the energy balance during cyclic deformation and fracture. The studies were conducted on 304 stainless steel AISE samples. The investigation of the fatigue crack propagation was carried out on flat samples with stress concentrators. The stress concentrator was three central holes. The heat flux sensor was developed based on the Seebeck effect. This sensor was used for measuring the heat dissipation power in the examined samples during the fatigue tests. The measurements showed that the rate of fatigue crack growth depends on the heat flux at the crack tip and there are two propagation mode of fatigue crack with different link between the propagation mode and heat flux from crack tip.
Redus, K. S.; Hampshire, G. J.; Patterson, J. E.; Perkins, A. B.
2002-02-25
The Waste Acceptance Criteria Forecasting and Analysis Capability System (WACFACS) is used to plan for, evaluate, and control the supply of approximately 1.8 million yd3 of low-level radioactive, TSCA, and RCRA hazardous wastes from over 60 environmental restoration projects between FY02 through FY10 to the Oak Ridge Environmental Management Waste Management Facility (EMWMF). WACFACS is a validated decision support tool that propagates uncertainties inherent in site-related contaminant characterization data, disposition volumes during EMWMF operations, and project schedules to quantitatively determine the confidence that risk-based performance standards are met. Trade-offs in schedule, volumes of waste lots, and allowable concentrations of contaminants are performed to optimize project waste disposition, regulatory compliance, and disposal cell management.
Singh, Aditya; Serbin, Shawn P.; McNeil, Brenden E.; Kingdon, Clayton C.; Townsend, Philip A.
2015-12-01
A major goal of remote sensing is the development of generalizable algorithms to repeatedly and accurately map ecosystem properties across space and time. Imaging spectroscopy has great potential to map vegetation traits that cannot be retrieved from broadband spectral data, but rarely have such methods been tested across broad regions. Here we illustrate a general approach for estimating key foliar chemical and morphological traits through space and time using NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-Classic). We apply partial least squares regression (PLSR) to data from 237 field plots within 51 images acquired between 2008 and 2011. Using a series of 500 randomized 50/50 subsets of the original data, we generated spatially explicit maps of seven traits (leaf mass per area (M_{area}), percentage nitrogen, carbon, fiber, lignin, and cellulose, and isotopic nitrogen concentration, δ^{15}N) as well as pixel-wise uncertainties in their estimates based on error propagation in the analytical methods. Both Marea and %N PLSR models had a R^{2} > 0.85. Root mean square errors (RMSEs) for both variables were less than 9% of the range of data. Fiber and lignin were predicted with R^{2} > 0.65 and carbon and cellulose with R^{2} > 0.45. Although R^{2} of %C and cellulose were lower than Marea and %N, the measured variability of these constituents (especially %C) was also lower, and their RMSE values were beneath 12% of the range in overall variability. Model performance for δ^{15}N was the lowest (R^{2} = 0.48, RMSE = 0.95‰), but within 15% of the observed range. The resulting maps of chemical and morphological traits, together with their overall uncertainties, represent a first-of-its-kind approach for examining the spatiotemporal patterns of forest functioning and nutrient cycling across a broad range of temperate and sub-boreal ecosystems. These results offer an alternative to
Singh, Aditya; Serbin, Shawn P.; McNeil, Brenden E.; Kingdon, Clayton C.; Townsend, Philip A.
2015-12-01
A major goal of remote sensing is the development of generalizable algorithms to repeatedly and accurately map ecosystem properties across space and time. Imaging spectroscopy has great potential to map vegetation traits that cannot be retrieved from broadband spectral data, but rarely have such methods been tested across broad regions. Here we illustrate a general approach for estimating key foliar chemical and morphological traits through space and time using NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-Classic). We apply partial least squares regression (PLSR) to data from 237 field plots within 51 images acquired between 2008 and 2011. Using a series ofmore » 500 randomized 50/50 subsets of the original data, we generated spatially explicit maps of seven traits (leaf mass per area (Marea), percentage nitrogen, carbon, fiber, lignin, and cellulose, and isotopic nitrogen concentration, δ15N) as well as pixel-wise uncertainties in their estimates based on error propagation in the analytical methods. Both Marea and %N PLSR models had a R2 > 0.85. Root mean square errors (RMSEs) for both variables were less than 9% of the range of data. Fiber and lignin were predicted with R2 > 0.65 and carbon and cellulose with R2 > 0.45. Although R2 of %C and cellulose were lower than Marea and %N, the measured variability of these constituents (especially %C) was also lower, and their RMSE values were beneath 12% of the range in overall variability. Model performance for δ15N was the lowest (R2 = 0.48, RMSE = 0.95‰), but within 15% of the observed range. The resulting maps of chemical and morphological traits, together with their overall uncertainties, represent a first-of-its-kind approach for examining the spatiotemporal patterns of forest functioning and nutrient cycling across a broad range of temperate and sub-boreal ecosystems. These results offer an alternative to categorical maps of functional or physiognomic types by providing non-discrete maps (i
Spherical Wave Propagation in a Nonlinear Elastic Medium
Korneev, Valeri A.
2009-07-01
Nonlinear propagation of spherical waves generated by a point-pressure source is considered for the cases of monochromatic and impulse primary waveforms. The nonlinear five-constant elastic theory advanced by Murnaghan is used where general equations of motion are put in the form of vector operators, which are independent of the coordinate system choice. The ratio of the nonlinear field component to the primary wave in the far field is proportional to ln(r) where r is a propagation distance. Near-field components of the primary field do not contribute to the far field of nonlinear component.
The fundamental solution of the unidirectional pulse propagation equation
Babushkin, I.; Bergé, L.
2014-03-15
The fundamental solution of a variant of the three-dimensional wave equation known as “unidirectional pulse propagation equation” (UPPE) and its paraxial approximation is obtained. It is shown that the fundamental solution can be presented as a projection of a fundamental solution of the wave equation to some functional subspace. We discuss the degree of equivalence of the UPPE and the wave equation in this respect. In particular, we show that the UPPE, in contrast to the common belief, describes wave propagation in both longitudinal and temporal directions, and, thereby, its fundamental solution possesses a non-causal character.
Gluon propagators and center vortices in gluon plasma
Chernodub, M. N.; Nakagawa, Y.; Nakamura, A.; Saito, T.; Zakharov, V. I.
2011-06-01
We study electric and magnetic components of the gluon propagators in quark-gluon plasma in terms of center vortices by using a quenched simulation of SU(2) lattice theory. In the Landau gauge, the magnetic components of the propagators are strongly affected in the infrared region by removal of the center vortices, while the electric components are almost unchanged by this procedure. In the Coulomb gauge, the time-time correlators, including an instantaneous interaction, also have an essential contribution from the center vortices. As a result, one finds that magnetic degrees of freedom in the infrared region couple strongly to the center vortices in the deconfinement phase.
Total Space Heating Water Heating Cook-
Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 634 578 46 1 Q 116.4 106.3...
Total System Performance Assessment Peer Review Panel
Total System Performance Assessment (TSPA) Peer Review Panel for predicting the performance of a repository at Yucca Mountain.
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
2 Alaska - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S2. Summary statistics for natural gas - Alaska, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 269 277 185 R 159 170 Production (million cubic feet) Gross Withdrawals From Gas Wells 127,417 112,268
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
6 District of Columbia - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
0 Indiana - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S16. Summary statistics for natural gas - Indiana, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 620 914 819 R 921 895 Production (million cubic feet) Gross Withdrawals From Gas Wells 6,802 9,075
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
4 Massachusetts - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
6 Nebraska - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S29. Summary statistics for natural gas - Nebraska, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 276 322 270 R 357 310 Production (million cubic feet) Gross Withdrawals From Gas Wells 2,092 1,854
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
50 North Dakota - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S36. Summary statistics for natural gas - North Dakota, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 188 239 211 200 200 Production (million cubic feet) Gross Withdrawals From Gas Wells
Systematic uncertainties from halo asphericity in dark matter searches
Bernal, Nicols; Forero-Romero, Jaime E.; Garani, Raghuveer; Palomares-Ruiz, Sergio E-mail: je.forero@uniandes.edu.co E-mail: sergio.palomares.ruiz@ific.uv.es
2014-09-01
Although commonly assumed to be spherical, dark matter halos are predicted to be non-spherical by N-body simulations and their asphericity has a potential impact on the systematic uncertainties in dark matter searches. The evaluation of these uncertainties is the main aim of this work, where we study the impact of aspherical dark matter density distributions in Milky-Way-like halos on direct and indirect searches. Using data from the large N-body cosmological simulation Bolshoi, we perform a statistical analysis and quantify the systematic uncertainties on the determination of local dark matter density and the so-called J factors for dark matter annihilations and decays from the galactic center. We find that, due to our ignorance about the extent of the non-sphericity of the Milky Way dark matter halo, systematic uncertainties can be as large as 35%, within the 95% most probable region, for a spherically averaged value for the local density of 0.3-0.4 GeV/cm {sup 3}. Similarly, systematic uncertainties on the J factors evaluated around the galactic center can be as large as 10% and 15%, within the 95% most probable region, for dark matter annihilations and decays, respectively.
Effects of swirl-flow on flame propagation in a constant-volume vessel
Cai, P.; Watanabe, Kazunori; Obara, Tetsuro; Yoshihashi, Teruo; Ohyagi, Shigeharu
1999-07-01
Flame propagation in a closed vessel is one of the fundamental topics in the combustion science and technology. This problem has been studied mostly for application to engine combustion because the combustion processes in a premixed spark ignition engine are well simulated by those processes in a constant-volume combustion chamber. One of the most important objective to study this phenomena is to elucidate the combustion phenomena to increase the thermal efficiency of engine by enhancing the combustion process. In real engines, a number of technical methods such as swirl, tumble, squish and jet flows ere developed to shorten a burning time. All of these methods make use of flows in the combustion chamber. The fundamental problem is then to elucidate a mechanism of reduction of the burning time by the flows and their turbulence. In the present work, experiments were conducted to investigate the effects of swirl-flow on the flame propagation in a disc-shaped constant-volume vessel of 100 mm in diameter and 30 mm in depth. Figure A-1 shows a schematic of the apparatus. Gaseous mixtures used were methane diluted with air at an atmospheric pressure, and their equivalence ratios were varied as a parameter. Ignition timing was varied to change the velocity of swirling flow before the flame propagation. As results, a burning time was found to be decreased as the swirling flow increased and a maximum pressure was increased as the velocity increased as a total heat loss decreased. Flame front structures were clearly observed by the instantaneous schlieren photography.
A Unified Approach for Reporting ARM Measurement Uncertainties Technical Report
Campos, E; Sisterson, DL
2015-10-01
The Atmospheric Radiation Measurement (ARM) Climate Research Facility is observationally based, and quantifying the uncertainty of its measurements is critically important. With over 300 widely differing instruments providing over 2,500 datastreams, concise expression of measurement uncertainty is quite challenging. The ARM Facility currently provides data and supporting metadata (information about the data or data quality) to its users through a number of sources. Because the continued success of the ARM Facility depends on the known quality of its measurements, the Facility relies on instrument mentors and the ARM Data Quality Office (DQO) to ensure, assess, and report measurement quality. Therefore, an easily-accessible, well-articulated estimate of ARM measurement uncertainty is needed.
Uncertainty quantification and validation of combined hydrological and macroeconomic analyses.
Hernandez, Jacquelynne; Parks, Mancel Jordan; Jennings, Barbara Joan; Kaplan, Paul Garry; Brown, Theresa Jean; Conrad, Stephen Hamilton
2010-09-01
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.
Hybrid processing of stochastic and subjective uncertainty data
Cooper, J.A.; Ferson, S.; Ginzburg, L.
1995-11-01
Uncertainty analyses typically recognize separate stochastic and subjective sources of uncertainty, but do not systematically combine the two, although a large amount of data used in analyses is partly stochastic and partly subjective. We have developed methodology for mathematically combining stochastic and subjective data uncertainty, based on new ``hybrid number`` approaches. The methodology can be utilized in conjunction with various traditional techniques, such as PRA (probabilistic risk assessment) and risk analysis decision support. Hybrid numbers have been previously examined as a potential method to represent combinations of stochastic and subjective information, but mathematical processing has been impeded by the requirements inherent in the structure of the numbers, e.g., there was no known way to multiply hybrids. In this paper, we will demonstrate methods for calculating with hybrid numbers that avoid the difficulties. By formulating a hybrid number as a probability distribution that is only fuzzy known, or alternatively as a random distribution of fuzzy numbers, methods are demonstrated for the full suite of arithmetic operations, permitting complex mathematical calculations. It will be shown how information about relative subjectivity (the ratio of subjective to stochastic knowledge about a particular datum) can be incorporated. Techniques are also developed for conveying uncertainty information visually, so that the stochastic and subjective constituents of the uncertainty, as well as the ratio of knowledge about the two, are readily apparent. The techniques demonstrated have the capability to process uncertainty information for independent, uncorrelated data, and for some types of dependent and correlated data. Example applications are suggested, illustrative problems are worked, and graphical results are given.
On flame kernel formation and propagation in premixed gases
Eisazadeh-Far, Kian; Metghalchi, Hameed [Northeastern University, Mechanical and Industrial Engineering Department, Boston, MA 02115 (United States); Parsinejad, Farzan [Chevron Oronite Company LLC, Richmond, CA 94801 (United States); Keck, James C. [Massachusetts Institute of Technology, Cambridge, MA 02139 (United States)
2010-12-15
Flame kernel formation and propagation in premixed gases have been studied experimentally and theoretically. The experiments have been carried out at constant pressure and temperature in a constant volume vessel located in a high speed shadowgraph system. The formation and propagation of the hot plasma kernel has been simulated for inert gas mixtures using a thermodynamic model. The effects of various parameters including the discharge energy, radiation losses, initial temperature and initial volume of the plasma have been studied in detail. The experiments have been extended to flame kernel formation and propagation of methane/air mixtures. The effect of energy terms including spark energy, chemical energy and energy losses on flame kernel formation and propagation have been investigated. The inputs for this model are the initial conditions of the mixture and experimental data for flame radii. It is concluded that these are the most important parameters effecting plasma kernel growth. The results of laminar burning speeds have been compared with previously published results and are in good agreement. (author)
Self-Propagating Assembly of a Molecular-Based Multilayer
Motiei,L.; Altman, M.; Gupta, T.; Lupo, F.; Gulino, A.; Evmenenko, G.; Dutta, P.; van der Boom, M.
2008-01-01
Accelerated growth of a molecular-based material that is an active participant in its continuing self-propagated assembly has been demonstrated. This nonlinear growth process involves diffusion of palladium into a network consisting of metal-based chromophores linked via palladium.
Failure propagation in multi-cell lithium ion batteries
Lamb, Joshua; Orendorff, Christopher J.; Steele, Leigh Anna M.; Spangler, Scott W.
2014-10-22
Traditionally, safety and impact of failure concerns of lithium ion batteries have dealt with the field failure of single cells. However, large and complex battery systems require the consideration of how a single cell failure will impact the system as a whole. Initial failure that leads to the thermal runaway of other cells within the system creates a much more serious condition than the failure of a single cell. This work examines the behavior of small modules of cylindrical and stacked pouch cells after thermal runaway is induced in a single cell through nail penetration trigger [1] within the module.more » Cylindrical cells are observed to be less prone to propagate, if failure propagates at all, owing to the limited contact between neighboring cells. However, the electrical connectivity is found to be impactful as the 10S1P cylindrical cell module did not show failure propagation through the module, while the 1S10P module had an energetic thermal runaway consuming the module minutes after the initiation failure trigger. Modules built using pouch cells conversely showed the impact of strong heat transfer between cells. In this case, a large surface area of the cells was in direct contact with its neighbors, allowing failure to propagate through the entire battery within 60-80 seconds for all configurations (parallel or series) tested. This work demonstrates the increased severity possible when a point failure impacts the surrounding battery system.« less
Corrigendum and addendum. Modeling weakly nonlinear acoustic wave propagation
Christov, Ivan; Christov, C. I.; Jordan, P. M.
2014-12-18
This article presents errors, corrections, and additions to the research outlined in the following citation: Christov, I., Christov, C. I., & Jordan, P. M. (2007). Modeling weakly nonlinear acoustic wave propagation. The Quarterly Journal of Mechanics and Applied Mathematics, 60(4), 473-495.
Failure propagation in multi-cell lithium ion batteries
Lamb, Joshua; Orendorff, Christopher J.; Steele, Leigh Anna M.; Spangler, Scott W.
2014-10-22
Traditionally, safety and impact of failure concerns of lithium ion batteries have dealt with the field failure of single cells. However, large and complex battery systems require the consideration of how a single cell failure will impact the system as a whole. Initial failure that leads to the thermal runaway of other cells within the system creates a much more serious condition than the failure of a single cell. This work examines the behavior of small modules of cylindrical and stacked pouch cells after thermal runaway is induced in a single cell through nail penetration trigger [1] within the module. Cylindrical cells are observed to be less prone to propagate, if failure propagates at all, owing to the limited contact between neighboring cells. However, the electrical connectivity is found to be impactful as the 10S1P cylindrical cell module did not show failure propagation through the module, while the 1S10P module had an energetic thermal runaway consuming the module minutes after the initiation failure trigger. Modules built using pouch cells conversely showed the impact of strong heat transfer between cells. In this case, a large surface area of the cells was in direct contact with its neighbors, allowing failure to propagate through the entire battery within 60-80 seconds for all configurations (parallel or series) tested. This work demonstrates the increased severity possible when a point failure impacts the surrounding battery system.
Beam Propagator for Weather Radars, Modules 1 and 2
Energy Science and Technology Software Center (OSTI)
2013-10-08
This program simulates the beam propagation of weather radar pulses under particular and realistic atmospheric conditions (without using the assumption of standard refraction conditions). It consists of two modules: radiosondings_refract_index_many.pro (MAIN MODULE) beam_propagation_function.pro(EXTERNAL FUNCTION) FOR THE MAIN MODULE, THE CODE DOES OUTPUT--INTO A FILE--THE BEAM HEIGHT AS A FUNCTION OF RANGE. THE RADIOSONDE INPUT FILES SHOULD BE ALREADY AVAILABLE BY THE USER. FOR EXAMPLE, RADIOSONDE OBSERVATION FILES CAN BE OBTAINED AT: RADIOSONDE OBSERVATIONS DOWNLOADED ATmore » "http://weather.uwyo.edu/upperair/soounding.html" OR "http://jervis.pyr.ec.gc.ca" THE EXTERNAL FUNCTION DOES THE ACTUAL COMPUTATION OF BEAM PROPAGATION. IT INCLUDES CONDITIONS OF ANOMALOUS PROPAGATION AND NEGATIVE ELEVATION ANGLES. THE EQUATIONS USED HERE WERE DERIVED BY EDWIN CAMPOS, BASED ON THE SNELL-DESCARTES LAW OF REFRACTION, CONSIDERING THE EARTH CURVATURE. THE PROGRAM REQUIRES A COMPILER FOR THE INTERACTIVE DATA LANGUAGE (IDL). DESCRIPTION AND VALIDATION DETAILS HAVE BEEN PUBLISHED IN THE PEER-REVIEWED SCIENTIFIC LITERATURE, AS FOLLOWS: Campos E. 2012. Estimating weather radar coverage over complex terrain, pp.26-32, peer reviewed, in Weather Radar and Hydrology, edited by Moore RJ, Cole SJ and Illingworth AJ. International Association of Hydrological Sciences (IAHS) Press, IAHS Publ. 351. ISBN 978-1-907161-26-1.« less
ON SUN-TO-EARTH PROPAGATION OF CORONAL MASS EJECTIONS
Liu, Ying D.; Luhmann, Janet G.; Moestl, Christian; Bale, Stuart D.; Lin, Robert P.; Lugaz, Noe; Davies, Jackie A.
2013-05-20
We investigate how coronal mass ejections (CMEs) propagate through, and interact with, the inner heliosphere between the Sun and Earth, a key question in CME research and space weather forecasting. CME Sun-to-Earth kinematics are constrained by combining wide-angle heliospheric imaging observations, interplanetary radio type II bursts, and in situ measurements from multiple vantage points. We select three events for this study, the 2012 January 19, 23, and March 7 CMEs. Different from previous event studies, this work attempts to create a general picture for CME Sun-to-Earth propagation and compare different techniques for determining CME interplanetary kinematics. Key results are obtained concerning CME Sun-to-Earth propagation: (1) the Sun-to-Earth propagation of fast CMEs can be approximately formulated into three phases: an impulsive acceleration, then a rapid deceleration, and finally a nearly constant speed propagation (or gradual deceleration); (2) the CMEs studied here are still accelerating even after the flare maximum, so energy must be continuously fed into the CME even after the time of the maximum heating and radiation has elapsed in the corona; (3) the rapid deceleration, presumably due to interactions with the ambient medium, mainly occurs over a relatively short timescale following the acceleration phase; and (4) CME-CME interactions seem a common phenomenon close to solar maximum. Our comparison between different techniques (and data sets) has important implications for CME observations and their interpretations: (1) for the current cases, triangulation assuming a compact CME geometry is more reliable than triangulation assuming a spherical front attached to the Sun for distances below 50-70 solar radii from the Sun, but beyond about 100 solar radii we would trust the latter more; (2) a proper treatment of CME geometry must be performed in determining CME Sun-to-Earth kinematics, especially when the CME propagation direction is far away from the
Uncertainty Analysis for RELAP5-3D
Aaron J. Pawel; Dr. George L. Mesina
2011-08-01
In its current state, RELAP5-3D is a 'best-estimate' code; it is one of our most reliable programs for modeling what occurs within reactor systems in transients from given initial conditions. This code, however, remains an estimator. A statistical analysis has been performed that begins to lay the foundation for a full uncertainty analysis. By varying the inputs over assumed probability density functions, the output parameters were shown to vary. Using such statistical tools as means, variances, and tolerance intervals, a picture of how uncertain the results are based on the uncertainty of the inputs has been obtained.
Uncertainty quantification in lattice QCD calculations for nuclear physics
Beane, Silas R.; Detmold, William; Orginos, Kostas; Savage, Martin J.
2015-02-05
The numerical technique of Lattice QCD holds the promise of connecting the nuclear forces, nuclei, the spectrum and structure of hadrons, and the properties of matter under extreme conditions with the underlying theory of the strong interactions, quantum chromodynamics. A distinguishing, and thus far unique, feature of this formulation is that all of the associated uncertainties, both statistical and systematic can, in principle, be systematically reduced to any desired precision with sufficient computational and human resources. As a result, we review the sources of uncertainty inherent in Lattice QCD calculations for nuclear physics, and discuss how each is quantified in current efforts.
Path Integral for Dirac oscillator with generalized uncertainty principle
Benzair, H.; Boudjedaa, T.; Merad, M.
2012-12-15
The propagator for Dirac oscillator in (1+1) dimension, with deformed commutation relation of the Heisenberg principle, is calculated using path integral in quadri-momentum representation. As the mass is related to momentum, we then adapt the space-time transformation method to evaluate quantum corrections and this latter is dependent from the point discretization interval.
Thermoacoustic wave propagation modeling using a dynamically adaptive wavelet collocation method
Vasilyev, O.V.; Paolucci, S.
1996-12-31
When a localized region of a solid wall surrounding a compressible medium is subjected to a sudden temperature change, the medium in the immediate neighborhood of that region expands. This expansion generates pressure waves. These thermally-generated waves are referred to as thermoacoustic (TAC) waves. The main interest in thermoacoustic waves is motivated by their property to enhance heat transfer by inducing convective motion away from the heated area. Thermoacoustic wave propagation in a two-dimensional rectangular cavity is studied numerically. The thermoacoustic waves are generated by raising the temperature locally at the walls. The waves, which decay at large time due to thermal and viscous diffusion, propagate and reflect from the walls creating complicated two-dimensional patterns. The accuracy of numerical simulation is ensured by using a highly accurate, dynamically adaptive, multilevel wavelet collocation method, which allows local refinements to adapt to local changes in solution scales. Subsequently, high resolution computations are performed only in regions of large gradients. The computational cost of the method is independent of the dimensionality of the problem and is O(N), where N is the total number of collation points.
Lidar arc scan uncertainty reduction through scanning geometry optimization
Wang, H.; Barthelmie, R. J.; Pryor, S. C.; Brown, G.
2015-10-07
Doppler lidars are frequently operated in a mode referred to as arc scans, wherein the lidar beam scans across a sector with a fixed elevation angle and the resulting measurements are used to derive an estimate of the n minute horizontal mean wind velocity (speed and direction). Previous studies have shown that the uncertainty in the measured wind speed originates from turbulent wind fluctuations and depends on the scan geometry (the arc span and the arc orientation). This paper is designed to provide guidance on optimal scan geometries for two key applications in the wind energy industry: wind turbine powermoreperformance analysis and annual energy production. We present a quantitative analysis of the retrieved wind speed uncertainty derived using a theoretical model with the assumption of isotropic and frozen turbulence, and observations from three sites that are onshore with flat terrain, onshore with complex terrain and offshore, respectively. The results from both the theoretical model and observations show that the uncertainty is scaled with the turbulence intensity such that the relative standard error on the 10 min mean wind speed is about 30 % of the turbulence intensity. The uncertainty in both retrieved wind speeds and derived wind energy production estimates can be reduced by aligning lidar beams with the dominant wind direction, increasing the arc span and lowering the number of beams per arc scan. Large arc spans should be used at sites with high turbulence intensity and/or large wind direction variation when arc scans are used for wind resource assessment.less
Reducing uncertainty in geostatistical description with well testing pressure data
Reynolds, A.C.; He, Nanqun; Oliver, D.S.
1997-08-01
Geostatistics has proven to be an effective tool for generating realizations of reservoir properties conditioned to static data, e.g., core and log data and geologic knowledge. Due to the lack of closely spaced data in the lateral directions, there will be significant variability in reservoir descriptions generated by geostatistical simulation, i.e., significant uncertainty in the reservoir descriptions. In past work, we have presented procedures based on inverse problem theory for generating reservoir descriptions (rock property fields) conditioned to pressure data and geostatistical information represented as prior means for log-permeability and porosity and variograms. Although we have shown that the incorporation of pressure data reduces the uncertainty below the level contained in the geostatistical model based only on static information (the prior model), our previous results assumed did not explicitly account for uncertainties in the prior means and the parameters defining the variogram model. In this work, we investigate how pressure data can help detect errors in the prior means. If errors in the prior means are large and are not taken into account, realizations conditioned to pressure data represent incorrect samples of the a posteriori probability density function for the rock property fields, whereas, if the uncertainty in the prior mean is incorporated properly into the model, one obtains realistic realizations of the rock property fields.
Improved lower bound on the entropic uncertainty relation
Jafarpour, Mojtaba; Sabour, Abbass
2011-09-15
We present a lower bound on the entropic uncertainty relation for the distinguished measurements of two observables in a d-dimensional Hilbert space for d up to 5. This bound provides an improvement over the best one yet available. The feasibility of the obtained bound presenting an improvement for higher dimensions is also discussed.
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
0 Alabama - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S1. Summary statistics for natural gas - Alabama, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7,026 7,063 6,327 R 6,165 6,118 Production (million cubic feet) Gross Withdrawals From Gas Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
6 Arkansas - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S4. Summary statistics for natural gas - Arkansas, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7,397 8,388 8,538 R 9,843 10,150 Production (million cubic feet) Gross Withdrawals From Gas Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
8 California - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S5. Summary statistics for natural gas - California, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 1,580 1,308 1,423 R 1,335 1,118 Production (million cubic feet) Gross Withdrawals From Gas
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
0 Colorado - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S6. Summary statistics for natural gas - Colorado, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 28,813 30,101 32,000 R 32,468 38,346 Production (million cubic feet) Gross Withdrawals From Gas
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
8 Florida - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S10. Summary statistics for natural gas - Florida, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 17,182 16,459 19,742
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
0 Georgia - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. Summary statistics for natural gas - Georgia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
6 Idaho - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S14. Summary statistics for natural gas - Idaho, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
8 Illinois - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S15. Summary statistics for natural gas - Illinois, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 50 40 40 R 34 36 Production (million cubic feet) Gross Withdrawals From Gas Wells E 1,697 2,114
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
2 Iowa - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S17. Summary statistics for natural gas - Iowa, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
4 Kansas - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S18. Summary statistics for natural gas - Kansas, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 22,145 25,758 24,697 R 23,792 24,354 Production (million cubic feet) Gross Withdrawals From Gas Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
6 Kentucky - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S19. Summary statistics for natural gas - Kentucky, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 17,670 14,632 17,936 R 19,494 19,256 Production (million cubic feet) Gross Withdrawals From Gas
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
8 Louisiana - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S20. Summary statistics for natural gas - Louisiana, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 19,137 21,235 19,792 R 19,528 19,251 Production (million cubic feet) Gross Withdrawals From Gas
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
0 Maine - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S21. Summary statistics for natural gas - Maine, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
6 Michigan - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S24. Summary statistics for natural gas - Michigan, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 10,100 11,100 10,900 R 10,550 10,500 Production (million cubic feet) Gross Withdrawals From Gas
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
0 Mississippi - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S26. Summary statistics for natural gas - Mississippi, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 1,979 5,732 1,669 R 1,967 1,645 Production (million cubic feet) Gross Withdrawals From Gas
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
2 Missouri - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S27. Summary statistics for natural gas - Missouri, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 53 100 R 26 28 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 R 8 8 From
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
4 Montana - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S28. Summary statistics for natural gas - Montana, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 6,059 6,477 6,240 5,754 5,754 Production (million cubic feet) Gross Withdrawals From Gas Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
8 Nevada - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S30. Summary statistics for natural gas - Nevada, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 0 0 0 R 4 4 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 3 From Oil Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
4 New Mexico - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S33. Summary statistics for natural gas - New Mexico, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 44,748 32,302 28,206 R 27,073 27,957 Production (million cubic feet) Gross Withdrawals From
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
6 New York - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S34. Summary statistics for natural gas - New York, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 6,736 6,157 7,176 R 6,902 7,119 Production (million cubic feet) Gross Withdrawals From Gas Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
2 Ohio - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S37. Summary statistics for natural gas - Ohio, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 34,931 46,717 35,104 R 32,664 32,967 Production (million cubic feet) Gross Withdrawals From Gas Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
4 Oklahoma - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S38. Summary statistics for natural gas - Oklahoma, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 44,000 41,238 40,000 39,776 40,070 Production (million cubic feet) Gross Withdrawals From Gas
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
6 Oregon - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 26 24 27 R 26 28 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,407 1,344 770 770
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
8 Pennsylvania - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S40. Summary statistics for natural gas - Pennsylvania, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 44,500 54,347 55,136 R 53,762 70,400 Production (million cubic feet) Gross Withdrawals
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
6 Tennessee - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S44. Summary statistics for natural gas - Tennessee, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 230 210 212 R 1,089 1,024 Production (million cubic feet) Gross Withdrawals From Gas Wells 5,144
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
8 Texas - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S45. Summary statistics for natural gas - Texas, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 95,014 100,966 96,617 97,618 98,279 Production (million cubic feet) Gross Withdrawals From Gas Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
0 Utah - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S46. Summary statistics for natural gas - Utah, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 6,075 6,469 6,900 R 7,030 7,275 Production (million cubic feet) Gross Withdrawals From Gas Wells 328,135
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
4 Virginia - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S48. Summary statistics for natural gas - Virginia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 7,470 7,903 7,843 R 7,956 7,961 Production (million cubic feet) Gross Withdrawals From Gas Wells
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
8 West Virginia - Natural Gas 2014 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S50. Summary statistics for natural gas - West Virginia, 2010-2014 2010 2011 2012 2013 2014 Number of Producing Gas Wells at End of Year 52,498 56,813 50,700 R 54,920 60,000 Production (million cubic feet) Gross Withdrawals
Incorporating Experimental Information in the Total Monte Carlo Methodology Using File Weights
Helgesson, P.; Sjöstrand, H.; Koning, A.J.; Rochman, D.; Alhassan, E.; Pomp, S.
2015-01-15
Some criticism has been directed towards the Total Monte Carlo method because experimental information has not been taken into account in a statistically well-founded manner. In this work, a Bayesian calibration method is implemented by assigning weights to the random nuclear data files and the method is illustratively applied to a few applications. In some considered cases, the estimated nuclear data uncertainties are significantly reduced and the central values are significantly shifted. The study suggests that the method can be applied both to estimate uncertainties in a more justified way and in the search for better central values. Some improvements are however necessary; for example, the treatment of outliers and cross-experimental correlations should be more rigorous and random files that are intended to be prior files should be generated.
Franco, Guillermo; Shen-Tu, Bing Ming; Bazzurro, Paolo; Goretti, Agostino; Valensise, Gianluca
2008-07-08
Increasing sophistication in the insurance and reinsurance market is stimulating the move towards catastrophe models that offer a greater degree of flexibility in the definition of model parameters and model assumptions. This study explores the impact of uncertainty in the input parameters on the loss estimates by departing from the exclusive usage of mean values to establish the earthquake event mechanism, the ground motion fields, or the damageability of the building stock. Here the potential losses due to a repeat of the 1908 Messina-Reggio Calabria event are calculated using different plausible alternatives found in the literature that encompass 12 event scenarios, 2 different ground motion prediction equations, and 16 combinations of damage functions for the building stock, a total of 384 loss scenarios. These results constitute the basis for a sensitivity analysis of the different assumptions on the loss estimates that allows the model user to estimate the impact of the uncertainty on input parameters and the potential spread of the model results. For the event under scrutiny, average losses would amount today to about 9.000 to 10.000 million Euros. The uncertainty in the model parameters is reflected in the high coefficient of variation of this loss, reaching approximately 45%. The choice of ground motion prediction equations and vulnerability functions of the building stock contribute the most to the uncertainty in loss estimates. This indicates that the application of non-local-specific information has a great impact on the spread of potential catastrophic losses. In order to close this uncertainty gap, more exhaustive documentation practices in insurance portfolios will have to go hand in hand with greater flexibility in the model input parameters.
Dynamic characteristic of intense short microwave propagation in an atmosphere
Yee, J.H.; Alvarez, R.A.; Mayhall, D.J.; Madsen, N.K.; Cabayan, H.S.
1983-07-01
The dynamic behavior of an intense microwave pulse which propagates through the atmosphere will be presented. Our theoretical results are obtained by solving Maxwell's equations, together with the electron fluid equations. Our calculations show that although large portions of the initial energy are absorbed by the electrons that are created through the avalanche process, a significant amount of energy is still able to reach the earth's surface. The amount of energy that reaches the earth's surface as a function of initial energy and wave shape after having propagated through 100 km in the atmosphere are investigated. Results for the air breakdown threshold intensity as a function of the pressure for different pulse widths and different frequencies will also be presented. In addition, we will present a comparison between the theoretical and the experimental results for the pulse shape of a short microwave pulse after it has traveled through a rectangular wave guide which contains a section of air. 23 references, 9 figures.
Propagation of ultra-short solitons in stochastic Maxwell's equations
Kurt, Levent; Schäfer, Tobias
2014-01-15
We study the propagation of ultra-short short solitons in a cubic nonlinear medium modeled by nonlinear Maxwell's equations with stochastic variations of media. We consider three cases: variations of (a) the dispersion, (b) the phase velocity, (c) the nonlinear coefficient. Using a modified multi-scale expansion for stochastic systems, we derive new stochastic generalizations of the short pulse equation that approximate the solutions of stochastic nonlinear Maxwell's equations. Numerical simulations show that soliton solutions of the short pulse equation propagate stably in stochastic nonlinear Maxwell's equations and that the generalized stochastic short pulse equations approximate the solutions to the stochastic Maxwell's equations over the distances under consideration. This holds for both a pathwise comparison of the stochastic equations as well as for a comparison of the resulting probability densities.
Modeling Crack Propagation in Polycrystalline Microstructure Using Variational Multiscale Method
Sun, S.; Sundararaghavan, V.
2016-01-01
Crack propagation in a polycrystalline microstructure is analyzed using a novel multiscale model. The model includes an explicit microstructural representation at critical regions (stress concentrators such as notches and cracks) and a reduced order model that statistically captures the microstructure at regions far away from stress concentrations. Crack propagation is modeled in these critical regions using the variational multiscale method. In this approach, a discontinuous displacement field is added to elements that exceed the critical values of normal or tangential tractions during loading. Compared to traditional cohesive zone modeling approaches, the method does not require the use of any specialmore » interface elements in the microstructure and thus can model arbitrary crack paths. The capability of the method in predicting both intergranular and transgranular failure modes in an elastoplastic polycrystal is demonstrated under tensile and three-point bending loads.« less
Numerical investigation of spontaneous flame propagation under RCCI conditions
Bhagatwala, Ankit V; Sankaran, Ramanan; Kokjohn, Sage; Chen, Jacqueline H
2015-06-30
This paper presents results from one and two-dimensional direct numerical simulations under Reactivity Controlled Compression Ignition (RCCI) conditions of a primary reference fuel (PRF) mixture consisting of n-heptane and iso-octane. RCCI uses in-cylinder blending of two fuels with different autoignition characteristics to control combustion phasing and the rate of heat release. These simulations employ an improved model of compression heating through mass source/sink terms developed in a previous work by Bhagatwala et al. (2014), which incorporates feedback from the flow to follow a predetermined experimental pressure trace. Two-dimensional simulations explored parametric variations with respect to temperature stratification, pressure profiles andmore » n-heptane concentration. Furthermore, statistics derived from analysis of diffusion/reaction balances locally normal to the flame surface were used to elucidate combustion characteristics for the different cases. Both deflagration and spontaneous ignition fronts were observed to co-exist, however it was found that higher n-heptane concentration provided a greater degree of flame propagation, whereas lower n-heptane concentration (higher fraction of iso-octane) resulted in more spontaneous ignition fronts. A significant finding was that simulations initialized with a uniform initial temperature and a stratified n-heptane concentration field, resulted in a large fraction of combustion occurring through flame propagation. The proportion of spontaneous ignition fronts increased at higher pressures due to shorter ignition delay when other factors were held constant. For the same pressure and fuel concentration, the contribution of flame propagation to the overall combustion was found to depend on the level of thermal stratification, with higher initial temperature gradients resulting in more deflagration and lower gradients generating more ignition fronts. Statistics of ignition delay are computed to assess the Zel
Computation of Diffractive Beam Propagation of Monochromatic Light
Energy Science and Technology Software Center (OSTI)
1999-02-20
Computation of diffractive beam propagation of monochromatic light through a l-dimensional (slab) structure defined by a piecewise continuous complex index of refraction. Finite difference equations are fourth-order-accurate in the lateral grid size and include discontinuities of higher-order field derivatives at dielectric interfaces. Variable grid spacing is allowed, and all dielectric interfaces are assumed to coincide with grid points.
Estimating propagation velocity through a surface acoustic wave sensor
Xu, Wenyuan; Huizinga, John S.
2010-03-16
Techniques are described for estimating the propagation velocity through a surface acoustic wave sensor. In particular, techniques which measure and exploit a proper segment of phase frequency response of the surface acoustic wave sensor are described for use as a basis of bacterial detection by the sensor. As described, use of velocity estimation based on a proper segment of phase frequency response has advantages over conventional techniques that use phase shift as the basis for detection.
Studying Resist Stochastics with the Multivariate Poisson Propagation Model
Naulleau, Patrick; Anderson, Christopher; Chao, Weilun; Bhattarai, Suchit; Neureuther, Andrew
2014-01-01
Progress in the ultimate performance of extreme ultraviolet resist has arguably decelerated in recent years suggesting an approach to stochastic limits both in photon counts and material parameters. Here we report on the performance of a variety of leading extreme ultraviolet resist both with and without chemical amplification. The measured performance is compared to stochastic modeling results using the Multivariate Poisson Propagation Model. The results show that the best materials are indeed nearing modeled performance limits.
Numerical investigation of spontaneous flame propagation under RCCI conditions
Bhagatwala, Ankit V; Sankaran, Ramanan; Kokjohn, Sage; Chen, Jacqueline H
2015-06-30
This paper presents results from one and two-dimensional direct numerical simulations under Reactivity Controlled Compression Ignition (RCCI) conditions of a primary reference fuel (PRF) mixture consisting of n-heptane and iso-octane. RCCI uses in-cylinder blending of two fuels with different autoignition characteristics to control combustion phasing and the rate of heat release. These simulations employ an improved model of compression heating through mass source/sink terms developed in a previous work by Bhagatwala et al. (2014), which incorporates feedback from the flow to follow a predetermined experimental pressure trace. Two-dimensional simulations explored parametric variations with respect to temperature stratification, pressure profiles and n-heptane concentration. Furthermore, statistics derived from analysis of diffusion/reaction balances locally normal to the flame surface were used to elucidate combustion characteristics for the different cases. Both deflagration and spontaneous ignition fronts were observed to co-exist, however it was found that higher n-heptane concentration provided a greater degree of flame propagation, whereas lower n-heptane concentration (higher fraction of iso-octane) resulted in more spontaneous ignition fronts. A significant finding was that simulations initialized with a uniform initial temperature and a stratified n-heptane concentration field, resulted in a large fraction of combustion occurring through flame propagation. The proportion of spontaneous ignition fronts increased at higher pressures due to shorter ignition delay when other factors were held constant. For the same pressure and fuel concentration, the contribution of flame propagation to the overall combustion was found to depend on the level of thermal stratification, with higher initial temperature gradients resulting in more deflagration and lower gradients generating more ignition fronts. Statistics of ignition delay are computed to assess the Zel
Modeling of Propagation of Interacting Cracks Under Hydraulic Pressure Gradient
Huang, Hai; Mattson, Earl Douglas; Podgorney, Robert Karl
2015-04-01
A robust and reliable numerical model for fracture initiation and propagation, which includes the interactions among propagating fractures and the coupling between deformation, fracturing and fluid flow in fracture apertures and in the permeable rock matrix, would be an important tool for developing a better understanding of fracturing behaviors of crystalline brittle rocks driven by thermal and (or) hydraulic pressure gradients. In this paper, we present a physics-based hydraulic fracturing simulator based on coupling a quasi-static discrete element model (DEM) for deformation and fracturing with conjugate lattice network flow model for fluid flow in both fractures and porous matrix. Fracturing is represented explicitly by removing broken bonds from the network to represent microcracks. Initiation of new microfractures and growth and coalescence of the microcracks leads to the formation of macroscopic fractures when external and/or internal loads are applied. The coupled DEM-network flow model reproduces realistic growth pattern of hydraulic fractures. In particular, simulation results of perforated horizontal wellbore clearly demonstrate that elastic interactions among multiple propagating fractures, fluid viscosity, strong coupling between fluid pressure fluctuations within fractures and fracturing, and lower length scale heterogeneities, collectively lead to complicated fracturing patterns.
2009 Total Energy Production by State | Department of Energy
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
Total Energy Production by State 2009 Total Energy Production by State 2009 Total Energy Production by State...
Problems with propagation and time evolution inf(T)gravity (Journal...
Office of Scientific and Technical Information (OSTI)
Problems with propagation and time evolution inf(T)gravity Citation Details In-Document Search Title: Problems with propagation and time evolution inf(T)gravity Authors: Ong, Yen...
Propagating spectroscopy of backward volume spin waves in a metallic FeNi film
Sato, N.; Ishida, N.; Kawakami, T.; Sekiguchi, K.
2014-01-20
We report a propagating spin wave spectroscopy for a magnetostatic backward volume spin wave in a metallic Fe{sub 19}Ni{sub 81} film. We show that the mutual-inductance between two independent antennas detects a small but clear propagation signal of backward volume spin waves. All experimental data are consistent with the time-domain propagating spin-wave spectroscopy. The control of propagating backward spin wave enables to realize the miniaturize spin-wave circuit.
Cell Total Activity Final Estimate.xls
Office of Legacy Management (LM)
WSSRAP Cell Total Activity Final Estimate (calculated September 2002, Fleming) (Waste streams & occupied cell volumes from spreadsheet titled "cell waste volumes-8.23.02 with macros.xls") Waste Stream a Volume (cy) Mass (g) 2 Radiological Profile 3 Nuclide Activity (Ci) 4 Total % of Total U-238 U-234 U-235 Th-228 Th-230 Th-232 Ra-226 Ra-228 Rn-222 5 Activity if > 1% Raffinate Pits Work Zone (Ci) Raffinate processed through CSS Plant 1 159990 1.49E+11 Raffinate 6.12E+01 6.12E+01
Giant dipole resonance parameters with uncertainties from photonuclear cross sections
Plujko, V.A.; Capote, R.; Gorbachenko, O.M.
2011-09-15
Updated values and corresponding uncertainties of isovector giant dipole resonance (IVGDR or GDR) model parameters are presented that are obtained by the least-squares fitting of theoretical photoabsorption cross sections to experimental data. The theoretical photoabsorption cross section is taken as a sum of the components corresponding to excitation of the GDR and quasideuteron contribution to the experimental photoabsorption cross section. The present compilation covers experimental data as of January 2010. - Highlights: {yields} Experimental {sigma} ({gamma}, abs) or a sum of partial cross sections are taken as input to the fitting. {yields} Data include contributions from photoproton reactions. {yields} Standard (SLO) or modified (SMLO) Lorentzian approaches are used for formulating GDR models. {yields} Spherical or axially deformed nuclear shapes are used in GDR least-squares fit. {yields} Values and uncertainties of the SLO and SMLO GDR model parameters are tabulated.
Investigation of uncertainty components in Coulomb blockade thermometry
Hahtela, O. M.; Heinonen, M.; Manninen, A.; Meschke, M.; Savin, A.; Pekola, J. P.; Gunnarsson, D.; Prunnila, M.; Penttil, J. S.; Roschier, L.
2013-09-11
Coulomb blockade thermometry (CBT) has proven to be a feasible method for primary thermometry in every day laboratory use at cryogenic temperatures from ca. 10 mK to a few tens of kelvins. The operation of CBT is based on single electron charging effects in normal metal tunnel junctions. In this paper, we discuss the typical error sources and uncertainty components that limit the present absolute accuracy of the CBT measurements to the level of about 1 % in the optimum temperature range. Identifying the influence of different uncertainty sources is a good starting point for improving the measurement accuracy to the level that would allow the CBT to be more widely used in high-precision low temperature metrological applications and for realizing thermodynamic temperature in accordance to the upcoming new definition of kelvin.
Reduction in maximum time uncertainty of paired time signals
Theodosiou, G.E.; Dawson, J.W.
1983-10-04
Reduction in the maximum time uncertainty (t[sub max]--t[sub min]) of a series of paired time signals t[sub 1] and t[sub 2] varying between two input terminals and representative of a series of single events where t[sub 1][<=]t[sub 2] and t[sub 1]+t[sub 2] equals a constant, is carried out with a circuit utilizing a combination of OR and AND gates as signal selecting means and one or more time delays to increase the minimum value (t[sub min]) of the first signal t[sub 1] closer to t[sub max] and thereby reduce the difference. The circuit may utilize a plurality of stages to reduce the uncertainty by factors of 20--800. 6 figs.
Reduction in maximum time uncertainty of paired time signals
Theodosiou, George E.; Dawson, John W.
1983-01-01
Reduction in the maximum time uncertainty (t.sub.max -t.sub.min) of a series of paired time signals t.sub.1 and t.sub.2 varying between two input terminals and representative of a series of single events where t.sub.1 .ltoreq.t.sub.2 and t.sub.1 +t.sub.2 equals a constant, is carried out with a circuit utilizing a combination of OR and AND gates as signal selecting means and one or more time delays to increase the minimum value (t.sub.min) of the first signal t.sub.1 closer to t.sub.max and thereby reduce the difference. The circuit may utilize a plurality of stages to reduce the uncertainty by factors of 20-800.
Reduction in maximum time uncertainty of paired time signals
Theodosiou, G.E.; Dawson, J.W.
1981-02-11
Reduction in the maximum time uncertainty (t/sub max/ - t/sub min/) of a series of paired time signals t/sub 1/ and t/sub 2/ varying between two input terminals and representative of a series of single events where t/sub 1/ less than or equal to t/sub 2/ and t/sub 1/ + t/sub 2/ equals a constant, is carried out with a circuit utilizing a combination of OR and AND gates as signal selecting means and one or more time delays to increase the minimum value (t/sub min/) of the first signal t/sub 1/ closer to t/sub max/ and thereby reduce the difference. The circuit may utilize a plurality of stages to reduce the uncertainty by factors of 20 to 800.
Charges versus taxes under uncertainty: A look from investment theory
Kohlhaas, M.
1996-12-31
The search for more cost-efficient economic instruments for environmental protection has been conducted with different priorities in the USA and most European countries. Whereas in Europe there seems to prevail a preference for charges and taxes, in the USA tradeable permits are preferred. Environmental policy has to take into consideration the trade-off between price uncertainty and ecological effectiveness. In the short run and on a national level, ecological effectiveness is less important, and price uncertainty is smaller with environmental taxes. In the long run and in an international framework, environmental constraints and repercussions on world market prices of energy become more important. Since taxes are politically more accepted in Europe, it would make sense to start with an ecological tax reform, which can be transformed or integrated into a system of internationally tradeable permits gradually.
Uncertainties in nuclear transition matrix elements of neutrinoless ?? decay
Rath, P. K.
2013-12-30
To estimate the uncertainties associated with the nuclear transition matrix elements M{sup (K)} (K=0?/0N) for the 0{sup +} ? 0{sup +} transitions of electron and positron emitting modes of the neutrinoless ?? decay, a statistical analysis has been performed by calculating sets of eight (twelve) different nuclear transition matrix elements M{sup (K)} in the PHFB model by employing four different parameterizations of a Hamiltonian with pairing plus multipolar effective two-body interaction and two (three) different parameterizations of Jastrow short range correlations. The averages in conjunction with their standard deviations provide an estimate of the uncertainties associated the nuclear transition matrix elements M{sup (K)} calculated within the PHFB model, the maximum of which turn out to be 13% and 19% owing to the exchange of light and heavy Majorana neutrinos, respectively.
Neutron reactions and climate uncertainties earn Los Alamos scientists DOE
U.S. Department of Energy (DOE) all webpages (Extended Search)
Early Career awards DOE Early Career awards Neutron reactions and climate uncertainties earn Los Alamos scientists DOE Early Career awards Marian Jandel and Nathan Urban are among the 61 national recipients of the Energy Department's Early Career Research Program awards for 2013. May 10, 2013 Marian Jandel (left) and Nathan Urban Marian Jandel (left) and Nathan Urban Contact Nancy Ambrosiano Communications Office (505) 667-0471 Email Marian and Nathan are excellent examples of the
Optimization of Complex Energy System Under Uncertainty | Argonne
U.S. Department of Energy (DOE) all webpages (Extended Search)
Leadership Computing Facility Optimization of Complex Energy System Under Uncertainty PI Name: Mihai Anitescu PI Email: anitescu@mcs.anl.gov Institution: Argonne National Laboratory Allocation Program: INCITE Allocation Hours at ALCF: 10,000,000 Year: 2012 Research Domain: Energy Technologies The U.S. electrical power system is at a crossroads between its mission to deliver cheap and safe electrical energy, a strategic aim to increase the penetration of renewable energy, an increased
Optimization of Complex Energy System Under Uncertainty | Argonne
U.S. Department of Energy (DOE) all webpages (Extended Search)
Leadership Computing Facility On the left: This shows the Illinois power grid system overlaid on fields portraying electricity prices under a deterministic economic dispatch scenario. Dark blue areas have the lowest prices while red and yellow have the highest. Argonne National Laboratory researchers use a model of the Illinois grid to test algorithms for making power dispatch decisions under uncertainty. On the right: This shows electricity prices in Illinois under a stochastic economic
Lidar arc scan uncertainty reduction through scanning geometry optimization
Wang, Hui; Barthelmie, Rebecca J.; Pryor, Sara C.; Brown, Gareth.
2016-04-13
Doppler lidars are frequently operated in a mode referred to as arc scans, wherein the lidar beam scans across a sector with a fixed elevation angle and the resulting measurements are used to derive an estimate of the n minute horizontal mean wind velocity (speed and direction). Previous studies have shown that the uncertainty in the measured wind speed originates from turbulent wind fluctuations and depends on the scan geometry (the arc span and the arc orientation). This paper is designed to provide guidance on optimal scan geometries for two key applications in the wind energy industry: wind turbine power performance analysis and annualmore » energy production prediction. We present a quantitative analysis of the retrieved wind speed uncertainty derived using a theoretical model with the assumption of isotropic and frozen turbulence, and observations from three sites that are onshore with flat terrain, onshore with complex terrain and offshore, respectively. The results from both the theoretical model and observations show that the uncertainty is scaled with the turbulence intensity such that the relative standard error on the 10 min mean wind speed is about 30 % of the turbulence intensity. The uncertainty in both retrieved wind speeds and derived wind energy production estimates can be reduced by aligning lidar beams with the dominant wind direction, increasing the arc span and lowering the number of beams per arc scan. Large arc spans should be used at sites with high turbulence intensity and/or large wind direction variation.« less
Lidar arc scan uncertainty reduction through scanning geometry optimization
Wang, Hui; Barthelmie, Rebecca J.; Pryor, Sara C.; Brown, Gareth.
2016-04-13
Doppler lidars are frequently operated in a mode referred to as arc scans, wherein the lidar beam scans across a sector with a fixed elevation angle and the resulting measurements are used to derive an estimate of the n minute horizontal mean wind velocity (speed and direction). Previous studies have shown that the uncertainty in the measured wind speed originates from turbulent wind fluctuations and depends on the scan geometry (the arc span and the arc orientation). This paper is designed to provide guidance on optimal scan geometries for two key applications in the wind energy industry: wind turbine power performance analysis and annualmore » energy production prediction. We present a quantitative analysis of the retrieved wind speed uncertainty derived using a theoretical model with the assumption of isotropic and frozen turbulence, and observations from three sites that are onshore with flat terrain, onshore with complex terrain and offshore, respectively. The results from both the theoretical model and observations show that the uncertainty is scaled with the turbulence intensity such that the relative standard error on the 10 min mean wind speed is about 30% of the turbulence intensity. The uncertainty in both retrieved wind speeds and derived wind energy production estimates can be reduced by aligning lidar beams with the dominant wind direction, increasing the arc span and lowering the number of beams per arc scan. As a result, large arc spans should be used at sites with high turbulence intensity and/or large wind direction variation.« less
Comment on ''Improved bounds on entropic uncertainty relations''
Bosyk, G. M.; Portesi, M.; Plastino, A.; Zozor, S.
2011-11-15
We provide an analytical proof of the entropic uncertainty relations presented by J. I. de Vicente and J. Sanchez-Ruiz [Phys. Rev. A 77, 042110 (2008)] and also show that the replacement of Eq. (27) by Eq. (29) in that reference introduces solutions that do not take fully into account the constraints of the problem, which in turn lead to some mistakes in their treatment.
Computational Fluid Dynamics & Large-Scale Uncertainty Quantification for
U.S. Department of Energy (DOE) all webpages (Extended Search)
Wind Energy Fluid Dynamics & Large-Scale Uncertainty Quantification for Wind Energy - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery
TotalView Parallel Debugger at NERSC
U.S. Department of Energy (DOE) all webpages (Extended Search)
The performance of the GUI can be greatly improved if used in conjunction with free NX software. The TotalView documentation web page is a good resource for learning more...
Million Cu. Feet Percent of National Total
U.S. Energy Information Administration (EIA) (indexed site)
-3,826 Total Supply 854,673 908,380 892,923 R 900,232 828,785 See footnotes at end of ... Gas Annual 165 Table S43. Summary statistics for natural gas - South Dakota, ...
Total Ore Processing Integration and Management
Leslie Gertsch; Richard Gertsch
2004-06-30
This report outlines the technical progress achieved for project DE-FC26-03NT41785 (Total Ore Processing Integration and Management) during the period 01 April through 30 June of 2004.
EQUUS Total Return Inc | Open Energy Information
Open Energy Information (Open El) [EERE & EIA]
Jump to: navigation, search Name: EQUUS Total Return Inc Place: Houston, Texas Product: A business development company and VC investor that trades as a closed-end fund. EQUUS is...
Million Cu. Feet Percent of National Total
as known volumes of natural gas that were the result of leaks, damage, accidents, migration, andor blow down. Notes: Totals may not add due to independent rounding. Prices are...
ARM - Measurement - Net broadband total irradiance
U.S. Department of Energy (DOE) all webpages (Extended Search)
govMeasurementsNet broadband total irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Net broadband total irradiance The difference between upwelling and downwelling, covering longwave and shortwave radiation. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each
ARM - Measurement - Shortwave broadband total downwelling irradiance
U.S. Department of Energy (DOE) all webpages (Extended Search)
downwelling irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Shortwave broadband total downwelling irradiance The total diffuse and direct radiant energy that comes from some continuous range of directions, at wavelengths between 0.4 and 4 {mu}m, that is being emitted downwards. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following
Error and uncertainty in Raman thermal conductivity measurements
Thomas Edwin Beechem; Yates, Luke; Graham, Samuel
2015-04-22
We investigated error and uncertainty in Raman thermal conductivity measurements via finite element based numerical simulation of two geometries often employed -- Joule-heating of a wire and laser-heating of a suspended wafer. Using this methodology, the accuracy and precision of the Raman-derived thermal conductivity are shown to depend on (1) assumptions within the analytical model used in the deduction of thermal conductivity, (2) uncertainty in the quantification of heat flux and temperature, and (3) the evolution of thermomechanical stress during testing. Apart from the influence of stress, errors of 5% coupled with uncertainties of ±15% are achievable for most materialsmore » under conditions typical of Raman thermometry experiments. Error can increase to >20%, however, for materials having highly temperature dependent thermal conductivities or, in some materials, when thermomechanical stress develops concurrent with the heating. A dimensionless parameter -- termed the Raman stress factor -- is derived to identify when stress effects will induce large levels of error. Together, the results compare the utility of Raman based conductivity measurements relative to more established techniques while at the same time identifying situations where its use is most efficacious.« less
Errors and Uncertainties in Dose Reconstruction for Radiation Effects Research
Strom, Daniel J.
2008-04-14
Dose reconstruction for studies of the health effects of ionizing radiation have been carried out for many decades. Major studies have included Japanese bomb survivors, atomic veterans, downwinders of the Nevada Test Site and Hanford, underground uranium miners, and populations of nuclear workers. For such studies to be credible, significant effort must be put into applying the best science to reconstructing unbiased absorbed doses to tissues and organs as a function of time. In many cases, more and more sophisticated dose reconstruction methods have been developed as studies progressed. For the example of the Japanese bomb survivors, the dose surrogate “distance from the hypocenter” was replaced by slant range, and then by TD65 doses, DS86 doses, and more recently DS02 doses. Over the years, it has become increasingly clear that an equal level of effort must be expended on the quantitative assessment of uncertainty in such doses, and to reducing and managing uncertainty. In this context, this paper reviews difficulties in terminology, explores the nature of Berkson and classical uncertainties in dose reconstruction through examples, and proposes a path forward for Joint Coordinating Committee for Radiation Effects Research (JCCRER) Project 2.4 that requires a reasonably small level of effort for DOSES-2008.
Error and uncertainty in Raman thermal conductivity measurements
Thomas Edwin Beechem; Yates, Luke; Graham, Samuel
2015-04-22
We investigated error and uncertainty in Raman thermal conductivity measurements via finite element based numerical simulation of two geometries often employed -- Joule-heating of a wire and laser-heating of a suspended wafer. Using this methodology, the accuracy and precision of the Raman-derived thermal conductivity are shown to depend on (1) assumptions within the analytical model used in the deduction of thermal conductivity, (2) uncertainty in the quantification of heat flux and temperature, and (3) the evolution of thermomechanical stress during testing. Apart from the influence of stress, errors of 5% coupled with uncertainties of ±15% are achievable for most materials under conditions typical of Raman thermometry experiments. Error can increase to >20%, however, for materials having highly temperature dependent thermal conductivities or, in some materials, when thermomechanical stress develops concurrent with the heating. A dimensionless parameter -- termed the Raman stress factor -- is derived to identify when stress effects will induce large levels of error. Together, the results compare the utility of Raman based conductivity measurements relative to more established techniques while at the same time identifying situations where its use is most efficacious.
Composite Multilinearity, Epistemic Uncertainty and Risk Achievement Worth
E. Borgonovo; C. L. Smith
2012-10-01
Risk Achievement Worth is one of the most widely utilized importance measures. RAW is defined as the ratio of the risk metric value attained when a component has failed over the base case value of the risk metric. Traditionally, both the numerator and denominator are point estimates. Relevant literature has shown that inclusion of epistemic uncertainty i) induces notable variability in the point estimate ranking and ii) causes the expected value of the risk metric to differ from its nominal value. We obtain the conditions under which the equality holds between the nominal and expected values of a reliability risk metric. Among these conditions, separability and state-of-knowledge independence emerge. We then study how the presence of epistemic uncertainty aspects RAW and the associated ranking. We propose an extension of RAW (called ERAW) which allows one to obtain a ranking robust to epistemic uncertainty. We discuss the properties of ERAW and the conditions under which it coincides with RAW. We apply our findings to a probabilistic risk assessment model developed for the safety analysis of NASA lunar space missions.
Achieving Robustness to Uncertainty for Financial Decision-making
Barnum, George M.; Van Buren, Kendra L.; Hemez, Francois M.; Song, Peter
2014-01-10
This report investigates the concept of robustness analysis to support financial decision-making. Financial models, that forecast future stock returns or market conditions, depend on assumptions that might be unwarranted and variables that might exhibit large fluctuations from their last-known values. The analysis of robustness explores these sources of uncertainty, and recommends model settings such that the forecasts used for decision-making are as insensitive as possible to the uncertainty. A proof-of-concept is presented with the Capital Asset Pricing Model. The robustness of model predictions is assessed using info-gap decision theory. Info-gaps are models of uncertainty that express the “distance,” or gap of information, between what is known and what needs to be known in order to support the decision. The analysis yields a description of worst-case stock returns as a function of increasing gaps in our knowledge. The analyst can then decide on the best course of action by trading-off worst-case performance with “risk”, which is how much uncertainty they think needs to be accommodated in the future. The report also discusses the Graphical User Interface, developed using the MATLAB® programming environment, such that the user can control the analysis through an easy-to-navigate interface. Three directions of future work are identified to enhance the present software. First, the code should be re-written using the Python scientific programming software. This change will achieve greater cross-platform compatibility, better portability, allow for a more professional appearance, and render it independent from a commercial license, which MATLAB® requires. Second, a capability should be developed to allow users to quickly implement and analyze their own models. This will facilitate application of the software to the evaluation of proprietary financial models. The third enhancement proposed is to add the ability to evaluate multiple models simultaneously
Bixler, Nathan E.; Osborn, Douglas M.; Sallaberry, Cedric Jean-Marie; Eckert-Gallup, Aubrey Celia; Mattie, Patrick D.; Ghosh, S. Tina
2014-02-01
This paper describes the convergence of MELCOR Accident Consequence Code System, Version 2 (MACCS2) probabilistic results of offsite consequences for the uncertainty analysis of the State-of-the-Art Reactor Consequence Analyses (SOARCA) unmitigated long-term station blackout scenario at the Peach Bottom Atomic Power Station. The consequence metrics evaluated are individual latent-cancer fatality (LCF) risk and individual early fatality risk. Consequence results are presented as conditional risk (i.e., assuming the accident occurs, risk per event) to individuals of the public as a result of the accident. In order to verify convergence for this uncertainty analysis, as recommended by the Nuclear Regulatory Commission’s Advisory Committee on Reactor Safeguards, a ‘high’ source term from the original population of Monte Carlo runs has been selected to be used for: (1) a study of the distribution of consequence results stemming solely from epistemic uncertainty in the MACCS2 parameters (i.e., separating the effect from the source term uncertainty), and (2) a comparison between Simple Random Sampling (SRS) and Latin Hypercube Sampling (LHS) in order to validate the original results obtained with LHS. Three replicates (each using a different random seed) of size 1,000 each using LHS and another set of three replicates of size 1,000 using SRS are analyzed. The results show that the LCF risk results are well converged with either LHS or SRS sampling. The early fatality risk results are less well converged at radial distances beyond 2 miles, and this is expected due to the sparse data (predominance of “zero” results).
A Two-Step Approach to Uncertainty Quantification of Core Simulators...
Office of Scientific and Technical Information (OSTI)
Journal Article: A Two-Step Approach to Uncertainty Quantification of Core Simulators Citation Details In-Document Search Title: A Two-Step Approach to Uncertainty Quantification of ...
Dubey, P. K. Kumar, Yudhisther; Gupta, Reeta; Jain, Anshul; Gohiya, Chandrashekhar
2014-05-15
The Radiation Force Balance (RFB) technique is well established and most widely used for the measurement of total ultrasonic power radiated by ultrasonic transducer. The technique is used as a primary standard for calibration of ultrasonic transducers with relatively fair uncertainty in the low power (below 1 W) regime. In this technique, uncertainty comparatively increases in the range of few watts wherein the effects such as thermal heating of the target, cavitations, and acoustic streaming dominate. In addition, error in the measurement of ultrasonic power is also caused due to movement of absorber at relatively high radiated force which occurs at high power level. In this article a new technique is proposed which does not measure the balance output during transducer energized state as done in RFB. It utilizes the change in buoyancy of the absorbing target due to local thermal heating. The linear thermal expansion of the target changes the apparent mass in water due to buoyancy change. This forms the basis for the measurement of ultrasonic power particularly in watts range. The proposed method comparatively reduces uncertainty caused by various ultrasonic effects that occur at high power such as overshoot due to momentum of target at higher radiated force. The functionality of the technique has been tested and compared with the existing internationally recommended RFB technique.
LOCA simulation: analysis of rarefaction waves propagating through geometric singularities
Crouzet, Fabien; Faucher, Vincent; Galon, Pascal; Piteau, Philippe; Izquierdo, Patrick
2012-07-01
The propagation of a transient wave through an orifice is investigated for applications to Loss Of Coolant Accident in nuclear plants. An analytical model is proposed for the response of an orifice plate and implemented in the EUROPLEXUS fast transient dynamics software. It includes an acoustic inertial effect in addition to a quasi-steady dissipation term. The model is experimentally validated on a test rig consisting in a single pipe filled with pressurized water. The test rig is designed to generate a rapid depressurization of the pipe, by means of a bursting disk. The proposed model gives results which compare favourably with experimental data. (authors)
Harmonic generation by circularly polarized laser beams propagating in plasma
Agrawal, Ekta; Hemlata,; Jha, Pallavi
2015-04-15
An analytical theory is developed for studying the phenomenon of generation of harmonics by the propagation of an obliquely incident, circularly polarized laser beam in homogeneous, underdense plasma. The amplitudes of second and third harmonic radiation as well as detuning distance have been obtained and their variation with the angle of incidence is analyzed. The amplitude of harmonic radiation increases with the angle of incidence while the detuning distance decreases, for a given plasma electron density. It is observed that the generated second and third harmonic radiation is linearly and elliptically polarized, respectively. The harmonic radiation vanishes at normal incidence of the circularly polarized laser beam.