A Statistical Sampling Method for Uncertainty Analysis with SCALE and XSUSA

Williams, Mark L.; Ilas, Germina; Jessee, Matthew Anderson; Rearden, Bradley T.; Wiarda, Dorothea; Zwermann, W.; Gallner, L.; Klein, M.; Krzykacz-Hausmann, B.; Pautz, Andreas

doi:10.13182/nt12-112

Cited by 79 publications

(41 citation statements)

References 6 publications

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“…In recent years, the Monte Carlo sampling approach has been playing an increasingly important role in the uncertainty propagation of nuclear data to integral observables (Koning and Rochman, 2008;Sanz et al, 2008;Zwermann et al, 2010;Buss et al, 2011;Williams et al, 2012;Wieselquist et al, 2013). This method consists in random sampling of nuclear data parameters -optionally together with technological and operational parameters -from their joint uncertainty distribution, where each random sample is used in a different computation of the integral variable of interest.…”

Section: Introductionmentioning

confidence: 99%

Improving PWR core simulations by Monte Carlo uncertainty analysis and Bayesian inference

Castro

Ahnert

Buss³

et al. 2016

Annals of Nuclear Energy

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A Monte Carlo-based Bayesian inference model is applied to the prediction of reactor operation parameters of a PWR nuclear power plant. In this non-perturbative framework, high-dimensional covariance information describing the uncertainty of microscopic nuclear data is combined with measured reactor operation data in order to provide statistically sound, well founded uncertainty estimates of integral parameters, such as the boron letdown curve and the burnupdependent reactor power distribution. The performance of this methodology is assessed in a blind test approach, where we use measurements of a given reactor cycle to improve the prediction of the subsequent cycle. As it turns out, the resulting improvement of the prediction quality is impressive. In particular, the prediction uncertainty of the boron letdown curve, which is of utmost importance for the planning of the reactor cycle length, can be reduced by one order of magnitude by including the boron concentration measurement information of the previous cycle in the analysis. Additionally, we present first results of non-perturbative nuclear-data updating and show that predictions obtained with the updated libraries are consistent with those induced by Bayesian inference applied directly to the integral observables.

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Section: Introductionmentioning

confidence: 99%

Improving PWR core simulations by Monte Carlo uncertainty analysis and Bayesian inference

Castro

Ahnert

Buss³

et al. 2016

Annals of Nuclear Energy

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“…The perturbations were generated assuming normal Probability Distribution Functions (PDFs) and random sampling (Williams et al 2013b) and covariances given by the covariance library provided by SCALE. The perturbation are defined as multiplicative factors for each nuclide i, nuclear reaction x and energy group g.…”

Section: Scale621/samplermentioning

confidence: 99%

“…After the input parameters are isolated, new perturbation factors must be created using DAKOTA statistical tool. As indicated in Williams et al 2013b, perturbations in the original perturbation library are randomly generated and follow a normal PDF with average one and covariance given by the covariance library. Here, the user is free to keep or change the distribution for each isotope-reaction pair and/or the sampling method.…”

Section: Perturbation Library Generationmentioning

confidence: 99%

Uncertainty Quantification and Sensitivity Analysis for Cross Sections and Thermohydraulic Parameters in Lattice and Core Physics Codes. Methodology for Cross Section Library Generation and Application to PWR and BWR.

Melia¹

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"There are three certainties in life: death, taxes and bugs in computer codes." Modified quote of Benjamin Franklin"Hi ha tres certeses en la vida: la mort, impostos i errades en programes informàtics."Modificació de la cita de Benjamin Franklin "Hay tres certezas en la vida: la muerte, impuestos y fallos en programas informáticos." Modificación de la cita de Benjamin Franklin AbstractThis PhD study, developed at Universitat Politècnica de València (UPV), aims to cover the first phase of the benchmark released by the expert group on Uncertainty Analysis in Modeling (UAM-LWR). The main contribution to the benchmark, made by the thesis' author, is the development of a Matlab program requested by the benchmark organizers. This is used to generate neutronic libraries to distribute among the benchmark participants. The UAM benchmark pretends to determine the uncertainty introduced by coupled multi-physics and multi-scale LWR analysis codes. The benchmark is subdivided into three phases:1. Neutronic phase: obtain collapsed and homogenized problem-dependent cross sections and criticality analyses.2. Core phase: standalone thermohydraulic and neutronic codes.3. System phase: coupled thermohydraulic and neutronic code.In this thesis the objectives of the first phase are covered. Specifically, a methodology is developed to propagate the uncertainty of cross sections and other neutronic parameters through a lattice physics code and core simulator. An Uncertainty and Sensitivity (U&S) analysis is performed over the cross sections contained in the ENDF/B-VII nuclear library. Their uncertainty is propagated through the lattice physics code SCALE6.2.1, including the collapse and homogenization phase, up to the generation of problem-dependent neutronic libraries. Afterward, the uncertainty contained in these libraries can be further propagated through a core simulator, in this study PARCSv3.2. The module SAMPLER -available in the latest release of SCALEand DAKOTA 6.3 statistical tool are used for the U&S analysis. As a part of this process, a methodology to obtain neutronic libraries in NEMTAB format -to be used in a core simulator-is also developed. A code-to-code comparison with CASMO-4 is used as a verification. The whole methodology is tested using a Boiling Water Reactor (BWR) reactor type. Nevertheless, there is not any concern or limitation regarding its use in any other type of nuclear reactor.The Gesellschaft für Anlagen und Reaktorsicherheit (GRS) stochastic methodology for uncertainty quantification is used. This methodology makes use of the high-fidelity model and nonparametric sampling to propagate the uncertainty. As a result, the number of samples (determined using the revised Wilk's formula) does not depend on the number of input parameters but only on the desired confidence and uncertainty of output parameters. Moreover, the output Probability Distribution Functions (PDFs) are not subject to normality. The main disadvantage is that each input parameter must have a pre-defined PDF. If possible, input PDFs are de...

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“…La aplicación de esta metodología en esta tesis, concretamente para la propagación de incertidumbres a cálculos de núcleo completo, se ha llevado a cabo gracias a la secuencia SAMPLER de SCALE, incorporada en la versión 6.2 que incluye el paquete XSUSA [134,135,138]. Este sistema muestrea las secciones eficaces microscópicas de forma que se obtienen N conjuntos de librerías de secciones eficaces para ser empleadas en N cálculos de transporte y obtener así N conjuntos de secciones eficaces homogeneizadas.…”

Section: Metodología Basada En Muestreounclassified

“…Estos factores multiplicativos se utilizan para obtener factores de Bondarenko y valores de secciones eficaces puntuales perturbados, ambos necesarios para llevar a cabo el autoblindaje con los módulos BONAMI y CENTRM/PMC respectivamente. Información más detallada sobre la metodología de muestreo e implantación de XSUSA en SCALE está disponible en [134,135].…”

Section: Samplerunclassified

Generación de librerías optimizadas con cuantificación de incertidumbres para cálculos realistas (BEPU) de reactores nucleares de agua ligera

Huerta¹

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A Statistical Sampling Method for Uncertainty Analysis with SCALE and XSUSA

Cited by 79 publications

References 6 publications

Improving PWR core simulations by Monte Carlo uncertainty analysis and Bayesian inference

Improving PWR core simulations by Monte Carlo uncertainty analysis and Bayesian inference

Uncertainty Quantification and Sensitivity Analysis for Cross Sections and Thermohydraulic Parameters in Lattice and Core Physics Codes. Methodology for Cross Section Library Generation and Application to PWR and BWR.

Generación de librerías optimizadas con cuantificación de incertidumbres para cálculos realistas (BEPU) de reactores nucleares de agua ligera

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