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Title: User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota

Abstract

Sandia’s Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a physics-based computational model. This can lend efficiency and rigor to manual parameter perturbation studies already being conducted by analysts. However, Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. Dakota algorithms enrich complex science and engineering models, enabling an analyst to answer crucial questions of - Sensitivity: Which are the most important input factors or parameters entering the simulation, and how do they influence key outputs?; Uncertainty: What is the uncertainty or variability in simulation output, given uncertainties in input parameters? How safe, reliable, robust, or variable is my system? (Quantification of margins and uncertainty, QMU); Optimization: What parameter values yield the best performing design or operating condition, given constraints? Calibration: Whatmore » models and/or parameters best match experimental data? In general, Dakota is the Consortium for Advanced Simulation of Light Water Reactors (CASL) delivery vehicle for verification, validation, and uncertainty quantification (VUQ) algorithms. It permits ready application of the VUQ methods described above to simulation codes by CASL researchers, code developers, and application engineers.« less

Authors:
 [1];  [2];  [1];  [1];  [1];  [3];  [2];  [1];  [2];  [1];  [2];  [3]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. North Carolina State Univ., Raleigh, NC (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Nuclear Energy (NE)
OSTI Identifier:
1398890
Report Number(s):
LA-UR-17-29083
DOE Contract Number:
AC52-06NA25396
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Dakota; sensitivity analysis; calibration; optimization; uncertainty quantification; experimental design

Citation Formats

Adams, Brian M., Coleman, Kayla, Gilkey, Lindsay N., Gordon, Natalie, Hooper, Russell, Khuwaileh, Bassam A., Lewis, Allison, Maupin, Kathryn, Smith, Ralph C., Swiler, Laura P., Turinsky, Paul J., and Williams, Brian J. User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota. United States: N. p., 2017. Web. doi:10.2172/1398890.
Adams, Brian M., Coleman, Kayla, Gilkey, Lindsay N., Gordon, Natalie, Hooper, Russell, Khuwaileh, Bassam A., Lewis, Allison, Maupin, Kathryn, Smith, Ralph C., Swiler, Laura P., Turinsky, Paul J., & Williams, Brian J. User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota. United States. doi:10.2172/1398890.
Adams, Brian M., Coleman, Kayla, Gilkey, Lindsay N., Gordon, Natalie, Hooper, Russell, Khuwaileh, Bassam A., Lewis, Allison, Maupin, Kathryn, Smith, Ralph C., Swiler, Laura P., Turinsky, Paul J., and Williams, Brian J. 2017. "User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota". United States. doi:10.2172/1398890. https://www.osti.gov/servlets/purl/1398890.
@article{osti_1398890,
title = {User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota},
author = {Adams, Brian M. and Coleman, Kayla and Gilkey, Lindsay N. and Gordon, Natalie and Hooper, Russell and Khuwaileh, Bassam A. and Lewis, Allison and Maupin, Kathryn and Smith, Ralph C. and Swiler, Laura P. and Turinsky, Paul J. and Williams, Brian J.},
abstractNote = {Sandia’s Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a physics-based computational model. This can lend efficiency and rigor to manual parameter perturbation studies already being conducted by analysts. However, Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. Dakota algorithms enrich complex science and engineering models, enabling an analyst to answer crucial questions of - Sensitivity: Which are the most important input factors or parameters entering the simulation, and how do they influence key outputs?; Uncertainty: What is the uncertainty or variability in simulation output, given uncertainties in input parameters? How safe, reliable, robust, or variable is my system? (Quantification of margins and uncertainty, QMU); Optimization: What parameter values yield the best performing design or operating condition, given constraints? Calibration: What models and/or parameters best match experimental data? In general, Dakota is the Consortium for Advanced Simulation of Light Water Reactors (CASL) delivery vehicle for verification, validation, and uncertainty quantification (VUQ) algorithms. It permits ready application of the VUQ methods described above to simulation codes by CASL researchers, code developers, and application engineers.},
doi = {10.2172/1398890},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2017,
month =
}

Technical Report:

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  • Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility. This manual offers Consortium for Advanced Simulation of Light Water Reactors (LWRs) (CASL) partners a guide to conducting Dakota-based VUQ studies for CASL problems. It motivates various classes of Dakota methods and includes examples of their use on representative application problems. On reading, a CASL analyst should understand why and howmore » to apply Dakota to a simulation problem. This SAND report constitutes the product of CASL milestone L3:VUQ.V&V.P8.01 and is also being released as a CASL unlimited release report with number CASL-U-2014-0038-000.« less
  • In general, Dakota is the Consortium for Advanced Simulation of Light Water Reactors (CASL) delivery vehicle for verification, validation, and uncertainty quantification (VUQ) algorithms. It permits ready application of the VUQ methods described above to simulation codes by CASL researchers, code developers, and application engineers. More specifically, the CASL VUQ Strategy [33] prescribes the use of Predictive Capability Maturity Model (PCMM) assessments [37]. PCMM is an expert elicitation tool designed to characterize and communicate completeness of the approaches used for computational model definition, verification, validation, and uncertainty quantification associated with an intended application. Exercising a computational model with the methodsmore » in Dakota will yield, in part, evidence for a predictive capability maturity model (PCMM) assessment. Table 1.1 summarizes some key predictive maturity related activities (see details in [33]), with examples of how Dakota fits in. This manual offers CASL partners a guide to conducting Dakota-based VUQ studies for CASL problems. It motivates various classes of Dakota methods and includes examples of their use on representative application problems. On reading, a CASL analyst should understand why and how to apply Dakota to a simulation problem.« less
  • Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically, it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility. This manual offers Consortium for Advanced Simulation of Light Water Reactors (LWRs) (CASL) partners a guide to conducting Dakota-based VUQ studies for CASL problems. It motivates various classes of Dakota methods and includes examples of their use on representative application problems. On reading, a CASL analyst should understand why and howmore » to apply Dakota to a simulation problem.« less
  • Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility.
  • The Dakota software project serves the mission of Sandia National Laboratories and supports a worldwide user community by delivering state-of-the-art research and robust, usable software for optimization and uncertainty quantification. These capabilities enable advanced exploration and riskinformed prediction with a wide range of computational science and engineering models. Dakota is the verification and validation (V&V) / uncertainty quantification (UQ) software delivery vehicle for CASL, allowing analysts across focus areas to apply these capabilities to myriad nuclear engineering analyses.