Analytic Solutions as a Tool for Verification and Validation of a Multiphysics ModelSource: Journal of Verification, Validation and Uncertainty Quantification:;2020:;volume( 004 ):;issue: 004DOI: 10.1115/1.4045747Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Computational physicists are commonly faced with the task of resolving discrepancies between the predictions of a complex, integrated multiphysics numerical simulation, and corresponding experimental datasets. Such efforts commonly require a slow iterative procedure. However, a different approach is available in casesx where the multiphysics system of interest admits closed-form analytic solutions. In this situation, the ambiguity is conveniently broken into separate consideration of theory–simulation comparisons (issues of verification) and theory–data comparisons (issues of validation). We demonstrate this methodology via application to the specific example of a fluid-instability-based ejecta source model under development at Los Alamos National Laboratory and implemented in flag, a Los Alamos continuum mechanics code. The formalism is conducted in the forward sense (i.e., from source to measurement) and enables us to compute, purely analytically, time-dependent piezoelectric ejecta mass measurements for a specific class of explosively driven metal coupon experiments. We incorporate published measurement uncertainties on relevant experimental parameters to estimate a time-dependent uncertainty on these analytic predictions. This motivates the introduction of a “compatibility score” metric, our primary tool for quantitative analysis of the RMI + SSVD model. Finally, we derive a modification to the model, based on boundary condition considerations, that substantially improves its predictions.
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contributor author | Tregillis, I. L. | |
contributor author | Koskelo, Aaron | |
date accessioned | 2022-02-04T14:38:14Z | |
date available | 2022-02-04T14:38:14Z | |
date copyright | 2020/01/16/ | |
date issued | 2020 | |
identifier issn | 2377-2158 | |
identifier other | vvuq_004_04_041004.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4274075 | |
description abstract | Computational physicists are commonly faced with the task of resolving discrepancies between the predictions of a complex, integrated multiphysics numerical simulation, and corresponding experimental datasets. Such efforts commonly require a slow iterative procedure. However, a different approach is available in casesx where the multiphysics system of interest admits closed-form analytic solutions. In this situation, the ambiguity is conveniently broken into separate consideration of theory–simulation comparisons (issues of verification) and theory–data comparisons (issues of validation). We demonstrate this methodology via application to the specific example of a fluid-instability-based ejecta source model under development at Los Alamos National Laboratory and implemented in flag, a Los Alamos continuum mechanics code. The formalism is conducted in the forward sense (i.e., from source to measurement) and enables us to compute, purely analytically, time-dependent piezoelectric ejecta mass measurements for a specific class of explosively driven metal coupon experiments. We incorporate published measurement uncertainties on relevant experimental parameters to estimate a time-dependent uncertainty on these analytic predictions. This motivates the introduction of a “compatibility score” metric, our primary tool for quantitative analysis of the RMI + SSVD model. Finally, we derive a modification to the model, based on boundary condition considerations, that substantially improves its predictions. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Analytic Solutions as a Tool for Verification and Validation of a Multiphysics Model | |
type | Journal Paper | |
journal volume | 4 | |
journal issue | 4 | |
journal title | Journal of Verification, Validation and Uncertainty Quantification | |
identifier doi | 10.1115/1.4045747 | |
page | 41004 | |
tree | Journal of Verification, Validation and Uncertainty Quantification:;2020:;volume( 004 ):;issue: 004 | |
contenttype | Fulltext |