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Title: Verification Test Suite for Physics Simulation Codes

Abstract

The DOE/NNSA Advanced Simulation & Computing (ASC) Program directs the development, demonstration and deployment of physics simulation codes. The defensible utilization of these codes for high-consequence decisions requires rigorous verification and validation of the simulation software. The physics and engineering codes used at Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and Sandia National Laboratory (SNL) are arguably among the most complex utilized in computational science. Verification represents an important aspect of the development, assessment and application of simulation software for physics and engineering. The purpose of this note is to formally document the existing tri-laboratory suite of verification problems used by LANL, LLNL, and SNL, i.e., the Tri-Lab Verification Test Suite. Verification is often referred to as ensuring that ''the [discrete] equations are solved [numerically] correctly''. More precisely, verification develops evidence of mathematical consistency between continuum partial differential equations (PDEs) and their discrete analogues, and provides an approach by which to estimate discretization errors. There are two variants of verification: (1) code verification, which compares simulation results to known analytical solutions, and (2) calculation verification, which estimates convergence rates and discretization errors without knowledge of a known solution. Together, these verification analyses support defensible verification and validationmore » (V&V) of physics and engineering codes that are used to simulate complex problems that do not possess analytical solutions. Discretization errors (e.g., spatial and temporal errors) are embedded in the numerical solutions of the PDEs that model the relevant governing equations. Quantifying discretization errors, which comprise only a portion of the total numerical simulation error, is possible through code and calculation verification. Code verification computes the absolute value of discretization errors relative to an exact solution of the governing equations. In contrast, calculation verification, which does not utilize a reference solution, combines an assessment of stable self-convergence and exact solution prediction to quantitatively estimate discretization errors. In FY01, representatives of the V&V programs at LANL, LLNL, and SNL identified a set of verification test problems for the Accelerated Strategic Computing Initiative (ASCI) Program. Specifically, a set of code verification test problems that exercise relevant single- and multiple-physics packages was agreed upon. The verification test suite problems can be evaluated in multidimensional geometry and span both smooth and non-smooth behavior.« less

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
898449
Report Number(s):
UCRL-TR-226984
TRN: US200708%%100
DOE Contract Number:  
W-7405-ENG-48
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ANALYTICAL SOLUTION; CONVERGENCE; EXACT SOLUTIONS; FORECASTING; GEOMETRY; NUMERICAL SOLUTION; PARTIAL DIFFERENTIAL EQUATIONS; PHYSICS; SIMULATION; VALIDATION; VERIFICATION

Citation Formats

Brock, J S, Kamm, J R, Rider, W J, Brandon, S, Woodward, C, Knupp, P, and Trucano, T G. Verification Test Suite for Physics Simulation Codes. United States: N. p., 2006. Web. doi:10.2172/898449.
Brock, J S, Kamm, J R, Rider, W J, Brandon, S, Woodward, C, Knupp, P, & Trucano, T G. Verification Test Suite for Physics Simulation Codes. United States. doi:10.2172/898449.
Brock, J S, Kamm, J R, Rider, W J, Brandon, S, Woodward, C, Knupp, P, and Trucano, T G. Thu . "Verification Test Suite for Physics Simulation Codes". United States. doi:10.2172/898449. https://www.osti.gov/servlets/purl/898449.
@article{osti_898449,
title = {Verification Test Suite for Physics Simulation Codes},
author = {Brock, J S and Kamm, J R and Rider, W J and Brandon, S and Woodward, C and Knupp, P and Trucano, T G},
abstractNote = {The DOE/NNSA Advanced Simulation & Computing (ASC) Program directs the development, demonstration and deployment of physics simulation codes. The defensible utilization of these codes for high-consequence decisions requires rigorous verification and validation of the simulation software. The physics and engineering codes used at Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and Sandia National Laboratory (SNL) are arguably among the most complex utilized in computational science. Verification represents an important aspect of the development, assessment and application of simulation software for physics and engineering. The purpose of this note is to formally document the existing tri-laboratory suite of verification problems used by LANL, LLNL, and SNL, i.e., the Tri-Lab Verification Test Suite. Verification is often referred to as ensuring that ''the [discrete] equations are solved [numerically] correctly''. More precisely, verification develops evidence of mathematical consistency between continuum partial differential equations (PDEs) and their discrete analogues, and provides an approach by which to estimate discretization errors. There are two variants of verification: (1) code verification, which compares simulation results to known analytical solutions, and (2) calculation verification, which estimates convergence rates and discretization errors without knowledge of a known solution. Together, these verification analyses support defensible verification and validation (V&V) of physics and engineering codes that are used to simulate complex problems that do not possess analytical solutions. Discretization errors (e.g., spatial and temporal errors) are embedded in the numerical solutions of the PDEs that model the relevant governing equations. Quantifying discretization errors, which comprise only a portion of the total numerical simulation error, is possible through code and calculation verification. Code verification computes the absolute value of discretization errors relative to an exact solution of the governing equations. In contrast, calculation verification, which does not utilize a reference solution, combines an assessment of stable self-convergence and exact solution prediction to quantitatively estimate discretization errors. In FY01, representatives of the V&V programs at LANL, LLNL, and SNL identified a set of verification test problems for the Accelerated Strategic Computing Initiative (ASCI) Program. Specifically, a set of code verification test problems that exercise relevant single- and multiple-physics packages was agreed upon. The verification test suite problems can be evaluated in multidimensional geometry and span both smooth and non-smooth behavior.},
doi = {10.2172/898449},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2006},
month = {12}
}

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