Local Truncation Error-Informed Code Verification

Author:

Krueger Aaron M.1,Mousseau Vincent A.2,Hassan Yassin A.1

Affiliation:

1. Department of Nuclear Engineering, Texas A&M University, College Station, TX 77843

2. Sandia National Laboratories, Albuquerque, NM 87123

Abstract

Abstract The method of manufactured solutions (MMS) has become increasingly popular in conducting code verification studies on predictive codes, such as nuclear power system codes and computational fluid dynamic codes. The reason for the popularity of this approach is that it can be used when an analytical solution is not available. Using MMS, code developers are able to verify that their code is free of coding errors that impact the observed order of accuracy. While MMS is still an excellent tool for code verification, it does not identify coding errors that are of the same order as the numerical method. This paper presents a method that combines MMS with modified equation analysis (MEA), which calculates the local truncation error (LTE) to identify coding error up to and including the order of the numerical method. This method is referred to as modified equation analysis methd of manufactured solutions (MEAMMS). MEAMMS is then applied to a custom-built code, which solves the shallow water equations, to test the performance of the code verification method. MEAMMS is able to detect all coding errors that impact the implementation of the numerical scheme. To show how MEAMMS is different than MMS, they are both applied to the same first-order numerical method test problem with a first-order coding error. When there are first-order coding errors, only MEAMMS is able to identify them. This shows that MEAMMS is able to identify a larger set of coding errors while still being able to identify the coding errors MMS is able to identify.

Publisher

ASME International

Subject

Computational Theory and Mathematics,Computer Science Applications,Modelling and Simulation,Statistics and Probability

Reference29 articles.

1. Impact of Coding Mistakes on Numerical Error and Uncertainty in Solutions to PDEs,2007

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