Computer Simulation Validation pp 271-293 | Cite as

# The Foundations of Verification in Modeling and Simulation

## Abstract

The practice of verification is grounded in mathematics highlighting the fundamental nature of its practice. Models of reality are fundamentally mathematical and verification assures the connection between the modeling intended and achieved in code. Code verification is a process where the correctness of a computer code for simulation and modeling is proven. This “proof” is defined by the collection of evidence that the numerical approximations are congruent with the model for the physical phenomena. **The key metric in code verification is the order of accuracy of the approximation that should match theoretical expectations. In contrast, solution verification is an aspect of uncertainty estimation associated with numerical error in simulations.** Solution verification uses many of the same approaches as code verification, but its principal outcome is an estimate of the numerical error. The order of convergence is a secondary outcome. Together these two practices form an important part of the foundation of quality and credibility in modeling and simulation.

## Keywords

Verification Error estimate Convergence Order-of-accuracy Solution verification Robust statistics## Notes

### Acknowledgements

The author would like to thank Tim Trucano, Vince Mousseau, Patrick Knupp, Bill Oberkampf, Chris Roy, Greg Weirs, and Patrick Roache for numerous discussions and informative suggestions. The DOE ASC V&V program has provided support for the development of the verification methodology. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, National Technology and Engineering Solutions of Sandia, LLC. Operated for the United States Department of Energy by National Technology and Engineering Solutions of Sandia, LLCDE-AC04-94AL85000.

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