Publications

Verification, validation, and predictive capability in computational engineering and physics

Bunge, Scott D.; Bunge, Scott D.; Boyle, Timothy J.; Headley, Thomas J.; Kotula, Paul G.; Rodriguez, Marko A.

Developers of computer codes, analysts who use the codes, and decision makers who rely on the results of the analyses face a critical question: How should confidence in modeling and simulation be critically assessed? Verification and validation (V&V) of computational simulations are the primary methods for building and quantifying this confidence. Briefly, verification is the assessment of the accuracy of the solution to a computational model. Validation is the assessment of the accuracy of a computational simulation by comparison with experimental data. In verification, the relationship of the simulation to the real world is not an issue. In validation, the relationship between computation and the real world, i.e., experimental data, is the issue.