Experimentation, Validation, and Uncertainty Analysis for Engineers, 4th Edition

9VALIDATION OF SIMULATIONS

9-1 INTRODUCTION TO VALIDATION METHODOLOGY

Over the past several decades, advances in computing power, modeling approaches, and numerical solution algorithms have increased the ability of the scientific and engineering community to simulate real-world processes to the point that it is realistic for predictions from surprisingly detailed simulations to be used to replace much of the experimentation that was previously necessary to develop designs for new systems and bring them to the market. In the past, it was necessary to test subsystem and system performance at numerous set points covering the expected domain of operation of the system. For large, complex systems such a testing program can be prohibitively expensive, if not outright impossible, with available finite resources.

The current approach seeks to replace some or much of the experimentation with (cheaper) simulation results that have been validated with experimental results at selected set points—but to do this with confidence one must know how good the predictions are at the set points selected for validation and also how good the predictions are in the interpolated or extrapolated regions of the operating domain for which there are no experimental results. This has led to the emergence of the field called verification and validation (V&V) of simulations (e.g., models, codes).

Verification refers to application of approaches to determine that the algorithms solve the equations in the ...