Publications Details

Validation methodology in computational fluid dynamics

Oberkampf, William L.; Trucano, Timothy G.

Verification and validation are the primary means to assess accuracy and reliability in computational simulations. This paper presents an extensive review of the literature in computational validation and develops a number of extensions to existing ideas. We discuss the early work in validation by the operations research, statistics, and CFD communities. The emphasis in our review is to bring together the diverse contributors to validation methodology and procedures. The disadvantages of standard practice of qualitative graphical validation are pointed out and the arguments for and the literature on validation quantification are presented. We discuss the attributes of a beneficial validation experiment hierarchy and then we give an example for a complex system; a hypersonic cruise missile. We present six recommended characteristics of how a validation experiment is designed, executed, and analyzed. Since one of the key features of a validation experiment is a careful experimental uncertainty estimation analysis, we discuss a statistical procedure that has been developed for improving the estimation of experimental uncertainty. One facet of code verification, the estimation of computational error and uncertainty, is discussed in some detail, but we do not address many other important issues in code verification. We argue for the separation of the concepts of error and uncertainty in computational simulations. Error estimation, primarily that due to numerical solution error, is discussed with regard to its importance in validation. In the same vein, we explain the need to move toward nondeterministic simulations in CFD validation, that is, the propagation of input quantity uncertainty in CFD simulations which yield probabilistic output quantities. We discuss the relatively new concept of validation quantification, also referred to as validation metrics. The inadequacy, in our view, of hypothesis testing in computational validation is discussed. We close the paper by presenting our ideas on validation metrics and we apply them to two conceptual examples. © 2000 The American Institute of Aeronautics and Astronautics Inc.