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.-3 -This paper presents our viewpoint of the state of the art in V&V in computational physics. (In this paper we refer to all fields of computational engineering and physics, e.g., computational fluid dynamics, computational solid mechanics, structural dynamics, shock wave physics, computational chemistry, etc., as computational physics.) We do not provide a comprehensive review of the multitudinous contributions to V&V, although we do reference a large number of previous works from many fields. We have attempted to bring together many different perspectives on V&V, highlight those perspectives that are effective from a practical engineering viewpoint, suggest future research topics, and discuss key implementation issues that are necessary to improve the effectiveness of V&V. We describe our view of the framework in which predictive capability relies on V&V, as well as other factors that affect predictive capability. Our opinions about the research needs and management issues in V&V are very practical: What methods and techniques need to be developed and what changes in the views of management need to occur to increase the usefulness, reliability, and impact of computational physics for decision making about engineering systems?We review the state of the art in V&V over a wide range of topics, for example, prioritization of V&V activities using the Phenomena Identification and Ranking Table (PIRT), code verification, software quality assurance (SQA), numerical error estimation, hierarchical experiments for validation, characteristics of validation experiments, the need to perform nondeterministic computational simulations in comparisons with experimental data, and validation metrics. We then provide an extensive discussion of V&V research and implementation issues that we believe must be addressed for V&V to be more effective in improving confidence in computational predictive capability. Some of the research topics addressed are development of improved procedures for the use of the PIRT for prioritizing V&V activities, the method of manufactured solutions for code verification, development and use of hierarchical validation diagrams, and the construction and use of validation metrics incorporating statistical measures. Some of the implementation topics address...

We have studied gas flow and particle deposition in a realistic three-dimensional (3D) model of the bronchial tree, extending from the trachea to the segmental bronchi (7th airway generation for the most distal ones) using computational fluid dynamics. The model is based on the morphometrical data of Horsfield et al. (Horsfield K, Dart G, Olson DE, Filley GF, and Cumming G. J Appl Physiol 31: 207-217, 1971) and on bronchoscopic and computerized tomography images, which give the spatial 3D orientation of the curved ducts. It incorporates realistic angles of successive branching planes. Steady inspiratory flow varying between 50 and 500 cm(3)/s was simulated, as well as deposition of spherical aerosol particles (1-7 microm diameter, 1 g/cm(3) density). Flow simulations indicated nonfully developed flows in the branches due to their relative short lengths. Velocity flow profiles in the segmental bronchi, taken one diameter downstream of the bifurcation, were distorted compared with the flow in a simple curved tube, and wide patterns of secondary flow fields were observed. Both were due to the asymmetrical 3D configuration of the bifurcating network. Viscous pressure drop in the model was compared with results obtained by Pedley et al. (Pedley TJ, Schroter RC, and Sudlow MF. Respir Physiol 9: 387-405, 1970), which are shown to be a good first approximation. Particle deposition increased with particle size and was minimal for approximately 200 cm(3)/s inspiratory flow, but it was highly heterogeneous for branches of the same generation.

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