The paper "Verification and Validation in Computational Fluid Dynamics" by William L. Oberkampf and Timothy G. Trucano, prepared by Sandia National Laboratories, reviews the literature on verification and validation (V&V) in computational fluid dynamics (CFD). It discusses methods and procedures for assessing V&V and proposes extensions to existing ideas. The authors trace the development of V&V terminology and methodology, highlighting contributions from operations research (OR), statistics, and CFD communities. They address fundamental issues such as code verification versus solution verification, model validation versus solution validation, and the distinction between error and uncertainty. The paper emphasizes the importance of software testing during verification activities and the need for detailed characterization of experimental conditions and uncertainty estimation in validation experiments. It also introduces a hierarchical methodology for validation, using a hypersonic cruise missile as an example. The authors propose guidelines for designing and conducting validation experiments and discuss statistical estimation of experimental uncertainty. They offer a three-step statistical approach for incorporating experimental uncertainties into computational analysis and present sample problems to demonstrate the construction of validation metrics. Finally, the paper makes recommendations for future research topics and improvements in engineering standards and software development processes.The paper "Verification and Validation in Computational Fluid Dynamics" by William L. Oberkampf and Timothy G. Trucano, prepared by Sandia National Laboratories, reviews the literature on verification and validation (V&V) in computational fluid dynamics (CFD). It discusses methods and procedures for assessing V&V and proposes extensions to existing ideas. The authors trace the development of V&V terminology and methodology, highlighting contributions from operations research (OR), statistics, and CFD communities. They address fundamental issues such as code verification versus solution verification, model validation versus solution validation, and the distinction between error and uncertainty. The paper emphasizes the importance of software testing during verification activities and the need for detailed characterization of experimental conditions and uncertainty estimation in validation experiments. It also introduces a hierarchical methodology for validation, using a hypersonic cruise missile as an example. The authors propose guidelines for designing and conducting validation experiments and discuss statistical estimation of experimental uncertainty. They offer a three-step statistical approach for incorporating experimental uncertainties into computational analysis and present sample problems to demonstrate the construction of validation metrics. Finally, the paper makes recommendations for future research topics and improvements in engineering standards and software development processes.