Verification, Validation, and Uncertainty Quantification in Scientific Computing

William L. Oberkampf has more than fifty years of experience in research and development in fluid dynamics, heat transfer, and solid mechanics. Over the past twnety-five years he has focused on research and teaching of verification, validation, and uncertainty quantification in modeling and simulation. He is a Fellow of AIAA and a Fellow of NAFEMS. Christopher J. Roy is Professor in the Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech. He has worked primarily in the area of computational fluid dynamics, but has participated in or organized multiple validation experiments. He has taught more than fifty short courses in the field of verification, validation, and uncertainty quantification and has more than 200 publications in the field.

1. Introduction; Part I. Fundamental Concepts: 2. Fundamental concepts and terminology; 3. Modeling and computational simulation; Part II. Code Verification and Software Engineering: 4. Software engineering for scientific computing; 5. Code order-of-accuracy verification; 6. Exact and manufactured solutions; Part III. Solution Verification: 7. Numerical uncertainty estimation; 8. Iterative error; 9. Discretization error; Part IV. Model Validation and Predictive Capability: 10. Model validation fundamentals; 11. Design and execution of model validation experiments; 12. Model accuracy assessment; 13. Predictive capability; Part V. Planning, Management, and Implementation Issues: 14. Planning and prioritization in modeling and simulation; 15. Maturity assessment of modeling and simulation; 16. Verification, validation, and uncertainty quantification responsibilities and management; Index.