"Advances in scientific computing have made modelling and simulation an important part of the decision-making process in engineering, science, and public policy. This book provides a comprehensive and systematic development of the basic concepts, principles, and procedures for verification and validation of models and simulations. The emphasis is placed on models that are described by partial differential and integral equations and the simulations that result from their numerical solution. The methods described can be applied to a wide range of technical fields, from the physical sciences, engineering and technology and industry, through to environmental regulations and safety, product and plant safety, financial investing, and governmental regulations. This book will be genuinely welcomed by researchers, practitioners, and decision makers in a broad range of fields, who seek to improve the credibility and reliability of simulation results. It will also be appropriate either for university courses or forindependent study"--
Arvustused
'This ambitious and well-written book is an excellent comprehensive review of what you need to know to evaluate or build a complex model or simulation of a physical process would be a good textbook for a senior-level engineering or physics undergraduate semester course, particularly a project-based one that develops requirements for a simple prototype numerical model of a system.' Joan Horvath, Computing Reviews 'This book provides a comprehensive and systematic development of basic concepts and procedures for verification and validation of models and simulations.' Zentralblatt MATH
Muu info
Can you trust results from modelling and simulation? Verification, validation, and uncertainty quantification can help.
Preface;
1. Introduction; Part I. Fundamental Concepts:
2. Fundamental
concepts and terminology;
3. Modeling and computational simulation; Part II.
Code Verification:
4. Software engineering;
5. Code verification;
6. Exact
solutions; Part III. Solution Verification:
7. Solution verification;
8.
Discretization error;
9. Solution adaptation; Part IV. Model Validation and
Prediction:
10. Model validation fundamentals;
11. Design and execution of
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. Development and responsibilities
for verification, validation and uncertainty quantification; Appendix.
Programming practices; Index.
William L. Oberkampf has 39 years of experience in research and development in fluid dynamics, heat transfer, flight dynamics, and solid mechanics. He has worked in both computational and experimental areas, and taught 30 short courses in the field of verification and validation. He recently retired as a Distinguished Member of the Technical Staff at Sandia National Laboratories. Christopher J. Roy is Associate Professor in the Department of Aerospace and Ocean Engineering at Virginia Tech University.
Lisainfo e-raamatute kohta