Verification and validation in scientific computing

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 for independent study.

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

Available:*

On Order

Summary

Summary

Table of Contents