Assessing the Reliability of Complex Models: Mathematical and Statistical Foundations of Verification, Validation, and Uncertainty Quantification
2012

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Advances in computing hardware and algorithms have dramatically improved the ability to simulate complex processes computationally. Today's simulation capabilities offer the prospect of addressing questions that in the past could be addressed only by resource-intensive experimentation, if at all. Assessing the Reliability of Complex Models recognizes the ubiquity of uncertainty in computational estimates of reality and the necessity for its quantification.

As computational science and engineering have matured, the process of quantifying or bounding uncertainties in a computational estimate of a physical quality of interest has evolved into a small set of interdependent tasks: verification, validation, and uncertainty of quantification (VVUQ). In recognition of the increasing importance of computational simulation and the increasing need to assess uncertainties in computational results, the National Research Council was asked to study the mathematical foundations of VVUQ and to recommend steps that will ultimately lead to improved processes.

Assessing the Reliability of Complex Models discusses changes in education of professionals and dissemination of information that should enhance the ability of future VVUQ practitioners to improve and properly apply VVUQ methodologies to difficult problems, enhance the ability of VVUQ customers to understand VVUQ results and use them to make informed decisions, and enhance the ability of all VVUQ stakeholders to communicate with each other. This report is an essential resource for all decision and policy makers in the field, students, stakeholders, UQ experts, and VVUQ educators and practitioners.

Publication information

144 pages · 8.5 x 11 · paperback
ISBN Paperback: 0-309-25634-8
ISBN Ebook: 0-309-25635-6
DOI: https://doi.org/10.17226/13395

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National Research Council. 2012. Assessing the Reliability of Complex Models: Mathematical and Statistical Foundations of Verification, Validation, and Uncertainty Quantification. Washington, DC: The National Academies Press.

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Front Matter i-xii
Summary 1-6
1 Introduction 7-18
2 Sources of Uncertainty and Error 19-30
3 Verification 31-36
4 Emulation, Reduced-Order Modeling, and Forward Propagation 37-51
5 Model Validation and Prediction 52-85
6 Making Decisions 86-94
7 Next Steps in Practice, Research, and Education for Verification, Validation, and Uncertainty Quantification 95-106
Appendixes 107-108
Appendix A: Glossary 109-119
Appendix B: Agendas of Committee Meetings 120-123
Appendix C: Committee Biographies 124-129
Appendix D: Acronyms 130-132

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Assessing the Reliability of Complex Models: Mathematical and Statistical Foundations of Verification, Validation, and Uncertainty Quantification (2012)

Chapter: Appendixes

Publication information

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Assessing the Reliability of Complex Models: Mathematical and Statistical Foundations of Verification, Validation, and Uncertainty Quantification (2012)

Chapter: Appendixes