9780309256346 - assessing the reliability of complex models: mathematical and statistical foundations of verification, validation, and uncertainty quantification (mathematics) von national research council; division on engineering and physical sci; board on mathematical sciences and their (2 Ergebnisse)
Assessing the Reliability of Complex Models: Mathematical and Statistical Foundations of Verification, Validation, and Uncertainty Quantification
National Research Council; Division on Engineering and Physical Sci; Board on Mathematical Sciences and Their
- Softcover
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Paperback. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
- Softcover
- Erstausgabe
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Trade paperback. Zustand: Very good. Presumed First Edition, First printing. xi, [1], 131, [1] pages. Footnotes. Formulae. Figures (some with color). Boxes (some with color). References. In recognition of the increasing importance of computational simulation and the increasing need to assess uncertainties in computational result…s, the National Research Council (NRC) was asked to study the mathematical foundations of VVUQ and to recommend steps that will ultimately lead to improved processes. The specific tasking to the Committee on Mathematical Foundations of Verification, Validation, and Uncertainty Quantification is as follows: ? A committee of the National Research Council will examine practices for VVUQ of large-scale computational simulations in several research communities. ? The committee will identify common concepts, terms, approaches, tools, and best practices of VVUQ. ? The committee will identify mathematical sciences research needed to establish a foundation for building a science of verification and validation (V&V) and for improving the practice of VVUQ. ? The committee will recommend educational changes needed in the mathematical sciences community and mathematical sciences education needed by other scientific communities to most effectively use VVUQ. 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.
