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Uncertainty Quantification

An Accelerated Course with Advanced Applications in Computational Engineering

Language EnglishEnglish
E-book Adobe ePub DRM
E-book Uncertainty Quantification Christian Soize
Libristo code: 41039210
Publishers Springer, April 2017
This book presents the fundamental notions and advanced mathematical tools in the stochastic modelin... Full description
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This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it focuses in parametric uncertainties, and non-parametric uncertainties with applications from the structural dynamics and vibroacoustics of complex mechanical systems, from micromechanics and multiscale mechanics of heterogeneous materials. Resulting from a course developed by the author, the book begins with a description of the fundamental mathematical tools of probability and statistics that are directly useful for uncertainty quantification. It proceeds with a well carried out description of some basic and advanced methods for constructing stochastic models of uncertainties, paying particular attention to the problem of calibrating and identifying a stochastic model of uncertainty when experimental data is available. This book is intended to be a graduate-level textbook for students as well as professionals interested in the theory, computation, and applications of risk and prediction in science and engineering fields.

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About the book

Full name Uncertainty Quantification
Language English
Binding E-book - Adobe ePub DRM
Date of issue 2017
EAN 9783319543390
Libristo code 41039210
Publishers Springer
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