T�tulo: Uncertainty Quantification: An Accelerated Course with Advanced Applications in Computational Engineering (Interdisciplinary Applied Mathematics, 47)
Editor: Springer
Fecha de publicaci�n: 2018
Idioma: Ingl�s
ISBN 10: 3319853724
ISBN 13: 9783319853727
Encuadernaci�n: Encuadernaci�n de tapa blanda
Estado: New

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Sinopsis

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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Christian Soize is professor at Universite Paris-Est Marne-la-Valee. His research interests include stochastic modeling of uncertainties in computational mechanics, their propagation and their quantification.

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