Christian Soize: Uncertainty Quantification

Cover: 9783319543383 | Uncertainty Quantification | Christian Soize | Buch | xxii | Englisch

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Beschreibung

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.

Über den Autor

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.

Zusammenfassung

Presents fundamental mathematical tools of probability and statistics that are directly useful for uncertainty quantification

Includes several topics not currently published in research monographs

Covers the basic models and advanced methodologies for constructing the stochastic modeling of uncertainties

Inhaltsverzeichnis

Fundamental Notions in Stochastic Modeling of Uncertainties and their Propagation in Computational Models.- Elements of Probability Theory.- Markov Process and Stochastic Differential Equation.- MCMC Methods for Generating Realizations and for Estimating the Mathematical Expectation of Nonlinear Mappings of Random Vectors.- Fundamental Probabilistic Tools for Stochastic Modeling of Uncertainties.- Brief Overview of Stochastic Solvers for the Propagation of Uncertainties.- Fundamental Tools for Statistical Inverse Problems.- Uncertainty Quantification in Computational Structural Dynamics and Vibroacoustics.- Robust Analysis with Respect to the Uncertainties for Analysis, Updating, Optimization, and Design.- Random Fields and Uncertainty Quantification in Solid Mechanics of Continuum Media.

Details

Erscheinungsjahr:	2017
Fachbereich:	EDV
Genre:	Informatik , Mathematik , Medizin , Naturwissenschaften , Technik
Rubrik:	Naturwissenschaften & Technik
Thema:	Lexika
Medium:	Buch
Reihe:	Interdisciplinary Applied Mathematics
Inhalt:	xxii 329 S. 24 s/w Illustr. 86 farbige Illustr. 329 p. 110 illus. 86 illus. in color.
ISBN-13:	9783319543383
ISBN-10:	3319543385
Sprache:	Englisch
Einband:	Gebunden
Autor:	Soize, Christian
Hersteller:	Springer-Verlag GmbH Springer International Publishing
Verantwortliche Person für die EU:	Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Abbildungen:	24 schwarz-weiße und 84 farbige Abbildungen, Bibliographie
Maße:	241 x 160 x 25 mm
Von/Mit:	Christian Soize
Erscheinungsdatum:	11.05.2017
Gewicht:	0,694 kg

Artikel-ID: 109045589