Uncertainty Quantification : An Accelerated Course with Advanced Applications in Computational Engineering

Christian Soize

ISBN 10: 3319543385 / ISBN 13: 9783319543383

Published by Springer-Verlag Gmbh, 2017

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783319543383

Bibliographic Details

• Title: Uncertainty Quantification : An Accelerated Course with Advanced Applications in Computational Engineering
• Publisher: Springer-Verlag Gmbh
• Publication Date: 2017
• Language: English
• ISBN 10: 3319543385
• ISBN 13: 9783319543383
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 25D millimeters 241 millimeters width by 160 millimeters height by 25 millimeters depth
• Weight: 694 grams

About this title

Synopsis

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.

About the Author

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.