Normal view MARC view ISBD view

Uncertainty quantification : an accelerated course with advanced applications in computational engineering

By: Soize, Christian.
Series: Interdisciplinary applied mathematics v. 47.Publisher: Cham Springer 2017Description: xxii, 329 p. ill. (some col.) 24 cm.ISBN: 9783319543383.Subject(s): Information theory | Statistical methods | Data processing | Stochastic models | Applied Mathematics | Computational Methods of Engineering | Engineering mathematics | Probability Theory and Stochastic ProcessesDDC classification: 620.0015192 Summary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
Item type Current location Call number Status Date due Barcode
Books 620.0015192 SOI (Browse shelf) Available 032172

Includes bibliographical references and index.

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.

There are no comments for this item.

Log in to your account to post a comment.

Powered by Koha