Uncertainty quantification : an accelerated course with advanced applications in computational engineering
- Cham Springer 2017
- xxii, 329 p. ill. (some col.) 24 cm
- Interdisciplinary applied mathematics v. 47 .
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. 9783319543383
Information theory Statistical methods Data processing Stochastic models Applied Mathematics Computational Methods of Engineering Engineering mathematics Probability Theory and Stochastic Processes