Soize, Christian <br/><br/>
Uncertainty quantification :  an accelerated course with advanced applications in computational engineering / 
Christian Soize 
 - Switzerland  Springer  2017 
 - 329 p. 
<br/><br/> This book presents the fundamental notions and advanced mathematical tools in the stochastic modelling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it focuses on 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. <br/><br/>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. <br/><br/>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. 
<br/><br/><label>ISBN: </label>9783319853727 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Uncertainty--Mathematical models<br/>Engineering mathematics<br/>Mathematics<br/>Probabilities<br/>Computer science--Mathematics<br/>Engineering--Mathematical models<br/>Stochastic models
<br/><br/><label>Dewey Class. No.: </label>003.54 SOI-C