Uncertainty in engineering : introduction to methods and applications /

Uncertainty in engineering : introduction to methods and applications /

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Bibliographic Details
Imprint:	Cham : Springer, [2022] ©2022
Description:	1 online resource (148 pages) : illustrations (chiefly color)
Language:	English
Series:	SpringerBriefs in statistics SpringerBriefs in statistics.
Subject:	Engineering -- Statistical methods. Probabilities. Uncertainty. Probability Engineering -- Statistical methods. Probabilities. Uncertainty.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/13397834

Hidden Bibliographic Details
Other authors / contributors:	Aslett, Louis J. M., editor. Coolen, Franciscus Petrus Antonius, 1965- editor. De Bock, Jasper, editor.
ISBN:	9783030836405 3030836401 9783030836399
Notes:	Includes bibliographical references. Open access Print version record.
Summary:	This open access book provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The final two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quantification for aerospace flight modelling. Written by experts in the subject, and based on lectures given at the Second Training School of the European Research and Training Network UTOPIAE (Uncertainty Treatment and Optimization in Aerospace Engineering), which took place at Durham University (United Kingdom) from 2 to 6 July 2018, the book offers an essential resource for students as well as scientists and practitioners.
Other form:	Print version: Aslett, Louis J.M. Uncertainty in Engineering. Cham : Springer International Publishing AG, ©2022 9783030836399
Standard no.:	10.1007/978-3-030-83640-5

Description
Summary:	<p>This open access book provides an introduction to uncertainty quantiﬁcation in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The ﬁnal two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quantiﬁcation for aerospace ﬂight modelling.</p> Written by experts in the subject, and based on lectures given at the Second Training School of the European Research and Training Network UTOPIAE (Uncertainty Treatment and Optimization in Aerospace Engineering), which took place at Durham University (United Kingdom) from 2 to 6 July 2018, the book offers an essential resource for students as well as scientists and practitioners.
Physical Description:	1 online resource (148 pages) : illustrations (chiefly color)
Bibliography:	Includes bibliographical references.
ISBN:	9783030836405 3030836401 9783030836399
Access:	Open access