Uncertainty in Engineering Introduction to Methods and Applications

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. T...

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Bibliographic Details
Other Authors: Aslett, Louis J. M. (Editor), Coolen, Frank P. A. (Editor), De Bock, Jasper (Editor)
Format: Electronic Book Chapter
Language:English
Published: Bern Springer Nature 2022
Series:SpringerBriefs in Statistics
Subjects:
Online Access:DOAB: download the publication
DOAB: description of the publication
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520 |a 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. 
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653 |a Uncertainty quantification 
653 |a Engineering applications 
653 |a Imprecise Probabilities 
653 |a Bayesian Statistics 
653 |a Markov Chains 
653 |a Reliability 
653 |a Complex systems 
653 |a Inconsistent information 
653 |a Model validation 
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