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dc.contributor.editorAslett, Louis J. M.
dc.contributor.editorCoolen, Frank P. A.
dc.contributor.editorDe Bock, Jasper
dc.description.abstractThis 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.
dc.relation.ispartofseriesSpringerBriefs in Statistics
dc.rightsopen access
dc.subject.classificationbic Book Industry Communication::P Mathematics & science::PB Mathematics::PBT Probability & statistics
dc.subject.classificationbic Book Industry Communication::T Technology, engineering, agriculture::TG Mechanical engineering & materials::TGP Production engineering::TGPR Reliability engineering
dc.subject.classificationbic Book Industry Communication::P Mathematics & science::PB Mathematics::PBT Probability & statistics::PBTB Bayesian inference
dc.subject.otherUncertainty quantification
dc.subject.otherEngineering applications
dc.subject.otherImprecise Probabilities
dc.subject.otherBayesian Statistics
dc.subject.otherMarkov Chains
dc.subject.otherComplex systems
dc.subject.otherInconsistent information
dc.subject.otherModel validation
dc.subject.otherExperimental measurements
dc.subject.otherOpen Access
dc.titleUncertainty in Engineering
dc.title.alternativeIntroduction to Methods and Applications
oapen.imprintSpringer International Publishing
oapen.grant.number[grantnumber unknown]
dc.relationisFundedByH2020 LEIT Space

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Except where otherwise noted, this item's license is described as open access