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oapen-20.500.12657-519572021-12-14T02:46:10Z Uncertainty in Engineering Aslett, Louis J. M. Coolen, Frank P. A. De Bock, Jasper Uncertainty quantification Engineering applications Imprecise Probabilities Bayesian Statistics Markov Chains Reliability Complex systems Inconsistent information Model validation Experimental measurements Open Access bic Book Industry Communication::P Mathematics & science::PB Mathematics::PBT Probability & statistics bic Book Industry Communication::T Technology, engineering, agriculture::TG Mechanical engineering & materials::TGP Production engineering::TGPR Reliability engineering bic Book Industry Communication::P Mathematics & science::PB Mathematics::PBT Probability & statistics::PBTB Bayesian inference 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. 2021-12-13T18:55:49Z 2021-12-13T18:55:49Z 2022 book ONIX_20211213_9783030836405_33 9783030836405 https://library.oapen.org/handle/20.500.12657/51957 eng SpringerBriefs in Statistics application/pdf n/a 978-3-030-83640-5.pdf https://link.springer.com/978-3-030-83640-5 Springer Nature Springer International Publishing 10.1007/978-3-030-83640-5 10.1007/978-3-030-83640-5 6c6992af-b843-4f46-859c-f6e9998e40d5 03cb9764-92f8-439b-86ef-7cdc5132117b 9783030836405 Springer International Publishing 147 Bern [grantnumber unknown] H2020 LEIT Space H2020 Leadership in enabling and industrial technologies – Space open access
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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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