LEADER 03834nam 22007215 450 001 9910512173403321 005 20250505000811.0 010 $a3-030-83640-1 024 7 $a10.1007/978-3-030-83640-5 035 $a(CKB)5590000000631161 035 $a(MiAaPQ)EBC6824949 035 $a(Au-PeEL)EBL6824949 035 $a(OCoLC)1290485018 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/74880 035 $a(PPN)259386650 035 $a(DE-He213)978-3-030-83640-5 035 $a(ODN)ODN0010074464 035 $a(oapen)doab74880 035 $a(EXLCZ)995590000000631161 100 $a20211209d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aUncertainty in Engineering $eIntroduction to Methods and Applications /$fedited by Louis J. M. Aslett, Frank P. A. Coolen, Jasper De Bock 205 $a1st ed. 2022. 210 $d2021 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (148 pages) 225 1 $aSpringerBriefs in Statistics,$x2191-5458 311 08$a3-030-83639-8 327 $aIntroduction to Bayesian statistical inference -- Sampling from complex probability distributions: a Monte Carlo primer for engineers -- Introduction to the theory of imprecise probability -- Imprecise discrete-time Markov chains -- Statistics with imprecise probabilities ? a short survey -- Reliability -- Simulation methods for the analysis of complex systems -- Overview of stochastic model updating in aerospace application under uncertainty treatment -- Aerospace flight modeling and experimental testing. 330 $aThis open access book provides an introduction to uncertainty quanti?cation in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The ?nal two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quanti?cation for aerospace ?ight modelling. Written by experts in the subject, and based on lectures given at the Second Training School of the European Research and Training Network UTOPIAE (Uncertainty Treatment and Optimization in Aerospace Engineering), which took place at Durham University (United Kingdom) from 2 to 6 July 2018, the book offers an essential resource for students as well as scientists and practitioners. 410 0$aSpringerBriefs in Statistics,$x2191-5458 606 $aStatistics 606 $aStatistics 606 $aIndustrial engineering 606 $aProduction engineering 606 $aStatistical Theory and Methods 606 $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences 606 $aIndustrial and Production Engineering 606 $aBayesian Inference 615 0$aStatistics. 615 0$aStatistics. 615 0$aIndustrial engineering. 615 0$aProduction engineering. 615 14$aStatistical Theory and Methods. 615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aIndustrial and Production Engineering. 615 24$aBayesian Inference. 676 $a519.5 686 $aMAT029000$aMAT029010$aTEC032000$2bisacsh 700 $aAslett$b Louis J. M$01075841 701 $aCoolen$b Frank P. A$01075842 701 $aDe Bock$b Jasper$01075843 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910512173403321 996 $aUncertainty in Engineering$92585666 997 $aUNINA