Uncertainty in Engineering

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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গ্রন্থ-পঞ্জীর বিবরন
বিন্যাস: Online
ভাষা:ইংরেজি
প্রকাশিত: Springer Nature 2021
বিষয়গুলি:
অনলাইন ব্যবহার করুন:ONIX_20211213_9783030836405_33
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collection Directory of Open Access Books
description 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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language eng
publishDate 2021
publishDateRange 2021
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publisher Springer Nature
publisherStr Springer Nature
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spelling doab-20.500.12854ir-748802025-07-30T11:55:55Z 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 thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGP Production and industrial engineering::TGPR Reliability engineering thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGP Production and industrial engineering::TGPR Reliability engineering thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and 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. 2021-12-14T04:01:33Z 2021-12-14T04:01:33Z 2021-12-13T18:55:49Z 2022 book ONIX_20211213_9783030836405_33 ONIX_20211213_9783030836405_33 OCN: 1289370872 https://library.oapen.org/handle/20.500.12657/51957 9783030836405 https://directory.doabooks.org/handle/20.500.12854/74880 eng SpringerBriefs in Statistics open access image/jpeg image/jpeg image/jpeg n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/51957/1/978-3-030-83640-5.pdf https://library.oapen.org/bitstream/20.500.12657/51957/1/978-3-030-83640-5.pdf https://library.oapen.org/bitstream/20.500.12657/51957/1/978-3-030-83640-5.pdf Springer Nature Springer International Publishing 10.1007/978-3-030-83640-5 10.1007/978-3-030-83640-5 9fa3421d-f917-4153-b9ab-fc337c396b5a H2020 LEIT Space 03cb9764-92f8-439b-86ef-7cdc5132117b 9783030836405 Springer International Publishing 147 Bern [grantnumber unknown] open access
spellingShingle Uncertainty quantification
Engineering applications
Imprecise Probabilities
Bayesian Statistics
Markov Chains
Reliability
Complex systems
Inconsistent information
Model validation
Experimental measurements
Open Access
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGP Production and industrial engineering::TGPR Reliability engineering
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGP Production and industrial engineering::TGPR Reliability engineering
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
Uncertainty in Engineering
title Uncertainty in Engineering
title_full Uncertainty in Engineering
title_fullStr Uncertainty in Engineering
title_full_unstemmed Uncertainty in Engineering
title_short Uncertainty in Engineering
title_sort uncertainty in engineering
topic Uncertainty quantification
Engineering applications
Imprecise Probabilities
Bayesian Statistics
Markov Chains
Reliability
Complex systems
Inconsistent information
Model validation
Experimental measurements
Open Access
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGP Production and industrial engineering::TGPR Reliability engineering
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGP Production and industrial engineering::TGPR Reliability engineering
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
topic_facet Uncertainty quantification
Engineering applications
Imprecise Probabilities
Bayesian Statistics
Markov Chains
Reliability
Complex systems
Inconsistent information
Model validation
Experimental measurements
Open Access
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGP Production and industrial engineering::TGPR Reliability engineering
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGP Production and industrial engineering::TGPR Reliability engineering
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
url ONIX_20211213_9783030836405_33