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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| Format: | Book Chapter |
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Bern
Springer Nature
2022
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| Subjects: | |
| Online Access: | Get Fullteks DOAB: description of the publication |
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| 001 | doab_20_500_12854_74880 | ||
| 005 | 20211214 | ||
| 020 | |a 978-3-030-83640-5 | ||
| 020 | |a 9783030836405 | ||
| 024 | 7 | |a 10.1007/978-3-030-83640-5 |c doi | |
| 041 | 0 | |a English | |
| 042 | |a dc | ||
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| 072 | 7 | |a TGPR |2 bicssc | |
| 072 | 7 | |a PBTB |2 bicssc | |
| 100 | 1 | |a Aslett, Louis J. M. |4 edt | |
| 700 | 1 | |a Coolen, Frank P. A. |4 edt | |
| 700 | 1 | |a De Bock, Jasper |4 edt | |
| 700 | 1 | |a Aslett, Louis J. M. |4 oth | |
| 700 | 1 | |a Coolen, Frank P. A. |4 oth | |
| 700 | 1 | |a De Bock, Jasper |4 oth | |
| 245 | 1 | 0 | |a Uncertainty in Engineering : Introduction to Methods and Applications |
| 260 | |a Bern |b Springer Nature |c 2022 | ||
| 300 | |a 1 electronic resource (147 p.) | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 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. | ||
| 536 | |a H2020 LEIT Space | ||
| 540 | |a Creative Commons |f by/4.0/ |2 cc |4 http://creativecommons.org/licenses/by/4.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Probability & statistics |2 bicssc | |
| 650 | 7 | |a Reliability engineering |2 bicssc | |
| 650 | 7 | |a Bayesian inference |2 bicssc | |
| 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 | ||
| 653 | |a Experimental measurements | ||
| 653 | |a Open Access | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/bitstream/20.500.12657/51957/1/978-3-030-83640-5.pdf |7 0 |z Get Fullteks |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/74880 |7 0 |z DOAB: description of the publication |