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contributor authorKarl Breitung
date accessioned2022-02-01T21:39:18Z
date available2022-02-01T21:39:18Z
date issued12/1/2021
identifier otherAJRUA6.0001166.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4271779
description abstractThe calculation of failure probabilities is one of the basic problems in structural reliability. But to understand the causes of failure, the pure calculation of probabilities is not sufficient. It is attempted to explain that this can be done using the concept of design points. Some important mathematical aspects of the subset simulation method are studied in detail. In this context, it is outlined that this approach is merely a Monte Carlo (MC) style numerical approximation attempt for finding the neighborhoods of the design points, i.e., a disguised importance sampling method. New methods based on first/second-order reliability methods (FORM/SORM) improved by suitable importance sampling methods are introduced. This approach combines the simplicity of the analytic concept with the flexibility of additional MC estimates. So the structuralist view based on design points, which was given up in favor of pure probability estimates by MC, is reintroduced.
publisherASCE
titleSORM, Design Points, Subset Simulation, and Markov Chain Monte Carlo
typeJournal Paper
journal volume7
journal issue4
journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
identifier doi10.1061/AJRUA6.0001166
journal fristpage04021052-1
journal lastpage04021052-12
page12
treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2021:;Volume ( 007 ):;issue: 004
contenttypeFulltext


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