Fuzzy-based optimised subset simulation for reliability analysis of engineering structures
Ebenuwa, Andrew Utomi and Tee, Kong Fah ORCID: https://orcid.org/0000-0003-3202-873X (2019) Fuzzy-based optimised subset simulation for reliability analysis of engineering structures. Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design and Performance, 15 (3). pp. 413-425. ISSN 1573-2479 (Print), 1744-8980 (Online) (doi:10.1080/15732479.2018.1552977)
Full text not available from this repository. (Request a copy)Abstract
This paper presents a numerical strategy for the efficient reliability assessment of engineering structures with random variables and fuzzy variables using fuzzy based optimised subset simulation (SS) approach. The proposed method relies on the performance function of the structure, which involves probability distribution functions and fuzzy variables for the modelling of the structural system. The values of the fuzzy variables for every alpha level are first obtained using the membership function. Therefore, the set values of the fuzzy variable bound the reliability of the structure, and this is evaluated using optimisation and efficient SS approach. The rationale behind the proposed strategy is to locate a failure domain or region where the objective function is minimised or maximised and compute the reliability using SS. The proposed algorithm in this study inherits the benefits of direct Monte Carlo approach in propagating the uncertainties associated with structural parameters but also demonstrate more robustness against the latter. The methodology can be applied to any engineering structures, and the applicability is demonstrated here, using a buried pipeline.
Item Type: | Article |
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Uncontrolled Keywords: | optimisation; random variable; fuzzy variable; subset simulation; pipe ovality; bending stress of buried pipe |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science Faculty of Engineering & Science > School of Engineering (ENG) |
Last Modified: | 24 Mar 2019 00:41 |
URI: | http://gala.gre.ac.uk/id/eprint/23186 |
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