Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machine
Selecting and using an appropriate structural reliability method is critical for the success of structural reliability analysis and reliability-based design optimization. However, most of existing structural reliability methods are developed and designed for a single limit state function and few met...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2016-09-01
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| Series: | Advances in Mechanical Engineering |
| Online Access: | https://doi.org/10.1177/1687814016671447 |
| _version_ | 1828451490548678656 |
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| author | Hong-Shuang Li An-Long Zhao Kong Fah Tee |
| author_facet | Hong-Shuang Li An-Long Zhao Kong Fah Tee |
| author_sort | Hong-Shuang Li |
| collection | DOAJ |
| description | Selecting and using an appropriate structural reliability method is critical for the success of structural reliability analysis and reliability-based design optimization. However, most of existing structural reliability methods are developed and designed for a single limit state function and few methods can be used to simultaneously handle multiple limit state functions in a structural system when the failure probability of each limit state function is of interest, for example, in a reliability-based design optimization loop. This article presents a new method for structural reliability analysis with multiple limit state functions using support vector machine technique. A sole support vector machine surrogate model for all limit state functions is constructed by a multi-input multi-output support vector machine algorithm. Furthermore, this multi-input multi-output support vector machine surrogate model for all limit state functions is only trained from one data set with one calculation process, instead of constructing a series of standard support vector machine models which has one output only. Combining the multi-input multi-output support vector machine surrogate model with direct Monte Carlo simulation, the failure probability of the structural system as well as the failure probability of each limit state function corresponding to a failure mode in the structural system can be estimated. Two examples are used to demonstrate the accuracy and efficiency of the presented method. |
| first_indexed | 2024-12-10T23:37:18Z |
| format | Article |
| id | doaj.art-970dc2f5ea3747db841a910d95b157bf |
| institution | Directory Open Access Journal |
| issn | 1687-8140 |
| language | English |
| last_indexed | 2024-12-10T23:37:18Z |
| publishDate | 2016-09-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Advances in Mechanical Engineering |
| spelling | doaj.art-970dc2f5ea3747db841a910d95b157bf2022-12-22T01:29:09ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402016-09-01810.1177/1687814016671447Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machineHong-Shuang Li0An-Long Zhao1Kong Fah Tee2College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, ChinaCollege of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, ChinaDepartment of Engineering Science, University of Greenwich, London, UKSelecting and using an appropriate structural reliability method is critical for the success of structural reliability analysis and reliability-based design optimization. However, most of existing structural reliability methods are developed and designed for a single limit state function and few methods can be used to simultaneously handle multiple limit state functions in a structural system when the failure probability of each limit state function is of interest, for example, in a reliability-based design optimization loop. This article presents a new method for structural reliability analysis with multiple limit state functions using support vector machine technique. A sole support vector machine surrogate model for all limit state functions is constructed by a multi-input multi-output support vector machine algorithm. Furthermore, this multi-input multi-output support vector machine surrogate model for all limit state functions is only trained from one data set with one calculation process, instead of constructing a series of standard support vector machine models which has one output only. Combining the multi-input multi-output support vector machine surrogate model with direct Monte Carlo simulation, the failure probability of the structural system as well as the failure probability of each limit state function corresponding to a failure mode in the structural system can be estimated. Two examples are used to demonstrate the accuracy and efficiency of the presented method.https://doi.org/10.1177/1687814016671447 |
| spellingShingle | Hong-Shuang Li An-Long Zhao Kong Fah Tee Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machine Advances in Mechanical Engineering |
| title | Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machine |
| title_full | Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machine |
| title_fullStr | Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machine |
| title_full_unstemmed | Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machine |
| title_short | Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machine |
| title_sort | structural reliability analysis of multiple limit state functions using multi input multi output support vector machine |
| url | https://doi.org/10.1177/1687814016671447 |
| work_keys_str_mv | AT hongshuangli structuralreliabilityanalysisofmultiplelimitstatefunctionsusingmultiinputmultioutputsupportvectormachine AT anlongzhao structuralreliabilityanalysisofmultiplelimitstatefunctionsusingmultiinputmultioutputsupportvectormachine AT kongfahtee structuralreliabilityanalysisofmultiplelimitstatefunctionsusingmultiinputmultioutputsupportvectormachine |