A Decoupling Strategy for Reliability Analysis of Multidisciplinary System with Aleatory and Epistemic Uncertainties
In reliability-based multidisciplinary design optimization, both aleatory and epistemic uncertainties may exist in multidisciplinary systems simultaneously. The uncertainty propagation through coupled subsystems makes multidisciplinary reliability analysis computationally expensive. In order to impr...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/15/7008 |
| _version_ | 1797525803878055936 |
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| author | Chao Fu Jihong Liu Wenting Xu |
| author_facet | Chao Fu Jihong Liu Wenting Xu |
| author_sort | Chao Fu |
| collection | DOAJ |
| description | In reliability-based multidisciplinary design optimization, both aleatory and epistemic uncertainties may exist in multidisciplinary systems simultaneously. The uncertainty propagation through coupled subsystems makes multidisciplinary reliability analysis computationally expensive. In order to improve the efficiency of multidisciplinary reliability analysis under aleatory and epistemic uncertainties, a comprehensive reliability index that has clear geometric meaning under multisource uncertainties is proposed. Based on the comprehensive reliability index, a sequential multidisciplinary reliability analysis method is presented. The method provides a decoupling strategy based on performance measure approach (PMA), probability theory and convex model. In this strategy, the probabilistic analysis and convex analysis are decoupled from each other and performed sequentially. The probabilistic reliability analysis is implemented sequentially based on the concurrent subspace optimization (CSSO) and PMA, and the non-probabilistic reliability analysis is replaced by convex model extreme value analysis, which improves the efficiency of multidisciplinary reliability analysis with aleatory and epistemic uncertainties. A mathematical example and an engineering application are demonstrated to verify the effectiveness of the proposed method. |
| first_indexed | 2024-03-10T09:19:09Z |
| format | Article |
| id | doaj.art-bc19b5fb10ed4ed88406c8317b9a3592 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T09:19:09Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-bc19b5fb10ed4ed88406c8317b9a35922023-11-22T05:22:59ZengMDPI AGApplied Sciences2076-34172021-07-011115700810.3390/app11157008A Decoupling Strategy for Reliability Analysis of Multidisciplinary System with Aleatory and Epistemic UncertaintiesChao Fu0Jihong Liu1Wenting Xu2School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, ChinaSchool of Mechanical Engineering and Automation, Beihang University, Beijing 100191, ChinaBeijing Institute of Mechanical and Electrical Engineering, Beijing 100072, ChinaIn reliability-based multidisciplinary design optimization, both aleatory and epistemic uncertainties may exist in multidisciplinary systems simultaneously. The uncertainty propagation through coupled subsystems makes multidisciplinary reliability analysis computationally expensive. In order to improve the efficiency of multidisciplinary reliability analysis under aleatory and epistemic uncertainties, a comprehensive reliability index that has clear geometric meaning under multisource uncertainties is proposed. Based on the comprehensive reliability index, a sequential multidisciplinary reliability analysis method is presented. The method provides a decoupling strategy based on performance measure approach (PMA), probability theory and convex model. In this strategy, the probabilistic analysis and convex analysis are decoupled from each other and performed sequentially. The probabilistic reliability analysis is implemented sequentially based on the concurrent subspace optimization (CSSO) and PMA, and the non-probabilistic reliability analysis is replaced by convex model extreme value analysis, which improves the efficiency of multidisciplinary reliability analysis with aleatory and epistemic uncertainties. A mathematical example and an engineering application are demonstrated to verify the effectiveness of the proposed method.https://www.mdpi.com/2076-3417/11/15/7008mixed uncertainties quantificationmultidisciplinary analysisreliability analysisconvex set theory |
| spellingShingle | Chao Fu Jihong Liu Wenting Xu A Decoupling Strategy for Reliability Analysis of Multidisciplinary System with Aleatory and Epistemic Uncertainties Applied Sciences mixed uncertainties quantification multidisciplinary analysis reliability analysis convex set theory |
| title | A Decoupling Strategy for Reliability Analysis of Multidisciplinary System with Aleatory and Epistemic Uncertainties |
| title_full | A Decoupling Strategy for Reliability Analysis of Multidisciplinary System with Aleatory and Epistemic Uncertainties |
| title_fullStr | A Decoupling Strategy for Reliability Analysis of Multidisciplinary System with Aleatory and Epistemic Uncertainties |
| title_full_unstemmed | A Decoupling Strategy for Reliability Analysis of Multidisciplinary System with Aleatory and Epistemic Uncertainties |
| title_short | A Decoupling Strategy for Reliability Analysis of Multidisciplinary System with Aleatory and Epistemic Uncertainties |
| title_sort | decoupling strategy for reliability analysis of multidisciplinary system with aleatory and epistemic uncertainties |
| topic | mixed uncertainties quantification multidisciplinary analysis reliability analysis convex set theory |
| url | https://www.mdpi.com/2076-3417/11/15/7008 |
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