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Estimation of Small Time-Dependent Failure Probability in High Dimensions using Subset Simulation
DC Field | Value | Language |
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dc.contributor.author | Leng, Yu | - |
dc.contributor.author | Lu, Zhao-Hui | - |
dc.contributor.author | Zhao, Yan-Gang | - |
dc.contributor.author | Li, Chun-Qing | - |
dc.date.accessioned | 2019-05-14T03:03:21Z | - |
dc.date.available | 2019-05-14T03:03:21Z | - |
dc.date.issued | 2019-05-26 | - |
dc.identifier.citation | 13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, May 26-30, 2019 | - |
dc.identifier.isbn | 979-11-967125-0-1 | - |
dc.identifier.other | ICASP13-145 | - |
dc.identifier.uri | https://hdl.handle.net/10371/153349 | - |
dc.description.abstract | Time-dependent reliability analysis of deteriorating structures is significant in their performance assessment and maintenance. Various methodologies have been used by researchers to predict the time-dependent reliability of structures. However, it is still a challenge to estimate the small time-dependent failure probability in high dimensions. In the present study, based on subset simulation an adaptive stochastic simulation procedure is proposed considering the stochastic nature of the occurrence of time-dependent random variables. Moreover, a modified Metropolis-Hastings algorithm is developed to reduce repeated trajectories and suit the property of time-dependent reliability problem. Fourth-moment transformation is utilized in the study for without the exclusion of random variables with unknown probability distributions. The proposed method is illustrated by a cantilever tube subjected to external forces and torsion. The methodology can be used as a tool for structural engineers and asset managers to assess small time-dependent failure probability of a deteriorating structure in high dimensions and make decisions with regard to its maintenance and rehabilitation. | - |
dc.description.sponsorship | The study is partially supported by the National Natural Science Foundation of China (Grant Nos.: 51820105014, 51738001), and the Fundamental Research Funds for the Central Universities of Central South University (Grant No.: 2018zzts187). The support is gratefully acknowledged. | - |
dc.language.iso | en | - |
dc.title | Estimation of Small Time-Dependent Failure Probability in High Dimensions using Subset Simulation | - |
dc.type | Conference Paper | - |
dc.identifier.doi | 10.22725/ICASP13.145 | - |
dc.sortNo | 855 | - |
dc.citation.pages | 745-752 | - |
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