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Reliability Assessment of Long-Span Cable-Stayed Bridges Based on Hybrid Algorithm
| Content Provider | Semantic Scholar |
|---|---|
| Author | Liu, Yang Wang, Qinyong Lu, Naiwei |
| Copyright Year | 2016 |
| Abstract | In order to evaluate the reliability of long-span cable-stayed bridges, a computational framework utilizing a hybrid algorithm is developed. The framework integrates the advantages of finite element analysis, radial basis function neural networks, genetic algorithms, and Monte-Carlo importance sampling method (MCIS) together. These approaches are combined intelligently with consideration of a platform. The feasibility of this framework is verified through a case study, where a prestressed concrete cable-stayed bridge is presented. The parametric study indicates that: a) the failure probability caused by displacement limit of mid-span is greater than that caused by the cable strength failure. b) the mean value and standard deviation of vehicle loads have a higher influence on reliability of the cable-stayed bridge. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://rec2016.sd.rub.de/papers/REC2016-FP-36_Y.%20Liu,%20Q.%20Wang%20and%20N.%20Lu__Reliability%20Assessment%20of%20Long-Span%20Cable-Stayed%20Bridges%20Based%20on%20Hybrid%20Algorithm.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
