科研之友
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摘要
Current methods of evaluating bridge safety are either subjective or expensive. In this study, we applied an improved response surface method based on the neural network to analyze the structural ultimate bearing capacity reliability. We defined an effective ultimate bearing capacity ratio based on the reliability index to evaluate the safety conditions of damaged structures. A quantitative analysis was achieved. Considering a concrete-filled steel tubular (CFST) arch/continuous beam bridge as an example, we calculated the reliabilities of the ultimate bearing capacity of a CFST arch and its pre-stressed concrete beam and suspenders. The results of the bridge safety evaluation based on the effective ratio of the ultimate bearing capacity coincide well with the specifications, with errors of less than 5%. This method can effectively evaluate safety conditions with respect to structural safety.
- 出版日期2016-4-25
- 单位华南理工大学
