Reliability Evaluation of Bridge Fatigue Life through Refined Statistical Analysis of Stochastic Traffic Flow Monitoring Data
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Bibliographic Details
Author(s): |
Donghui Yang
(Dalian University of Technology, Dalian, China)
Zexin Guan (Dalian University of Technology, Dalian, China) |
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Medium: | conference paper | ||||
Language(s): | English | ||||
Conference: | IABSE Congress: Bridges and Structures: Connection, Integration and Harmonisation, Nanjing, People's Republic of China, 21-23 September 2022 | ||||
Published in: | IABSE Congress Nanjing 2022 | ||||
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Page(s): | 1489-1496 | ||||
Total no. of pages: | 8 | ||||
DOI: | 10.2749/nanjing.2022.1489 | ||||
Abstract: |
To evaluate the reliability of the fatigue performance of key bridge components under stochastic vehicle loads, a prediction and evaluation method for the fatigue life of bridges based on elaborate statistical analysis of traffic flow and strain influence line identification is established in this paper. Firstly, The two-step clustering (TSC) method is applied to distinguish the different traffic states with the clustering numbers to be determined objectively. The elaborate stochastic traffic flow is simulated by random sampling of vehicle feature probabilistic models for each traffic state. Secondly, the actual bridge strain influence line inverted based on the fatigue detail measured strain data is used to be loaded by the stochastic traffic flow, and the stress time history under the stochastic traffic flow is calculated. The Monte Carlo method is applied to predict fatigue life. Finally, a real bridge is taken as an example to verify the effectiveness of the proposed method. |
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Keywords: |
fatigue reliability Cluster analysis vehicle load monitoring stochastic vehicle flow influence line identification
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Copyright: | © 2022 International Association for Bridge and Structural Engineering (IABSE) | ||||
License: | This creative work is copyrighted material and may not be used without explicit approval by the author and/or copyright owner. |