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Multisection Optimization-Based Target Proof Load Determination Method for Bridge Load Testing

delete2023-06-01
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PRE
AI
X
Xu Zheng
伊廷华 cover
伊廷华 (Ting‐Hua Yi) *
D
Dong‐Hui Yang
李宏男 cover
李宏男 (Hong‐Nan Li)
DOI:10.1061/JBENF2.BEENG-6073delete
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Abstract

Abstract

En 中文
Load testing provides a useful alternative for cases in which current calculation or inspection methods cannot provide satisfactory answers to performance questions about an existing bridge. When determining the target proof load for long-span bridges during the proof load test, to ensure that all target control sections produce the same load effect with design live load, it is usually necessary to design independent load cases with different truck locations for each control section, which greatly increases the implementation cost of load testing. To solve this problem, this paper proposes a multisection optimization-based, target proof load determination method. First, the load cases are determined through control section classification, and the location of the peak of the influence surface is applied as classification criteria. Second, the load efficiency objective functions that are aimed at optimizing the truck-induced internal forces or deformation are constructed. Last, the number, positions, and formation of the load trucks for each load case are determined by a multisection joint optimization method. The effectiveness of the proposed method is shown by a target proof load determination example of a long-span arch bridge at the end of the paper. The proposed method can identify the minimum number of trucks and load cases that simultaneously meets the live load equivalent requirements of all control sections, which significantly reduces the proof load application cost of load testing.
Keywords:
Load testing
Long-span bridge
Bridge evaluation
Load trucks
Multiobjective optimization

Journal

Journal of Bridge Engineering cover
Journal of Bridge Engineering
IF:
3.5
Papers:
2.7K
Citations:
9.7K

Organization

D
dalian university of technology
Scholars:
5.0K
Papers: 1.4K
Citations: 4
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