Affiliation:
1. Department of Bridge Engineering, Southwest Jiaotong University, Chengdu, PR China
Abstract
Flutter may lead to collapse of long-span bridges and need to be avoided, which makes the estimation of the onset flutter essential for long-span bridge design. However, the efficiency of traditional solution methods of predicting onset flutter is not high. In this study, it is converted into an optimization model, which is solved by a proposed advanced particle swarm optimization (APSO) with a novel inertia weight strategy and mutation mechanism. Two well-known benchmark functions are firstly employed to validate the performance of APSO. Compared with other existing PSO methods, APSO not only has high accuracy, but also has the fastest convergence speed. Then, APSO is used to find the flutter critical wind speed of bridges. A good agreement is obtained comparing predictions on the onset flutter by the proposed methods and available tests on several study cases. In addition, the value range of APSO variables is discussed in depth. It is confirmed that the proposed APSO algorithm has excellent stability, robustness and fast convergence, which is suitable for searching onset flutter of bridges.
Funder
Fundamental Research Funds for the Central Universities
National Natural Science Foundation of China
Science and Technology Plan Project of Sichuan Province of China
China Postdoctoral Science Foundation funded project
Subject
Building and Construction,Civil and Structural Engineering
Cited by
1 articles.
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