Bridge Critical State Search by Using Quantum Genetic Firefly Algorithm

Ai-Ping Tang,Dian-Zhong Liu,Shi-Bo Tao

doi:10.1155/2019/3253280

Ai-Ping Tang, Dian-Zhong Liu + Show 1 more

Open Access

https://doi.org/10.1155/2019/3253280

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Abstract

When performing flutter analysis through the traditional methods, it is difficult to solve high-order strong nonlinear equations. For overcoming this difficulty, this paper establishes a double-parameter optimization model for searching the flutter critical wind speed and frequency. A new hybrid firefly algorithm called the quantum genetic firefly algorithm is presented to search the optimal solution to the optimization model. The proposed algorithm is the combination of the firefly algorithm and the quantum genetic algorithm. The results of the quantum genetic firefly algorithm are compared with the results shown by the firefly algorithm and quantum genetic algorithm. Numerical and experimental results of the proposed algorithm are competitive and in most cases are better than that of the firefly algorithm and quantum genetic algorithm.

Highlights

In 1940, the Tacoma Narrows Bridge collapsed due to the phenomenon called flutter. e flutter is a kind of aeroelastic divergence phenomena that can induce structural failure.erefore, in the design of the long-span bridges, the critical flutter state has to be carefully investigated not to excite the flutter below the designed wind speed [1]. e semi-retrosolution method is the most common way to analyze the critical flutter state. e traditional semi-retro-solution methods are required to compare the roots of the flutter state equations repeatedly [2], as it has high complexity and large computation amount
The wind speed ranged from 4 m/s to 16 m/s. e correspondingly reduced wind speed (Ur) was U/fB, in which U, f, and B were de ned in the previous subsections. e MITD method was adopted to identify the utter derivatives [19]. e aerodynamic derivatives of the bridge are provided in Figure 5. e range of ωcr ∈ [0.6, 1.3] and Ucr ∈ [60, 120] was considered in the experiment
Of quantum genetic firefly algorithm (QGFA) are very similar with the other references in Table 7, and it shows that the results of the QGFA can be accepted

Summary

Introduction

In 1940, the Tacoma Narrows Bridge collapsed due to the phenomenon called flutter. e flutter is a kind of aeroelastic divergence phenomena that can induce structural failure.erefore, in the design of the long-span bridges, the critical flutter state has to be carefully investigated not to excite the flutter below the designed wind speed [1]. e semi-retrosolution method is the most common way to analyze the critical flutter state. e traditional semi-retro-solution methods are required to compare the roots of the flutter state equations repeatedly [2], as it has high complexity and large computation amount. E traditional semi-retro-solution methods are required to compare the roots of the flutter state equations repeatedly [2], as it has high complexity and large computation amount. Too much intervention affects the efficiency of computation and affects the accuracy and stability of the algorithm that may lead to the failure of the analysis process. Lee et al [3] calculated the onset flutter of the aeroelastic bridge system by using the quasi-steady approach and approximated formula. In these methods, it is not necessary to resolve highly nonlinear equations directly, but it needs to set the initial value of the proposed equation. When the selection of the algorithm is unsuitable, the search can get stuck in a local optimum [4]

Methods

Results

Conclusion