Layout and size optimization of suspension bridges based on coupled modelling approach and enhanced particle swarm optimization

•We couple a form-finding method with FEA for the suspension bridge optimization.•The paper presents an enhanced particle swarm optimization for suspension bridge.•The EPSO leads to significant computational savings in the optimization of bridges. This paper presents a computationally efficient opti...

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Veröffentlicht in:Engineering structures 2017-09, Vol.146, p.170-183
Hauptverfasser: Cao, Hongyou, Qian, Xudong, Chen, Zhijun, Zhu, Hongping
Format: Artikel
Sprache:eng
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Zusammenfassung:•We couple a form-finding method with FEA for the suspension bridge optimization.•The paper presents an enhanced particle swarm optimization for suspension bridge.•The EPSO leads to significant computational savings in the optimization of bridges. This paper presents a computationally efficient optimal design approach for suspension bridges. The proposed method utilizes a coupled suspension-bridge modelling approach, which integrates an analytical form-finding method with the conventional finite element (FE) model to enhance the FE modelling efficiency during the optimization process. This study also employs an enhanced particle swarm optimization (EPSO), which introduces a particle categorization mechanism to handle the constraints instead of the commonly used penalty method, to improve the computational efficiency of the optimization procedure. The numerical investigation examines the feasibility and computational efficiency of the proposed method on the optimization of a three-span suspension bridge with both size and geometric design variables. The results demonstrate that the proposed method successfully overcomes the difficulties in the FE-based suspension bridge optimization, while considering the bridge geometric parameters (the sag-to-span ratio and side-to-central span ratio) as design variables, and improves significantly the computational efficiency of PSO-based methods as used in large-scale and complex structural optimization problems.
ISSN:0141-0296
1873-7323
DOI:10.1016/j.engstruct.2017.05.048