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

机译:基于耦合建模方法和改进粒子群算法的悬索桥布局和尺寸优化

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摘要

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. (C) 2017 Elsevier Ltd. All rights reserved.
机译:本文提出了一种计算有效的悬索桥优化设计方法。所提出的方法利用了耦合悬索桥建模方法,该方法将解析形式查找方法与常规有限元(​​FE)模型相集成,以在优化过程中提高FE建模效率。这项研究还采用了增强的粒子群优化(EPSO),它引入了一种粒子分类机制来处理约束,而不是通常使用的惩罚方法,以提高优化过程的计算效率。数值研究验证了所提方法对具有大小和几何设计变量的三跨悬索桥优化的可行性和计算效率。结果表明,该方法成功克服了基于有限元的悬索桥优化中的困难,同时将桥梁的几何参数(下垂跨度比和侧向中心跨度比)作为设计变量,并显着改善了大型复杂结构优化问题中使用的基于PSO的方法的计算效率。 (C)2017 Elsevier Ltd.保留所有权利。

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