基于遗传算法的张弦桁架设计与选形优化

引用文献:

孙彦平 孙玉萍. 基于遗传算法的张弦桁架设计与选形优化[J]. 建筑结构,2022,48(01):56-62.

SUN Yanping SUN Yuping. Design and shape selection optimization of truss string structures based on genetic algorithm[J]. Building Structure,2022,48(01):56-62.

作者:孙彦平 孙玉萍
单位:兰州理工大学土木工程学院
摘要:张弦桁架设计参数较多且相互影响,常伴有较大的几何非线性变形,因此需要精确寻找结构形状及预拉力,以获得结构整体性能的优化结果。在MATLAB平台上利用多种群遗传算法,通过命令流调用SAP2000,在对结构优化的同时,实现“找形”及“找力”;第一阶段寻找各类构件的截面,发现桁架弦杆截面的改变对整体优化结果影响较小,在此基础上进行第二阶段结构整体优化。通过对10组模型优化,发现最优矢高、垂度、桁架上弦截面高度、初始预拉力与跨度呈显著线性上升变化,腹杆间距基本保持不变,而撑杆数目则在6~13范围内变化;通过分析得到各最优设计参数与跨度的方程,发现变化范围越大的参数线性程度越高,说明该方法可用于一般张弦桁架的优化。
关键词:张弦桁架;多种群遗传算法;选形优化
作者简介:孙彦平,硕士研究生,主要从事预应力钢结构研究,Email:syp4055@163.com。
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Design and shape selection optimization of truss string structures based on genetic algorithm
SUN Yanping SUN Yuping
(School of Civil Engineering,Lanzhou University of Technology)
Abstract: The design parameters of the truss string structure are many and influence each other, often accompanied by large geometric nonlinear deformation, so it is necessary to accurately find the structure shape and pretension to obtain the optimization results of the overall performance of the structure. On the MATLAB platform, the multi population genetic algorithm called SAP2000 was used through the command flow, while optimizing the structure, achieved "shape finding" and "force finding". In the first stage, the section of various components was searched, and it was found that the change of components section of truss chord has little influence on the overall optimization results. On this basis, the second stage was optimized of overall structure. Through the optimization of 10 groups of models, it was found that the optimal rise, sag, height of upper truss chord section of truss, initial pretension and span show obvious linear upward change; the distance between web members is basically constant and the number of strut varies from 6 to 13. The equations of the optimal design parameters and span were obtained by analysis. It was found that the larger the variation range, the higher the linearity of the parameters, which shows that the method can be used for the optimization of general truss string structure.
Keywords: truss string; multi population genetic algorithm; shape selection optimization
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