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清华大学学报(自然科学版)  2016, Vol. 56 Issue (6): 572-579    DOI: 10.16511/j.cnki.qhdxxb.2016.22.014
  汽车工程 本期目录 | 过刊浏览 | 高级检索 |
基于子结构方法的离散结构协同优化
钟薇1, 苏瑞意2, 桂良进1, 范子杰1
1. 清华大学 汽车工程系, 汽车安全与节能国家重点实验室, 北京 100084;
2. 北京机电工程总体设计部, 北京 100854
Collaborative optimization of discrete structures based on a substructuring method
ZHONG Wei1, SU Ruiyi2, GUI Liangjin1, FAN Zijie1
1. State Key Laboratory of Automotive Safety and Energy, Department of Automotive Engineering, Tsinghua University, Beijing 100084, China;
2. Beijing System Design Institute of Electromechanical Engineering, Beijing 100854, China
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摘要 针对复杂离散结构优化存在设计变量多、寻优困难等问题, 提出一种基于子结构方法的分解协调策略, 并采用基于子结构分解协同优化框架求解。将大规模结构分解为多个不重叠的、规模较小的子结构, 每个子结构对应一个学科。将原优化问题的设计变量、优化目标以及约束分配至各个学科。每一轮系统迭代中, 系统层仅进行一次完整结构的有限元分析, 学科层执行子结构优化和有限元分析。耦合状态变量由系统层输入, 在学科层作为定值。系统层进行整体结构分析后更新耦合状态变量值, 以协调学科之间耦合状态变量的差异。该方法将复杂的整体结构优化问题分解为多个并行、独立的子结构优化问题。算例表明: 相比于整体结构优化, 该协同优化方法显著降低了整体结构分析次数, 能够更加稳定地找到更优解。
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钟薇
苏瑞意
桂良进
范子杰
关键词 离散结构结构优化子结构方法协同优化    
Abstract:A decomposition strategy based on substructuring is developed for optimizing complex discrete structures with a large number of design variables and a collaborative architecture is used as the solver. A large structure is decomposed into several small substructures with no overlap, where each substructure corresponds to a discipline. The variables, objectives and constraints in the original problem are assigned to the separate disciplines. Only one finite element analysis of the complete structure is performed at the system level during each iteration with optimization and finite element analyses of the substructures at the discipline levels. Coupled state variables are passed from the system level to the disciplines as constants. The coupled state variables are updated after each finite element analysis of the complete structure at the system level to coordinate the differences in the coupled state variables among disciplines. Thus, a complex structural optimization problem is decomposed into several parallel, self-governed subproblems. The results of numerical examples demonstrate that this cooperative optimization method requires less evaluations of the complete structure and is able to obtain better results with better stability than optimizing the complete structure as a whole.
Key wordsdiscrete structure    structural optimization    substructuring method    collaborative optimization
收稿日期: 2015-11-09      出版日期: 2016-07-01
ZTFLH:  TH123  
通讯作者: 范子杰, 教授, E-mail: zjfan@tsinghua.edu.cn     E-mail: zjfan@tsinghua.edu.cn
引用本文:   
钟薇, 苏瑞意, 桂良进, 范子杰. 基于子结构方法的离散结构协同优化[J]. 清华大学学报(自然科学版), 2016, 56(6): 572-579.
ZHONG Wei, SU Ruiyi, GUI Liangjin, FAN Zijie. Collaborative optimization of discrete structures based on a substructuring method. Journal of Tsinghua University(Science and Technology), 2016, 56(6): 572-579.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2016.22.014  或          http://jst.tsinghuajournals.com/CN/Y2016/V56/I6/572
  图1 标准协同优化算法的基本框图
  图2 结构分解示意图
  图3 本文的离散结构协同优化算法框图(两个子学科)
  图4 20G杆桁架结构
  表1 20G杆桁架结构求解结果
  图5 20G杆桁架结构子结构质量迭代曲线
  表2 20G杆桁架结构协同优化与整体优化结果对比
  图6 72G杆空间桁架结构
  表3 72G杆空间桁架结构的载荷工况
  表4 72G杆桁架子结构输入的结构内部边界条件
  表5 72G杆空间桁架结构求解结果
  图7 72G杆空间桁架结构子结构质量迭代曲线
  表6 72G杆空间桁架结构协同优化与整体优化结果对比
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