中国机械工程 ›› 2012, Vol. 23 ›› Issue (7): 860-864.

• 机械基础工程 • 上一篇    下一篇

基于混合元胞自动机的柔顺机构多目标拓扑优化方法

倪昀1;占金青2;朱大昌3   

  1. 1.金华职业技术学院,金华,321007
    2.华东交通大学,南昌,330013
    3.江西理工大学,赣州,341000
  • 出版日期:2012-04-10 发布日期:2012-04-13
  • 基金资助:
    国家自然科学基金资助项目(51165009);江西省自然科学基金资助项目(20114BAB216001) 
    National Natural Science Foundation of China(No. 51165009);
    Jiangxi Provincial Natural Science Foundation of China(No. 20114BAB216001)

Multi-objective Topological Optimum Design of Compliant Mechanisms Using Hybrid Cellular Automata Method

Ni Yun1;Zhan Jinqing2;Zhu Dachang3   

  1. 1.Jinhua College of Profession and Technology, Jinhua, Zhejiang,321007
    2.East China Jiaotong Uinveristy, Nanchang, 330013
    3.Jiangxi University of Science and Technology, Ganzhou, Jiangxi,34100
  • Online:2012-04-10 Published:2012-04-13
  • Supported by:
     
    National Natural Science Foundation of China(No. 51165009);
    Jiangxi Provincial Natural Science Foundation of China(No. 20114BAB216001)

摘要:

采用无梯度优化方法——混合元胞自动机方法进行体积约束下柔顺机构多目标拓扑优化设计。以应变能最小化和互应变能最大化为目标,以结构体积为约束,采用标准化方法定义多目标拓扑优化的目标函数,消除不同性质目标函数在数量级上的差异。将混合元胞自动机方法用于多目标优化问题的求解,以比例控制作为局部控制规律。数值算例结果表明,该方法用于柔顺机构多目标拓扑优化设计是有效的,优化迭代次数较少,且结构不易出现单节点铰链现象。

关键词: 柔顺机构, 拓扑优化, 混合元胞自动机;多目标优化

Abstract:

A multi-objective topology optimization method for compliant mechanisms was proposed using hybrid cellular automata method. The multi-objective function was developed by the minimum strain energy and maximum mutual strain energy to design the mechanism which met both stiffness and flexibility requirements, respectively. The objective function was normalized to eliminate magnitude difference of the objectives. The structure volume was used as the constraints. The hybrid cellular automata method was adopted as solving strategy for the multi-objective topology optimization problem. The local changes in the design variables were determined by local rules based on the proportional control law. A numerical example was presented to show the feasibility of the approach. The iteration number of optimization is relatively fewer, and the final topologies have less one node hinges.

Key words: compliant mechanism, topology optimization, hybrid cellular automaton method, multi-objective optimization

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