基于粒子群敏度更新的拓扑优化方法  

Topology optimization based on particle swarm sensitivity updating

作　　者：周哲浩 徐曼曼 蒋国璋[1,2] ZHOU Zhehao;XU Manman;JIANG Guozhang(College of Machinery and Automation,Wuhan University of Science and Technology,Wuhan 430081,China;Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering,Wuhan University of Science and Technology,Wuhan 430081,China)

机构地区：[1]武汉科技大学机械自动化学院,湖北武汉430081 [2]武汉科技大学机械传动与制造工程湖北省重点实验室,湖北武汉430081

出　　处：《武汉科技大学学报》2024年第3期227-233,共7页Journal of Wuhan University of Science and Technology

基　　金：湖北省自然科学基金项目(2022CFB998);湖北省教育厅科研计划项目(Q20211103).

摘　　要：为了进一步减少拓扑优化过程中出现的灰度单元,提出一种基于粒子群优化和分区加权敏度过滤的敏度更新方法。引入粒子群状态更新表达式,以寻找周围单元的敏度极值,将其在一定权重下与经过过滤的敏度值相加,组成新的敏度更新策略。结合变密度法和基于粒子群的敏度更新策略,以柔度最小化为目标,利用5个经典算例验证本文方法的可行性和有效性。优化结果表明,基于粒子群敏度更新的拓扑优化方法能有效减少灰度单元并能快速收敛。To further reduce gray units in the topology optimization,a sensitivity updating method using particle swarm optimization and partition-weighted sensitivity filtering was proposed.The status updating expression for the particle swarm was introduced to find the sensitivity extremum of the surrounding units,and the value was added to the filtered sensitivity under a certain weight to form a new sensitivity updating strategy.By combining the variable density method with the particle swarm based sensitivity updating strategy,and aimed at compliance minimization,five classical test cases were used to verify the feasibility and effectiveness of the proposed method.The results show that the topology optimization method based on particle swarm sensitivity updating can effectively reduce gray units and converge rapidly.

关 键 词：拓扑优化 变密度法 敏度更新 敏度过滤 粒子群 

分 类 号：TH122[机械工程—机械设计及理论] O343.1[理学—固体力学]