摘要
基于渐进结构优化算法(ESO)、双向渐进结构优化算法(BESO)及遗传算法(GA),提出了一种新的、用于结构拓扑优化设计的算法:双向进化遗传算法(BGESO)。此算法从待优化的初始结构出发,以结构单元的应变能灵敏度分析为依据,用GA算法来实现新算法的双向进化。同时,使用ANSYS中的APDL参数化编程语言实现了双向进化遗传算法的编程,并将新算法的程序模块化。针对企业现生产的汽车真空泵支架需轻量化的技术要求,对支架进行了拓扑优化设计,依据优化结果,结合支架的加工工艺提出了结构的改进方案,使其质量减少了9.5%,并对新支架结构进行了有限元分析验证,验证结果显示,优化设计后的支架在应力、变形量及模态方面都满足其使用要求。。
A bi-directional genetic evolutionary structural optimization （BGESO） algorithm, as a novel approach for realising the optimization and design of a structural topology is proposed based on an evolutionary structural optimization （ESO） algorithm, a bi-directional evolutionary structural optimization （BESO） algorithm, and a genetic algorithm （GA）. An initial structure comprising all feasible solutions is used as the research object, this algorithm realises bi-directional evolution by using a GA based on the sensitivity analysis of structural elements strain energy. Moreover, this work fulfils the programming requirement of the BGESO algorithm by using ANSYS parametric design language （APDL）, and the program of this new algorithm is modularised.Support to the lightweight technology requirements of enterprise production automotive vacuum pump bracket,atopology optimization of stent design is made for vacuum pump bracket.Based on the analysis results, a rational structure is obtained by combining with the processing craft improvement progrant,aud the new bracket reduces the quality of 9.5%. Afinite element analysis is made for the new bracket. The results show the stress, deformation and mode of the new bracketare satisfied the requirement.
出处
《机械设计与制造》
北大核心
2016年第9期255-258,共4页
Machinery Design & Manufacture
基金
贵州省科技厅省级工业攻关项目(黔科合GY字[2012]3004)
关键词
双向渐进结构优化算法
遗传算法
双向进化遗传算法
结构拓扑优化
ANSYS
APDL
BESO
Genetic Algorithm
Bi-direetioual Genetic Evolutionary Structural Optimization Algorithm
Structural Topological Optimization
ANSYS
APDL1
