| 基于畸变比能全局化策略的应力拓扑优化 |
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| 引用本文： | 高云凯,马超,刘哲,徐亚男. 基于畸变比能全局化策略的应力拓扑优化[J]. 浙江大学学报(工学版), 2020, 54(11): 2169-2178. DOI: 10.3785/j.issn.1008-973X.2020.11.012 |
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| 作者姓名： | 高云凯 马超 刘哲 徐亚男 |
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| 作者单位： | 同济大学 汽车学院，上海 201804 |
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| 基金项目： | 国家重点研发计划资助项目（2016YFB0101602）；国家自然科学基金资助项目（51575399） |
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| 摘 要： | 针对受体积约束的应力最小化连续体结构拓扑优化，提出一种改进的双向渐进结构优化方法. 使用Kreisselmeier-Steihauser函数建立畸变比能的全局化函数，以克服应力优化计算量大的难题. 利用伴随变量法求解单元灵敏度，并引入灵敏度过滤及修正方法稳定优化过程. 双向渐进结构优化方法通过逐渐增加和删除单元，使结构进化至最优构型. 3个典型的拓扑优化算例结果表明：提出的方法可有效提升应力拓扑优化的计算效率；与柔度最小化拓扑优化相比，使用适当的凝聚函数参数消除了结构中的应力集中效应，最优设计中的最大应力值较原设计有不同程度下降，提高了结构的强度. 双向渐进结构优化方法使用离散设计变量避免了应力奇异现象，拓扑优化结果的边界清晰.
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| 关 键 词： | 拓扑优化 畸变比能 凝聚函数 双向渐进结构优化 结构设计 |
Stress-based topology optimization based on global measure of distort energy density |
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| Yun-kai GAO,Chao MA,Zhe LIU,Ya-nan XU. Stress-based topology optimization based on global measure of distort energy density[J]. Journal of Zhejiang University(Engineering Science), 2020, 54(11): 2169-2178. DOI: 10.3785/j.issn.1008-973X.2020.11.012 |
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| Authors: | Yun-kai GAO Chao MA Zhe LIU Ya-nan XU |
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| Abstract: | A modified bi-directional evolutionary structural optimization (BESO) method for stress minimization topology optimization of continuum structures was proposed. A global measure was formulated by Kreisselmeier-Steihauser aggregation function to reduce the computational cost. The sensitivity numbers were derived by the computationally efficient adjoint variable method. The optimization process was stabilized by a sensitivity filtering and correction scheme. Design variables were updated by BESO with its material addition and removal scheme that drove the initial structure gradually evolved to the optimal design. The effectiveness of the proposed method was verified by three representative numerical examples. The efficiency of the topology optimization process was significantly improved by the proposed method. Compared with the compliance minimization design, the proposed method with appropriate stress norm parameter can effectively alleviate stress concentration. The maximum stress values of the optimal designs showed various degrees of decrease, thus enhancing the strength of structures. BESO method using discrete variables avoids the stress singularity and obtains the black-and-white design. |
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| Keywords: | topology optimization distort energy density aggregation function bi-directional evolutionary structural optimization structural design |
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