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作 者:Xinqing Li Qinghai Zhao Hongxin Zhang Tiezhu Zhang Jianliang Chen
机构地区:[1]College of Mechanical and Electrical Engineering,Qingdao University,Qingdao,266071,China [2]Power Integration and Energy Storage System Engineering Technology Center,Qingdao University,Qingdao,266071,China
出 处:《Computer Modeling in Engineering & Sciences》2021年第5期683-704,共22页工程与科学中的计算机建模(英文)
基 金:This work is supported by the Natural Science Foundation of China(Grant 51705268);China Postdoctoral Science Foundation Funded Project(Grant 2017M612191).
摘 要:This paper presents a robust topology optimization design approach for multi-material functional graded structures under periodic constraint with load uncertainties.To characterize the random-field uncertainties with a reduced set of random variables,the Karhunen-Lo`eve(K-L)expansion is adopted.The sparse grid numerical integration method is employed to transform the robust topology optimization into a weighted summation of series of deterministic topology optimization.Under dividing the design domain,the volume fraction of each preset gradient layer is extracted.Based on the ordered solid isotropic microstructure with penalization(Ordered-SIMP),a functionally graded multi-material interpolation model is formulated by individually optimizing each preset gradient layer.The periodic constraint setting of the gradient layer is achieved by redistributing the average element compliance in sub-regions.Then,the method of moving asymptotes(MMA)is introduced to iteratively update the design variables.Several numerical examples are presented to verify the validity and applicability of the proposed method.The results demonstrate that the periodic functionally graded multi-material topology can be obtained under different numbers of sub-regions,and robust design structures are more stable than that indicated by the deterministic results.
关 键 词:Multi-material topology optimization robust design periodic functional gradient sparse grid method
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