Self-consistent Clustering Analysis-Based Moving Morphable Component(SMMC)Method for Multiscale Topology Optimization
作者机构：Department of Mechanical EngineeringNorthwestern UniversityEvanstonIL 60208USA Theoretical and Applied Mechanics ProgramNorthwestern UniversityEvanstonIL 60208USA Department of Engineering MechanicsTsinghua UniversityBeijing 100084China
出 版 物：《Acta Mechanica Solida Sinica》 (固体力学学报（英文版）)
年 卷 期：2023年第36卷第6期
页 面：884-898页
核心收录：
学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学]
基 金：Northwestern University NU
主 题：Topology optimization Moving morphable component method Multiscale concurrent design Reduced-order model
摘 要：Current multiscale topology optimization restricts the solution space by enforcing the use of a few repetitive microstructures that are predetermined,and thus lack the ability for structural concerns like buckling strength,robustness,and ***,in this paper,a new multiscale concurrent topology optimization design,referred to as the self-consistent analysis-based moving morphable component(SMMC)method,is *** with the conventional moving morphable component method,the proposed method seeks to optimize both material and structure simultaneously by explicitly designing both macrostructure and representative volume element(RVE)-level *** examples with transducer design requirements are provided to demonstrate the superiority of the SMMC method in comparison to traditional *** proposed method has broad impact in areas of integrated industrial manufacturing design:to solve for the optimized macro and microstructures under the objective function and constraints,to calculate the structural response efficiently using a reduced-order model:self-consistent analysis,and to link the SMMC method to manufacturing(industrial manufacturing or additive manufacturing)based on the design requirements and application areas.
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