程耿东

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:男

毕业院校:丹麦技术大学

学位:博士

所在单位:力学与航空航天学院

电子邮箱:chenggd@dlut.edu.cn

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Some development of structural topology optimization

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论文类型:会议论文

发表时间:1997-01-01

收录刊物:CPCI-S

页面范围:379-394

摘要:The present paper reviews some development in the area of structural optimization with particular emphasis on one of the most challenging problems: structural topology optimization. We first revisit the previous study on the minimum compliance design problem of thin solid elastic plate with weight constraint. From its mesh dependent solutions we observed that optimization for thin isotropic plate leads to a plate with micro-structure, which is essentially a plate of macro-orthotropic materials. To obtain the optimum design we expanded the design space and regularized the problem formulation. The implication of the solution approach and numerical results is discussed in the light of the latest development in continuum topology optimization: homogenization method and artificial density method. These two approaches featured an integrated optimization of structural size, topology and material. They have opened a new way to continuum topology optimization and aroused the surging interest in application of structural optimization in industries as design tools.
   We next review the recent development of topology optimization of discrete structure. With the new achievement in this direction, it is now possible to design optimum topology of large scale trusses for minimum compliance under weight constraints. Furthermore, the recent study showed that singular optima in topology optimization with stress constraints originates from discontinuities of constraint functions and leads to jelly-fish like feasible domain. Accordingly, structural topology optimization may be catalogued into two types: these with singular optimum and those without singular optimum. An E-relaxed approach proposed recently transforms topology optimization problems of both types into structural size optimization ones by modifying the feasible domains.