4.4 Article

Explicit Topology Optimization with Moving Morphable Component (MMC) Introduction Mechanism

期刊

ACTA MECHANICA SOLIDA SINICA
卷 35, 期 3, 页码 384-408

出版社

SPRINGER
DOI: 10.1007/s10338-021-00308-x

关键词

Topology optimization; Moving morphable component (MMC); Component introduction mechanism

资金

  1. Foundation for Innovative Research Groups of the National Natural Science Foundation of China [11821202]
  2. National Natural Science Foundation of China [11872138, 11702048, 11732004, 11772076, 12002073]
  3. 111 Project [B14013]
  4. Young Elite Scientists Sponsorship Program by CAST [2018QNRC001]
  5. Fundamental Research Funds for the Central Universities, China [DUT20RC(3)020, DUT21RC(3)076]
  6. Dalian Talent Innovation Program [2020RQ099]

向作者/读者索取更多资源

In this article, an explicit topology optimization approach with components-growing ability is proposed under the MMC framework. The approach optimizes the shape and topology layout of structures by the growth evolution of moving morphable components. It eliminates the initial design dependency by allowing the addition of new components or modification of the current layout.
In this article, an explicit topology optimization approach with components-growing ability is proposed under the moving morphable component (MMC) framework. In this approach, the shape and topology layout of structures are explicitly optimized by growth evolution of moving morphable components. To this end, a competition criterion is developed to optimize the structural layout from two options: adding several new components or changing the current layout. In addition, some numerical technqiues are also developed to preserve the stability of the iterative process. The present topology optimization approach allows rational generation of new components and does not require a specific distribution of components in the initial design, which is compulsory for the conventional MMC method. Three numerical examples are provided to illustrate the effectiveness of the proposed method. The optimization results indicate that the proposed method does have the potential to improve the existing MMC-based explicit topology optimization framework by eliminating the initial design dependency of optimal solutions.

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