A density-and-strain-based K-clustering approach to microstructural topology optimization
A density-and-strain-based K-clustering approach to microstructural topology optimization
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DOI：
10.1007/s00158-019-02422-4
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发表时间：
2019-11
影响因子：
3.9
通讯作者：
T. Kumar;K. Suresh
中科院分区：
文献类型：
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作者：
T. Kumar;K. Suresh
微结构拓扑优化是对宏观拓扑结构和微观结构同时进行优化。MTO承诺将产品性能提高到目前的水平。此外，随着增材制造的出现，所得到的多尺度结构可以相对容易地制造。然而，存在与MTO相关联的两个显著挑战：（1）高计算成本，以及（2）微结构连接性的潜在损失。本文提出了一种新的基于密度和应变的K均值聚类方法，以减少MTO的计算量。此外，引入旋转自由度以充分利用微结构的各向异性性质。最后，通过辅助有限元领域的连通性问题。所提出的概念说明通过几个数值例子应用到二维单载荷问题。
Microstructural topology optimization (MTO) is the simultaneous optimization of macroscale topology and microscale structure. MTO holds the promise of enhancing product-performance beyond what is possible today. Furthermore, with the advent of additive manufacturing, the resulting multiscale structures can be fabricated with relative ease. There are however two significant challenges associated with MTO: (1) high computational cost, and (2) potential loss of microstructural connectivity. In this paper, a novel density-and-strain-based K-means clustering method is proposed to reduce the computational cost of MTO. Further, a rotational degree of freedom is introduced to fully utilize the anisotropic nature of microstructures. Finally, the connectivity issue is addressed through auxiliary finite element fields. The proposed concepts are illustrated through several numerical examples applied to two-dimensional single-load problems.