Cube-Tet transformation method accelerating the process of topology optimization

ABSTRACT

High-resolution topology optimization ensures highly accurate solutions and structural details; however, it also imposes a heavy computational burden. In this study, an efficient topology optimization method based on Cube-Tet mesh is proposed that significantly shortens the duration of finite element analysis (FEA) by compressing the size of the sparse matrix. First, the uniform cubic voxel set is obtained from the model. Each cubic voxel is transformed into six tetrahedral voxels without changing the total number of nodes; then, the FEA is performed. By transforming the mesh style, the coupling terms between nodes are decreased, the difficulty in solving the sparse matrix is reduced, and the iterative solution time is shortened, thus increasing the efficiency of topology optimization.

Keywords:

• High-resolution topology optimization
• mesh style
• efficiency
• Cube-Tet mesh

Acknowledgments

The authors gratefully acknowledge Zuqi Tang for a suggestion, as well as Mr Xinyu Wang and Zhifang Guan for their helpful work.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Key R&D Program of China under Grant [2017YFB1103000] and Grant [2019YFB1706900], National Natural Science Foundation of China under Grant [No.52005261] and Grant [No.51775281].