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Transformed Tensor Decomposition Method for Topology Optimization
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DOI：10.1002/nme.70061.png)
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Abstract
En 中文
In this paper, we propose a transformed tensor decomposition method for topology optimization. A transform is performed on the density variable to manipulate its range. The transformed variable is then decomposed as the sum of a number of modes, each in a variable-separated form. In this way, the number of design variables in discrete form and the optimization time used in each iteration are considerably reduced. Numerical tests are performed to illustrate the nice features of the proposed method with evidence for solving the problems of checkerboard and mesh-dependency.
Keywords:
reduced-order modeling
tensor decomposition
topology optimization
Journal
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2.9
Papers:
419
Citations:
2.2W