Topology Optimization Design Parameter Enhanced by Univariate Dynamic Encoding Algorithm for Searches

Abstract

This paper proposes a methodology to find the hyperparameter that minimizes the compliance of the topology using a univariate dynamic encoding algorithm for searches. The difficulty in topology optimization is that there are various parameters that affects the topology of the modeling design such as the size of the elements to be designed, skip level, Poissions’ ratio, volume fraction limit, penalization power, and filter size. In most studies, these parameters were fixed and topology optimization was performed until the compliance value (cost value) converged. However, the result of the final topology optimization changes according to the change of the value of the hyperparameter in the design stage, it is necessary to study the optimization according to the change of the hyperparameters. To solve this difficulty, this paper pro- poses the methodology for hyperparameter optimization using a univariate dynamic encoding algorithm for searches. The hyperparameters were optimized using the proposed method with three topology optimization problems (both 2D and 3D cantilever beam, and 3D wheel) to show the effectiveness of the proposed methodology.