Study on mesh segmentation of topology optimization results using Reeb graph

Mesh segmentation is a powerful tool for the management of digital models. Reeb graph based segmentation is robust to the variations of model pose and insensitive to the highly noised model. Thus, in this paper, an improved Reeb graph based mesh segmentation for the topology optimization result is proposed. Generally, the topology optimization result is short of prominent components. Therefore, previous mesh segmentation methods are difficult used for the mesh segmentation of the topology optimization result. By combining methods proposed in literature, a new mapping function is proposed. Firstly, feature points are extracted from the original mesh. Then, the mapping function is defined as the summation of geodesic distances of a generic vertex to all of the feature points. Subsequently, vertices are classified into different patches based on their mapping function values. The aforementioned steps are repeated with each patch considered as the new model until a desirable solution is obtained. To demonstrate the proposed method, two numerical examples are solved by the proposed method and methods presented in literature. The results demonstrate that, for the topology optimization results, the proposed method could generate a better solution which can facilitates the further post-processing of the topology optimization results.