Abstract: Boundary representation (BREP) and construction solid geometry (CSG) serve as the two most widely employed entity representations. There remains an urgent need for the BREP→CSG automatic conversion algorithm in such fields as particle transport calculation auxiliary modeling. However, the most commonly adopted segmentation-based BREP→CSG conversion algorithm is disadvantageous in “large amount of calculation and too complicated CSG expression”. Through the observation that “the CSG expression structure of the topologically similar BREP model is similar”, it was proposed to establish a model library containing the two tuples BREP and CSG. For the BREP model to be converted, the similar model was retrieved from the model library, and then the conversion result was generated based on the CSG expression of the similar model. On the one hand, this method can improve the conversion speed, and on the other hand, by optimizing the CSG expression, it can overcome the shortcomings of the space-based segmentation method. The extended attribute adjacency graph was applied to the description of the topological characteristics of the BREP model, the model similarity problem was regarded as the attribute adjacency graph classification problem, and then the graph convolutional network (GCN) was utilized to achieve fast model retrieval. The extended attributes of the attribute adjacency graph were also carefully designed to boost the accuracy of model retrieval. The algorithm has been integrated into the self-developed particle transport visual modeling software cosVMPT (COSINE visual modelling of particle transport), and tests were performed using the typical complex component divertor model in China Fusion Engineering Test Reactor (CFETR). The test results show the time validity of the algorithm and the superiority of the CSG results. 

Key words: BREP→CSG conversion, similarity, attribute adjacency graph, graph convolutional network, China Fusion Engineering Test Reactor