Automatic recognition and decomposition of rib features in thin-shell parts for mold flow analysis

• Published in: Engineering with computers Vol. 34; no. 4; pp. 801 - 820
• Main Authors: Lai, Jiing-Yih, Wang, Ming-Hsuan, Song, Pei-Pu, Hsu, Chia-Hsiang, Tsai, Yao-Chen
• Format: Journal Article
• Language: English
• Published: London Springer London 01.10.2018; Springer Nature B.V
• Subjects: Algorithms; CAD; CAE) and Design; Calculus of Variations and Optimal Control; Optimization; Classical Mechanics; Computer aided design; Computer Science; Computer-Aided Engineering (CAD; Control; Decomposition; Face recognition; Feasibility studies; Feature recognition; Finite element method; Math. Applications in Chemistry; Mathematical and Computational Engineering; Mesh generation; Original Article; Shape recognition; Systems Theory; B-rep model; Meshing; Rib decomposition; Feature recognition; Rib recognition
• ISSN: 0177-0667; 1435-5663
• DOI: 10.1007/s00366-017-0574-2

In mold flow analysis, for greater accuracy, convergence, and application specificity, it is beneficial to apply a hybrid combination of pyramidal, prismatic, and hexahedral meshes to replace traditional tetrahedral meshes. This, however, requires the recognition of specific features from the computer-aided design (CAD) model and decomposition into regions, so that high-quality meshes can be applied. The purpose of this study is to propose a rib recognition and decomposition algorithm for detecting all the types of ribs on thin-shell plastic parts, and decomposing them into rib regions. Conventional rib recognition methods emphasizing only the recognition of the constructing faces are not suitable for high-quality mesh generation, because they cannot provide sufficient information for region decomposition. We employ a concept of parallel pairs of edges to identify regions of regular shape on a rib structure. This not only recognizes the constructing faces, but also evaluates the constructing edges on each regular region. With the edge data on regular regions, the transition regions are recognized and the associated face and edge data are evaluated. This study focuses on the development of a feasible algorithm that can be used to deal with industrial CAD models with various kinds of geometric conditions. Several CAD examples are presented to demonstrate the feasibility of the proposed algorithm.