A Three-Dimensional Adaptive Tie-dye Mesh Automatic Generation Algorithm For Auto-CFD

• Published in: IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC ...) (Online) Vol. 6; pp. 1636 - 1640
• Main Authors: Junjie, Gao, Jianqi, Ma, Xinyuan, Cao, Jun, Liu, Jie, Chen
• Format: Conference Proceeding
• Language: English
• Published: IEEE 24.05.2024
• Subjects: Accuracy; Adaptation models; Auto-CFD; automatic topological connection; Classification algorithms; Memory management; mesh generation; Parallel processing; Solid modeling; Spatiotemporal phenomena; tie-dye algorithm
• ISSN: 2693-2776
• DOI: 10.1109/IMCEC59810.2024.10575034

Auto-CFD, characterized by automated mesh generation, is becoming a new research hotspot due to its numerous advantages. The tie-dye algorithm, with its uniqueness, is particularly suitable for Auto-CFD. As the principle verification and parallelism analysis in two-dimensional space have been completed, there is an urgent need to extend the research to more complex three-dimensional spaces. Addressing the low spatiotemporal efficiency of the algorithm caused by basic tie-dye meshes, a Three-dimensional Adaptive Tie-dye Mesh Auto-generation (TATMA) algorithm is proposed in this paper. After inputting CAD models, an adaptive Cartesian background grid is automatically generated using ADT trees, ray intersection methods, and coloring algorithms. Subsequently, the nodes with missing topological relationships are classified based on unstructured finite difference methods. Then, the missing topological relationships are completed automatically, allowing the automatic generation of unstructured grids. The results of numerical experiments validate the effectiveness of TATMA. It is shown that TATMA, compared with the basic tie-dye algorithm, has a smaller memory space ratio and an improvement of over 40% in spatiotemporal efficiency, on the premise of similar accuracy in solving the flow field.