Work

Efficient adaptive Cartesian mesh generation for complex boundary representation models

Year: 2025

Type: article

Abstract: Cartesian mesh-based fluid simulation methods are gaining popularity due to their fully automated mesh generation capabilities for geometries without repair. The performance and flexibility of Cartesian mesh generation significantly influence their application across various fields. This study introduces an efficient adaptive Cartesian mesh generation framework directly for arbitrary geometries. Initially, we propose a robust, high-quality build-in tessellation method and compute proximity. Subsequently, we design a hierarchical storage method combined with binary search for efficient intersection determination. To enhance flexibility, a fully unstructured data type and compressed data representation are established. Finally, we develop a four-step refinement mechanism to achieve geometric adaptation and smooth transitions effectively. The robustness and efficiency of the approach were validated through typical case studies, demonstrating that the mesh generation process for complex models can reach speeds of up to 1 0 5 cells per second, which presents significant potential to address the challenges of real-time simulations.

Source: Graphical Models

DOI: 10.1016/j.gmod.2025.101305

Authors: Xiang Gao, Qingyang Zhang, Chunye Gong, Chao Li, Xiaowei Guo, Jie Liu

Institution: National University of Defense Technology

Language: English

Topic: Computational Geometry and Mesh Generation

Subfield: Computer Graphics and Computer-Aided Design

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,180

Funders: National Natural Science Foundation of China, National Key Research and Development Program of China