Work

Automatic hexahedral mesh generation for B-rep axisymmetric models via geometric feature recognition

Year: 2026

Type: article

Abstract: This paper presents an automatic hexahedral mesh generation method for B-rep axisymmetric models, with core innovations of distance-energy-based block structure optimization and geometric hard-edge aware low-distortion approximately isometric mapping, eliminating manual intervention and improving mesh quality. Axisymmetric models are classified into six categories via feature recognition and matched with blocking templates. Singular points are optimized using CVT distance energy, redundant soft-edge constraints are removed, and high-quality meshes are generated via 3D TFI. Algorithm contributions include the distance-energy optimization and hard-edge mapping; engineering implementation integrates the method into the CAE software SuperMesh with GUI-driven automation. Experiments show that the method generates tens of millions of elements within minutes, with minimum Jacobian ratio above 0.81, maximum aspect ratio below 4.89, and geometric error less than 0.08%, meeting high-precision simulation requirements. The approach is strictly limited to B-rep axisymmetric models without generalization guarantees for arbitrary topologies.

Source: Graphical Models

DOI: 10.1016/j.gmod.2026.101334

Authors: Yang Yang, Qingli Dong, Yi Cao, Xu Liu

Institution: Institute of Applied Physics and Computational Mathematics

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

Funder: National Natural Science Foundation of China