一种基于属性感知的SPH各向同性非结构网格生成算法
A Feature-aware SPH for Isotropic Unstructured Mesh Generation
摘要：
本文提出了一种基于特征的SPH方法，用于各向同性非结构网格的并行自动生成。与原始的基于SPH的网格生成器（Fu等人，2019年）。首先，引入特征边界修正项，解决边界附近核支持度不完全的问题。特征曲线、特征曲面和体积的网格生成可以同时处理，而无需明确遵循尺寸序列。其次，提出了一个两阶段模型来描述网格生成过程的特征尺寸适应阶段和网格质量优化阶段。通过提出一种新的误差测量标准和一个具有两组仿真参数的自适应控制系统，将更快的特征尺寸自适应和局部网格质量改善的目标合并到一个一致的框架中。一组不同复杂度和规模的二维和三维数值试验验证了所提出的方法。结果表明，高质量的网格生成具有显着的加速收敛。
英文摘要：
In this paper, we present a feature-aware SPH method for the concurrent and automated isotropic unstructured mesh generation. Two additional objectives are achieved with the proposed method compared to the original SPH-based mesh generator (Fu et al., 2019). First, a feature boundary correction term is introduced to address the issue of incomplete kernel support at the boundary vicinity. The mesh generation of feature curves, feature surfaces and volumes can be handled concurrently without explicitly following a dimensional sequence. Second, a two-phase model is proposed to characterize the mesh-generation procedure by a feature-size-adaptation phase and a mesh-quality-optimization phase. By proposing a new error measurement criterion and an adaptive control system with two sets of simulation parameters, the objectives of faster feature-size adaptation and local mesh-quality improvement are merged into a consistent framework. The proposed method is validated with a set of 2D and 3D numerical tests with different complexities and scales. The results demonstrate that high-quality meshes are generated with a significant speedup of convergence.
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