论文标题
各向同性非结构化网格生成的功能感知的SPH
A Feature-aware SPH for Isotropic Unstructured Mesh Generation
论文作者
论文摘要
在本文中,我们提出了一种特征感知的SPH方法,用于并发和自动的各向同性非结构化网格生成。与原始的基于SPH的网格发生器相比,提出的方法还实现了两个其他目标(Fu等,2019)。首先,引入了特征边界校正项,以解决边界附近不完整的内核支持问题。可以同时处理特征曲线,特征表面和体积的网格生成,而无需明确的遵循尺寸序列。其次,提出了一个两相模型来通过特征大小适应阶段和网格质量优化阶段来表征网格生成程序。通过提出一个具有两组仿真参数的新错误测量标准和自适应控制系统,将更快的特征大小自适应和本地网格质量改进的目标合并为一致的框架。所提出的方法通过一组具有不同复杂性和尺度的2D和3D数值测试验证。结果表明,高质量的网格是通过显着的收敛加速产生的。
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.