Dyedov Volodymyr, Einstein Daniel, Jiao Xiangmin, Kuprat Andrew, Carson James, Pin Facundo Del
Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY. Email:
Int J Numer Methods Eng. 2009 Aug 20;79(8):907-945. doi: 10.1002/nme.2583.
Boundary-layer meshes are important for numerical simulations in computational fluid dynamics, including computational biofluid dynamics of air flow in lungs and blood flow in hearts. Generating boundary-layer meshes is challenging for complex biological geometries. In this paper, we propose a novel technique for generating prismatic boundary-layer meshes for such complex geometries. Our method computes a feature size of the geometry, adapts the surface mesh based on the feature size, and then generates the prismatic layers by propagating the triangulated surface using the face-offsetting method. We derive a new variational method to optimize the prismatic layers to improve the triangle shapes and edge orthogonality of the prismatic elements and also introduce simple and effective measures to guarantee the validity of the mesh. Coupled with a high-quality tetrahedral mesh generator for the interior of the domain, our method generates high-quality hybrid meshes for accurate and efficient numerical simulations. We present comparative study to demonstrate the robustness and quality of our method for complex biomedical geometries.
边界层网格对于计算流体动力学中的数值模拟非常重要,包括肺部气流和心脏血流的计算生物流体动力学。对于复杂的生物几何形状,生成边界层网格具有挑战性。在本文中,我们提出了一种为这种复杂几何形状生成棱柱形边界层网格的新技术。我们的方法计算几何形状的特征尺寸,基于特征尺寸调整表面网格,然后通过使用面偏移方法传播三角化表面来生成棱柱层。我们推导了一种新的变分方法来优化棱柱层,以改善棱柱单元的三角形形状和边正交性,并引入简单有效的措施来保证网格的有效性。结合用于域内部的高质量四面体网格生成器,我们的方法生成高质量的混合网格,以进行准确高效的数值模拟。我们进行了比较研究,以证明我们的方法对于复杂生物医学几何形状的稳健性和质量。