Direct modifications of tetrahedral meshes

Abstract

Purpose During the industrial design process, a product is usually modified and analyzed repeatedly until reaching the final design. Modifying the model and regenerating a mesh for every update during this process is very time consuming. To improve efficiency, it is necessary to circumvent the computer-aided design modeling stage when possible and directly modify the meshes to save valuable time. The purpose of this paper is to develop a method for mesh modifications. Design/methodology/approach In contrast to existing studies, which focus on one or a class of modifications, this paper comprehensively studies mesh union, mesh gluing, mesh cutting and mesh partitioning. To improve the efficiency of the method, the paper presents a fast and effective surface mesh remeshing algorithm based on a ball-packing method and controls the remeshing regions with a size field. Findings Examples and results show that the proposed mesh modification method is efficient and effective. The proposed method can be also applied to meshes with different material properties, which is very different with previous work that is only suitable for the meshes with same material property. Originality/value This paper proposes an efficient and comprehensive tetrahedral mesh modification method, through which engineers can directly modify meshes instead of models and save time.

An Enhanced Steepest Descent Method for Global Optimization-Based Mesh Smoothing

“…The quality value of an element with different configurations can vary significantly according to the metric. Various formulas have been used to compute the aspect ratio quality metric [3] [28]. We use a simple one implemented in Mesquite.…”

“…Mesh with high quality can reduce the time to solution, and increase the solution accuracy [1] [2]. Therefore, mesh quality improvement methods are often used in the mesh generation [3] [4]. There are three types of mesh improvement methods: node insertion/deletion optimization [5] [6] [7], topological optimization [8] [9] [10] [11] and geometrical optimization [12]- [23].…”