High-order mesh curving by distortion minimization with boundary nodes free to slide on a 3D CAD representation. (March 2016) - Ruiz-Gironés, Eloi; Roca, Xevi; Sarrate, Jose
Abstract: We propose a 3D mesh curving method that converts a straight-sided mesh to an optimal-quality curved high-order mesh that interpolates a CAD boundary representation. The main application of this method is the generation of discrete approximations of curved domains that are valid for simulation analysis with unstructured high-order methods. We devise the method as follows. First, the boundary of a straight-sided high-order mesh is curved to match the curves and surfaces of a CAD model. Second, the method minimizes the volume mesh distortion with respect to the coordinates of the inner nodes and the parametric coordinates of the curve and surface nodes. The proposed minimization features untangling capabilities and therefore, it repairs the invalid elements that may arise from the initial curving step. Compared with other mesh curving methods, the only goal of the proposed residual system is to minimize the volume mesh distortion. Furthermore, it is less constrained since the boundary nodes are free to slide on the CAD curves and surfaces. Hence, the proposed method is well suited to generate curved high-order meshes of optimal quality from CAD models that contain thin parts or high-curvature entities. To illustrate these capabilities, we generate several curved high-order meshes from CAD models with the implementation detailed in this work. Specifically, we detail a node-by-node non-linear iterative solver that minimizes the proposed objective function in a block Gauss–Seidel manner. Highlights: We present a method to generate curved high-order meshes for industrial applications. The method is based on the minimization of a single and global objective function. The objective function is defined as the distortion of the volume mesh. To enlarge the feasible region, boundary nodes are free to slide on the CAD model. A block iterative implementation of the global objective function is presented.