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Algebraic–hyperbolic grid generation with precise control of intersection of angles
Author(s) -
Brakhage KarlHeinz,
Müller Siegfried
Publication year - 2000
Publication title -
international journal for numerical methods in fluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 112
eISSN - 1097-0363
pISSN - 0271-2091
DOI - 10.1002/(sici)1097-0363(20000515)33:1<89::aid-fld4>3.0.co;2-a
Subject(s) - grid , intersection (aeronautics) , mesh generation , mathematics , context (archaeology) , parametric statistics , ordinary differential equation , algorithm , geometry , computer science , mathematical optimization , computational science , mathematical analysis , differential equation , finite element method , paleontology , statistics , physics , biology , engineering , thermodynamics , aerospace engineering
A new approach to construct high quality meshes for flow calculations is investigated in the context of algebraic grid generation, where the angle of intersection between two alternate co‐ordinate lines can be specified by the user. From an initial grid, new co‐ordinate lines in one parameter direction are determined by solving a set of ordinary differential equations (ODE). These trajectories intersect the alternate co‐ordinate lines of the initial grid in a prescribed angle. The resulting grid function is proven to be folding‐free. The advantages with respect to grid quality achieved by prescribing the angles are gained at the expense that the boundary distribution can only be prescribed on three of four boundaries. In view of a sparse representation of the grid function, the points of intersection are interpolated by a B‐spline surface. Thus, the grid can be accessed evaluating the generated parametric representation of the computational domain. Investigations of several test configurations have shown that useful grids with high resolution can be computed from the B‐spline representation only depending on a small number of locally chosen parameters . Therefore, only a small amount of computational memory is required for storing these parameters and evaluating the grid function can be efficiently performed at reduced computational costs. This is particularly promising when the mesh has to be frequently changed or updated in time. Copyright © 2000 John Wiley & Sons, Ltd.