1995
DOI: 10.2514/3.12701
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Unstructured grid generation using iterative point insertion and local reconnection

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Cited by 284 publications
(109 citation statements)
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“…This problem also has an explicitly defined radially symmetric similarity solution in d dimensions in the special case n = 1, given by in which 93) and U 0 = 1/192 is chosen so that u(0,t 0 ) = 1, where t 0 is such that the initial position of the moving front is at r = 1. Fig.…”
Section: Fourth Order Nonlinear Diffusionmentioning
confidence: 99%
See 1 more Smart Citation
“…This problem also has an explicitly defined radially symmetric similarity solution in d dimensions in the special case n = 1, given by in which 93) and U 0 = 1/192 is chosen so that u(0,t 0 ) = 1, where t 0 is such that the initial position of the moving front is at r = 1. Fig.…”
Section: Fourth Order Nonlinear Diffusionmentioning
confidence: 99%
“…This has the effect of lowering the order of convergence when n is increased beyond 1. The convergence results have been obtained using a series of unstructured meshes generated on a circle of radius 0.5 by an advancing front method [93] in which the mesh size parameter has been repeatedly halved. In fact, every two-dimensional experiment presented in this paper has been carried out on unstructured meshes of this type.…”
Section: The Porous Medium Equationmentioning
confidence: 99%
“…The grids for the simulations were generated using the SimCenter software developed at Mississippi State University Marcum and Weatherill [1995]. Since the geometry is essentially two-dimensional, a planar grid was generated first and then this grid was extruded in the spanwise direction.…”
Section: Grid Generationmentioning
confidence: 99%
“…Two approaches can be followed to obtain an updated Delaunay triangulation T new after the insertion of a new point P into an existing Delaunay triangulation T old [22,[25][26][27]. The approach adopted in the present work uses local splitting together with repeated edge swapping until all the edges, except constrained edges, satisfy the Delaunay property [25,26].…”
Section: Constrained Delaunay Constructionmentioning
confidence: 99%
“…Oliva et al [3], constructed the Voronoi diagram and then subdivided each cell into triangles. However, as the well-developed Delaunay triangulation [22][23][24][25][26] provides the optimality of nearest connection, and this in turn favours vertical connection in the reconstruction, the problems of tiling and correspondence are naturally solved.…”
Section: Surface Recovery Based On Parametric Domain Triangulationmentioning
confidence: 99%