{"id":36175,"date":"2016-04-01T10:47:42","date_gmt":"2016-04-01T10:47:42","guid":{"rendered":"https:\/\/silvaco.com\/%e6%9c%aa%e5%88%86%e7%b1%bb\/hints-tips-and-solutions-april-may-june-2016\/"},"modified":"2021-10-13T09:57:24","modified_gmt":"2021-10-13T16:57:24","slug":"hints-tips-and-solutions-april-may-june-2016","status":"publish","type":"post","link":"https:\/\/silvaco.com\/zh-hans\/simulation-standard-zh-hans\/hints-tips-and-solutions-april-may-june-2016\/","title":{"rendered":"Hints, Tips and Solutions – Types of 3D Delaunay Shape Refinement"},"content":{"rendered":"
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Hints, Tips and Solutions<\/h1>\n

Q: What Types of 3D Delaunay Shape Refinement can be used in Victory Process?<\/strong><\/p>\n

A. The Victory Process cell mode Delaunay 3D device meshing algorithm already includes various TCAD-based local refinement algorithms to ensure accurate and robust device simulation. These include junction and interface distance refinement. One benefit of these approaches is that complex refinement behavior can be specified via a simple deck interface, but a limitation is that the results can only vary according to the small number of parameters of the schemes. In some cases, such as particle path refinement, it can be useful to have finer, more local control over the mesh and the shape distance refinement schemes have been produced to support this.<\/p>\n

The new shape refinement algorithms plug into the existing framework for distance-based refinement based on a scalar sizing field. All of the distance-based refinement schemes share a subset of deck syntax which controls the size of the mesh elements on or inside the particular focus geometry and the distance over which the size of the elements increases to the uniform, background refinement size. The shape refinement algorithms have additional syntax which controls the parameters of the shape, such as the center of a sphere and its radius.<\/p>\n<\/div><\/section><\/div>

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