Metric-Field Conditioning for Mesh Adaptation Problems

نویسندگان

  • Ved Vyas
  • Kenji Shimada
چکیده

Metric tensor fields computed from solution data for adaptation problems are not always well-behaved. They may contain noise, high gradients in desired directionality and anisotropy, global undulations in directionality, and other defects that pose challenges for meshing algorithms. We focus on the application of filters to address some of these defects through noise removal and a form of fairing. At the same time, it is desirable to retain characteristics of the original metric data. These methods are demonstrated on metric data from a high-speed, 2D flow problem.

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تاریخ انتشار 2012