A second order accurate level set method on non-graded adaptive cartesian grids

Chohong Min, Frédéric Gibou

Research output: Contribution to journalArticlepeer-review

189 Scopus citations

Abstract

We present a level set method on non-graded adaptive Cartesian grids, i.e. grids for which the ratio between adjacent cells is not constrained. We use quadtree and octree data structures to represent the grid and a simple algorithm to generate a mesh with the finest resolution at the interface. In particular, we present (1) a locally third order accurate reinitialization scheme that transforms an arbitrary level set function into a signed distance function, (2) a second order accurate semi-Lagrangian methods to evolve the linear level set advection equation under an externally generated velocity field, (3) a second order accurate upwind method to evolve the non-linear level set equation under a normal velocity as well as to extrapolate scalar quantities across an interface in the normal direction, and (4) a semi-implicit scheme to evolve the interface under mean curvature. Combined, we obtain a level set method on adaptive Cartesian grids with a negligible amount of mass loss. We propose numerical examples in two and three spatial dimensions to demonstrate the accuracy of the method.

Original languageEnglish
Pages (from-to)300-321
Number of pages22
JournalJournal of Computational Physics
Volume225
Issue number1
DOIs
StatePublished - 1 Jul 2007

Bibliographical note

Funding Information:
The research of F. Gibou was supported in part by the Alfred P. Sloan Foundation through a research fellowship in Mathematics.

Keywords

  • Adaptive mesh refinement
  • Extrapolation in the normal direction
  • Ghost fluid method
  • Level set method
  • Motion by mean curvature
  • Motion in an externally generated velocity field
  • Motion in the normal direction
  • Non-graded Cartesian grids

Fingerprint

Dive into the research topics of 'A second order accurate level set method on non-graded adaptive cartesian grids'. Together they form a unique fingerprint.

Cite this