Adaptive tetrahedral mesh generation by constrained centroidal voronoi-delaunay tessellations for finite element methods

Jie Chen*, Yunqing Huang, Desheng Wang, Xiaoping Xie

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This article presents a tetrahedral mesh adaptivity algorithm for three-dimensional elliptic partial differential equations (PDEs) using finite element methods. The main issues involved are the mesh size and mesh quality, which have great influence on the accuracy of the numerical solution and computational cost. The first issue is addressed by a posteriori error estimator based on superconvergent gradient recovery. The second issue is solved by constrained centroidal Voronoi-Delaunay tessellations (CCVDT), which guarantees good quality tetrahedrons over a large class of mesh domains even, if the grid size varies a lot at any particular refinement level. The CCVDT enjoys the energy equidistribution property so that the errors are very well equidistributed with properly chosen sizing field (density function). And with this good property, a new refinement criteria is raised which is different from the traditional bisection refinement.

Original languageEnglish
Pages (from-to)1633-1653
Number of pages21
JournalNumerical Methods for Partial Differential Equations
Volume30
Issue number5
DOIs
Publication statusPublished - Sept 2014
Externally publishedYes

Keywords

  • a posteriori error estimates
  • adaptive finite element methods
  • centroidal Voronoi-Delaunay tessellations
  • superconvergence

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