MGM: A MESHFREE GEOMETRIC MULTILEVEL METHOD FOR SYSTEMS ARISING FROM ELLIPTIC EQUATIONS ON POINT CLOUD SURFACES

Grady B. Wright, Andrew Jones, Varun Shankar

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

We develop a new meshfree geometric multilevel (MGM) method for solving linear systems that arise from discretizing elliptic PDEs on surfaces represented by point clouds. The method uses a Poisson disk sampling-type technique for coarsening the point clouds and new meshfree restriction/interpolation operators based on polyharmonic splines for transferring information between the coarsened point clouds. These are then combined with standard smoothing and operator coarsening methods in a V-cycle iteration. MGM is applicable to discretizations of elliptic PDEs based on various localized meshfree methods, including RBF finite differences (RBF-FD) and generalized finite differences (GFD). We test MGM both as a standalone solver and preconditioner for Krylov subspace methods on several test problems using RBF-FD and GFD and numerically analyze convergence rates, efficiency, and scaling with increasing point cloud sizes. We also perform a side-by-side comparison to algebraic multigrid methods for solving the same systems. Finally, we further demonstrate the effectiveness of MGM by applying it to three challenging applications on complicated surfaces: pattern formation, surface harmonics, and geodesic distance.

Original languageEnglish
Pages (from-to)A312-A337
JournalSIAM Journal on Scientific Computing
Volume45
Issue number2
DOIs
StatePublished - 2023

Keywords

  • GFD
  • PDEs on surfaces
  • RBF-FD
  • meshfree
  • meshless
  • multilevel
  • preconditioners

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