Adaptive mesh refinement and load balancing based on multi-level block-structured Cartesian mesh

Takashi Misaka, Daisuke Sasaki, Shigeru Obayashi

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


We developed a framework for a distributed-memory parallel computer that enables dynamic data management for adaptive mesh refinement and load balancing. We employed simple data structure of the building cube method (BCM) where a computational domain is divided into multi-level cubic domains and each cube has the same number of grid points inside, realising a multi-level block-structured Cartesian mesh. Solution adaptive mesh refinement, which works efficiently with the help of the dynamic load balancing, was implemented by dividing cubes based on mesh refinement criteria. The framework was investigated with the Laplace equation in terms of adaptive mesh refinement, load balancing and the parallel efficiency. It was then applied to the incompressible Navier–Stokes equations to simulate a turbulent flow around a sphere. We considered wall-adaptive cube refinement where a non-dimensional wall distance y+ near the sphere is used for a criterion of mesh refinement. The result showed the load imbalance due to y+ adaptive mesh refinement was corrected by the present approach. To utilise the BCM framework more effectively, we also tested a cube-wise algorithm switching where an explicit and implicit time integration schemes are switched depending on the local Courant-Friedrichs-Lewy (CFL) condition in each cube.

Original languageEnglish
Pages (from-to)476-487
Number of pages12
JournalInternational Journal of Computational Fluid Dynamics
Issue number10
Publication statusPublished - 2017 Nov 26


  • Adaptive mesh refinement
  • block-structured Cartesian mesh
  • large-eddy simulation
  • load balancing

ASJC Scopus subject areas

  • Computational Mechanics
  • Aerospace Engineering
  • Condensed Matter Physics
  • Energy Engineering and Power Technology
  • Mechanics of Materials
  • Mechanical Engineering


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