A Unified Multigrid Solver for the Navier-Stokes Equations on Mixed Element Meshes.

Abstract

A unified multigrid solution technique is presented for solving the Euler and Reynolds averaged Navier Stokes equations on unstructured meshes using mixed elements consisting of triangles and quadrilaterals in two dimensions, and of hexahedra, pyramids, prisms and tetrahedra in three dimensions. While the use of mixed elements is by no means a novel idea, the contribution of the paper lies in the formulation of a complete solution technique which can handle structured grids, block structured grids, and unstructured grids of tetrahedra or mixed elements without any modification. This is achieved by discretizing the full Navier Stokes equations on tetrahedral elements, and the thin layer version of these equations on other types of elements, while using a single edge based data structure to construct the discretization over all element types. An agglomeration multigrid algorithm, which naturally handles meshes of any types of elements, is employed to accelerate convergence. An automatic algorithm which reduces the complexity of a given triangular or tetrahedral mesh by merging candidate triangular or tetrahedral elements into quadrilateral or prismatic elements is also described. The gains in computational efficiency afforded by the use of nonsimplicial meshes over fully tetrahedral meshes are demonstrated through several examples.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1995
Accession Number
ADA302603

Entities

People

  • D. J. Mavriplis
  • V. Venkatakrishnan

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Boundary Layer
  • Computational Fluid Dynamics
  • Convergence
  • Differential Equations
  • Efficiency
  • Equations
  • Euler Equations
  • Experimental Data
  • Fluid Dynamics
  • Fluid Flow
  • Geometry
  • Navier Stokes Equations
  • Three Dimensional
  • Triangles
  • Two Dimensional
  • Viscous Flow

Readers

  • Computational Fluid Dynamics (CFD)
  • Graph Algorithms and Convex Optimization.