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Title: A Parallel Reconstructed Discontinuous Galerkin Method for the Compressible Flows on Aritrary Grids

Conference ·
OSTI ID:978354

A reconstruction-based discontinuous Galerkin method is presented for the solution of the compressible Navier-Stokes equations on arbitrary grids. In this method, an in-cell reconstruction is used to obtain a higher-order polynomial representation of the underlying discontinuous Galerkin polynomial solution and an inter-cell reconstruction is used to obtain a continuous polynomial solution on the union of two neighboring, interface-sharing cells. The in-cell reconstruction is designed to enhance the accuracy of the discontinuous Galerkin method by increasing the order of the underlying polynomial solution. The inter-cell reconstruction is devised to remove an interface discontinuity of the solution and its derivatives and thus to provide a simple, accurate, consistent, and robust approximation to the viscous and heat fluxes in the Navier-Stokes equations. A parallel strategy is also devised for the resulting reconstruction discontinuous Galerkin method, which is based on domain partitioning and Single Program Multiple Data (SPMD) parallel programming model. The RDG method is used to compute a variety of compressible flow problems on arbitrary meshes to demonstrate its accuracy, efficiency, robustness, and versatility. The numerical results demonstrate that this RDG method is third-order accurate at a cost slightly higher than its underlying second-order DG method, at the same time providing a better performance than the third order DG method, in terms of both computing costs and storage requirements.

Research Organization:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
DE-AC07-05ID14517
OSTI ID:
978354
Report Number(s):
INL/CON-10-17571; TRN: US201010%%56
Resource Relation:
Conference: 48th AIAA Aerospace Sciences Meeting and Exhibit,Orlando, Florida,01/04/2010,01/07/2010
Country of Publication:
United States
Language:
English