A parallel adaptive numerical method with generalized curvilinear coordinate transformation for compressible Navier–Stokes equations
Journal Article
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· International Journal for Numerical Methods in Fluids
- Colorado State Univ., Fort Collins, CO (United States); DOE/OSTI
- Colorado State Univ., Fort Collins, CO (United States)
A fourth-order finite-volume method for solving the Navier–Stokes equations on a mapped grid with adaptive mesh refinement is proposed, implemented, and demonstrated for the prediction of unsteady compressible viscous flows. The method employs fourth-order quadrature rules for evaluating face-averaged fluxes. Our approach is freestream preserving, guaranteed by the way of computing the averages of the metric terms on the faces of cells. The standard Runge–Kutta marching method is used for time discretization. Solutions of a smooth flow are obtained in order to verify that the method is formally fourth-order accurate when applying the nonlinear viscous operators on mapped grids. Solutions of a shock tube problem are obtained to demonstrate the effectiveness of adaptive mesh refinement in resolving discontinuities. A Mach reflection problem is solved to demonstrate the mapped algorithm on a non-rectangular physical domain. The simulation is compared against experimental results. Future work will consider mapped multiblock grids for practical engineering geometries.
- Research Organization:
- Colorado State Univ., Fort Collins, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- Grant/Contract Number:
- EE0006086
- OSTI ID:
- 1533176
- Journal Information:
- International Journal for Numerical Methods in Fluids, Journal Name: International Journal for Numerical Methods in Fluids Journal Issue: 10 Vol. 82; ISSN 0271-2091
- Publisher:
- WileyCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Correction: A Fourth-Order Finite-Volume Method with Adaptive Mesh Refinement for the Multifluid Plasma Model
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conference | January 2018 |
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