4.7 Article

A Cartesian-based embedded geometry technique with adaptive high-order finite differences for compressible flow around complex geometries

Journal

JOURNAL OF COMPUTATIONAL PHYSICS
Volume 262, Issue -, Pages 379-407

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcp.2014.01.004

Keywords

Immersed interface; Immersed boundary; Embedded geometry; Compressible Navier Stokes; High order finite differences

Funding

  1. DOE/PECASE [LLNL B574743]
  2. NASA NRA award [NNX08AL31A, NNX12AJ65A]
  3. NASA [NNX08AL31A, 43408, NNX12AJ65A, 99653] Funding Source: Federal RePORTER

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An immersed boundary methodology to solve the compressible Navier-Stokes equations around complex geometries in Cartesian fluid dynamics solvers is described. The objective of the new approach is to enable smooth reconstruction of pressure and viscous stresses around the embedded objects without spurious numerical artifacts. A standard level set represents the boundary of the object and defines a fictitious domain into which the flow fields are smoothly extended. Boundary conditions on the surface are enforced by an approach inspired by analytic continuation. Each fluid field is extended independently, constrained only by the boundary condition associated with that field. Unlike most existing methods, no jump conditions or explicit derivation of them from the boundary conditions are required in this approach. Numerical stiffness that arises when the fluid-solid interface is close to grid points of the mesh is addressed by preconditioning. In addition, the embedded geometry technique is coupled with a stable high-order adaptive discretization that is enabled around the object boundary to enhance resolution. The stencils used to transition the order of accuracy of the discretization are derived using the summationby-parts technique that ensures stability. Applications to shock reflections, shock-ramp interactions, and supersonic and low-Mach number flows over two- and three-dimensional geometries are presented. (C) 2014 Elsevier Inc. All rights reserved.

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