Constrained Reconstruction in MUSCL-type Finite Volume Schemes
Provides a general stabilization framework for second-order finite volume schemes on non-conforming grids, though the result is incremental as it extends existing constrained reconstruction ideas.
This paper stabilizes MUSCL-type finite volume schemes on arbitrary grids using inequality-constrained linear or quadratic programming reconstructions, showing that a novel QP reconstruction on Cartesian meshes matches the Minmod method, with numerical experiments confirming accuracy and efficiency.
In this paper we are concerned with the stabilization of MUSCL-type finite volume schemes in arbitrary space dimensions. We consider a number of limited reconstruction techniques which are defined in terms inequality-constrained linear or quadratic programming problems on individual grid elements. No restrictions to the conformity of the grid or the shape of its elements are made. In the special case of Cartesian meshes a novel QP reconstruction is shown to coincide with the widely used Minmod reconstruction. The accuracy and overall efficiency of the stabilized second-order finite volume schemes is supported by numerical experiments.