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This repository has been archived by the owner on Jul 19, 2023. It is now read-only.
Summation By Parts is the discrete equivalent of integrating by parts. This is in many cases a very convenient property to have in a discretization operator. Technically, one needs to choose boundary locations, discretization operators, and the dot product (norm) in a consistent manner.
On a practical level, one needs to choose stencil near boundaries in a particular manner. The straightforward choice to use slightly off-centred stencils with the same order of accuracy does not work.
This paper lists and examines such operators for up to 8th order with various properties. The original idea is much older than this paper, of course.
Different from the current setup, one typically applies the difference stencil to all grid points, i.e. there are no ghost points. Boundary conditions are usually applied weakly, i.e. by modifying the RHS of the PDE that is solved. Is this setup (no ghost points) possible?
The text was updated successfully, but these errors were encountered:
The source code is distributed as part of the paper source. This link downloads a tarball that contains the LaTeX source, as well as the coefficients in the coeffs directory. I realize that there is no Fortran (or pseudo) code included that would easily tell how to use the coefficients. I will write some.
@eschnett If you are interested in SBP operators in Julia, you could look at my package SummationByPartsOperators.jl. I have coded up many coefficients there (but not yours, which I should get fixed...). This package is mostly for teaching and simple research projects, not optimized for high performance with multiple dimensions (yet).
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Summation By Parts is the discrete equivalent of integrating by parts. This is in many cases a very convenient property to have in a discretization operator. Technically, one needs to choose boundary locations, discretization operators, and the dot product (norm) in a consistent manner.
On a practical level, one needs to choose stencil near boundaries in a particular manner. The straightforward choice to use slightly off-centred stencils with the same order of accuracy does not work.
This paper lists and examines such operators for up to 8th order with various properties. The original idea is much older than this paper, of course.
Different from the current setup, one typically applies the difference stencil to all grid points, i.e. there are no ghost points. Boundary conditions are usually applied weakly, i.e. by modifying the RHS of the PDE that is solved. Is this setup (no ghost points) possible?
The text was updated successfully, but these errors were encountered: