trixi-framework / paper-2021-juliacon

Adaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing
MIT License
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clarify nonconservative terms #23

Closed ranocha closed 2 years ago

ranocha commented 2 years ago

@simonbyrne Thank you very much for your review. I hope this PR clarifies the aspect mentioned in your first comment

the paper states "Trixi.jl also handles non-conservative PDE terms as in the shallow water equations”. I was bit confused by this at first as Trixi uses the conservative formulation of the SWE (https://trixi-framework.github.io/Trixi.jl/stable/reference-trixi/#Trixi.ShallowWaterEquations2D) as opposed to the so-called "vector invariant" form of the SWE. This appears to be referring to a source term that involves a spatial gradient. Could this be expressed in a slightly different way?

You are right, the "nonconservative terms" refer to source terms that depend on derivatives of the solution. These terms cannot be expressed in a conservative form, i.e., as a divergence.

Xref https://github.com/trixi-framework/paper-2021-juliacon/issues/22