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Add subcell positivity limiting of non-linear variables #1738
Add subcell positivity limiting of non-linear variables #1738
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Review checklistThis checklist is meant to assist creators of PRs (to let them know what reviewers will typically look for) and reviewers (to guide them in a structured review process). Items do not need to be checked explicitly for a PR to be eligible for merging. Purpose and scope
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Created with ❤️ by the Trixi.jl community. |
Codecov ReportAttention:
Additional details and impacted files@@ Coverage Diff @@
## main #1738 +/- ##
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Coverage 96.38% 96.38%
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Files 454 455 +1
Lines 36249 36391 +142
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+ Hits 34937 35074 +137
- Misses 1312 1317 +5
Flags with carried forward coverage won't be shown. Click here to find out more. ☔ View full report in Codecov by Sentry. |
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Looks great to me!!
Just a couple minor comments here.
Thanks @amrueda 🙌 |
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Not much left to do imho, ready to party by the end of the week 👯♂️
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LGTM, thanks! There are just two names that I'd like to get @ranocha's feedback on; if he agrees, this can be merged
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LGTM, thanks!
This PR expand the support of the subcell positivity limiting to non-linear variables. This allows for instance to reduce the initial pressure from
1.0
to0.01
in the existing mhd elixirexamples/tree_2d_dgsem/elixir_mhd_shockcapturing_subcell.jl
.The limiting is done as follows (same as in Fluxo):
Now, and as for the Zalesak-type limiting before, each node is looked at separately. Then, we look at the
antidiffusive_flux
(DG flux - FV flux) for all 4 (=2*dimension
) directions separately again.So, we want to calculate the maximum amount of flux, we can add to meet our given bounds.
For this, we start with the current (from local limiting and positivity limiting for conservative variables) coefficient and increase it until the resulting solution fulfills the bounds. For this iterative approach, we use a Newton-bisection method.