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I have not yet tried to run it, but here are some first, easy-to-address comments.
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| - Added PCE-base surrogate for micro-dumux in two-scale heat conduction [#684](https://github.com/precice/tutorials/pull/684) | |||
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The README.md file of the tutorial also needs to document this alternative and what kind of surrogate it is.
In other cases (e.g., perpendicular-flap), we had participants named -fake? Is this case doing something similar?
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| python3 -m venv .venv | ||
| . .venv/bin/activate | ||
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| pip install -r requirements.txt |
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See #680 for some updates (or directly copy from other run.sh in the same tutorial).
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Thanks for the comments. I am still thinking about how to structure the folders so that only the full-order model and the surrogate model are exposed to the user. By adding a surrogate model at the micro scale, we have a unique scenario in which the Micro Manager runs not one but two solvers simultaneously. Technically, the solvers are not participants of the coupling; the Micro Manager is. But having the solvers in individual folders makes sense because it highlights which physics is being used and which software is being run. |
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Makes sense to me. The only real alternative would be a subfolder micro or micro-manager and in there multiple folders with the different models. |
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Since there is now activity on this PR, notice some recent changes in the rest of the tutorials, regarding:
You could also directly try to update the tests.yaml to add a test case.
Don't forget to update the tutorial README.md file to add the cases to the overview.
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| numpy | |||
| bayesvalidrox | |||
| micro-manager-precice | |||
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Recent update: Please also add pyprecice here, even if implied by the micro-manager-precice.
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Recent: This will need some updates regarding the venv setup. See how the other tutorials now (consistently) handle that.
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… in micro-dumux-surrogate
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This PR adds a surrogate variant to the existing participant micro-dumux, called the micro-dumux-surrogate. The surrogate is created using the tool BayesValidRox. The surrogate is built using PCE (Polynomial Chaos Expansion). This participant is built to highlight the functionality of model adaptivity in the Micro Manager: precice/micro-manager#198
Checklist: