Najwa:
I ran step-22 with Q2^d-Q1 and Q3^d-Q2, and I observed the same behavior.
Additionally, I found that in my code, even when using Q2, these jumps also
appear, though on a smaller scale and in fewer locations.
This brings me to an updated question:
* Is this behavior not significantly affecting the result, and is there any
way to improve it?
If this jump is negligible ( or if it is only a visualizing issue), does
anyone have any suggestions on where else the issue might lie? The relative
errors remain small, but we lose convergence during refinement when using Q3.
The issue with the gap is likely a visualization artifact:
https://github.com/dealii/dealii/wiki/Frequently-Asked-Questions#in-my-graphical-output-the-solution-appears-discontinuous-at-hanging-nodes
In other words, what you are seeing is probably not what internally happens.
The documentation of DataOut::build_patches() also discusses this and gives
you a suggestion of how to produce a better visual representation of the
truth. I would try that out first; it is of course also possible that you are
setting up hanging node constraints wrongly, though that's not very likely if
you ask me -- you just have to copy the 6 or 8 lines that deal with hanging
nodes from step-6 and it will work for any scheme.
What it is that affects your convergence rates is of course a different
question, but one I don't think any of us can help with knowing neither the
method nor the implementation in detail :-( Do you get the expected
convergence rate for uniform refinement? That's usually the first place to
start -- make the problem simple -- before using adaptive meshes.
Best
W.
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Wolfgang Bangerth email: bange...@colostate.edu
www: http://www.math.colostate.edu/~bangerth/
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