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Monotonic Convergence Rebound

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Old   October 30, 2012, 13:01
Default Monotonic Convergence Rebound
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I have noticed this twice in different simulations. I get beautiful convergence and imbalance progress; so much so I can go 1000 times the starting time scale. As soon as it gets to a certain point (in this case RMS residuals < 5e-4 and imbalances <0.5%) I get a massive rebound growth on both sides that is equally smooth and monotonic. An immediate attempt to limit these issues by lowering the time scale rarely resolves this and hours of work is lost. I haven't noticed a pattern as to why, nor any of the traditional reasons for poor convergence (poor mesh stats, ill defined or poor boundary conditions, trying to simulate extremely advanced physics).

Is this generally indicative of a specific mistake?
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Old   October 30, 2012, 16:02
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I'm not sure about the reason for this, but to avoid "hours of work" being lost you should probably start saving backups. At least that way you don't have to start from scratch when you restart the simulation.
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Old   October 30, 2012, 17:24
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are you running a simulation that might have a feature (high pressure wave, shock, or something like that) that is traveling in your domain in a relative "free" area then hits something (boundary of some sort)?

Even steady state solutions can have this phenomena. You might have to "travel" past this to get the correct solution field, or resolve this feature, and proceed to a converge solution.
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Old   October 30, 2012, 17:49
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Following on from Edmund's comment - Do not regard the convergence rebound as "lost work". Generally this means something has happened in the flow which has caused convergence to be harder. This could be an initial condition finally reaching the exit, or conditions being reached where a transient flow can stop up (eg vortex shedding).

The important thing to note is that these effects are real and the apparent good convegernce before-hand was just because the solver did not know that the simulation was harder than it thought. So previously you had an incorrect and optimistic idea of how well it had converged, and you are getting a more realistic picture now.
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