Optimisation for steady-state flows
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| == End the simulation when the state is steady == | == End the simulation when the state is steady == | ||
| - | In the same mail thread, Stéphane shows how to stop simulation as soon as a steady state is reached. This optimisation won't decrease computing time of the simulation, but will end it automatically without watching you how the flow develops. | + | In the same [http://sourceforge.net/mailarchive/message.php?msg_id=dffa7a3b0611011420v5b1cc1cdr254005b4877fc82c%40mail.gmail.com mailing list thread], Stéphane Popinet shows how to stop simulation as soon as a steady state is reached. This optimisation won't decrease computing time of the simulation, but will end it automatically without watching you how the flow develops. |
| In your calculation script, remove the end time and insert an [[GfsEventStop]]. The result could look like this: | In your calculation script, remove the end time and insert an [[GfsEventStop]]. The result could look like this: | ||
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| == Using a different solver == | == Using a different solver == | ||
| - | The third point Stéphane made in this thread belongs to the type of solver. He writes: | + | The third point Stéphane made in this [http://sourceforge.net/mailarchive/message.php?msg_id=dffa7a3b0611011420v5b1cc1cdr254005b4877fc82c%40mail.gmail.com thread] belongs to the type of solver. He writes: |
| :''Also for Stokes flows, you probably want to use the fully-implicit diffusion solver to avoid potential oscillations in time in the solution which can appear when using the default Crank-Nicholson diffusion solver. This decreases the time-accuracy from second-order to first-order but it doesn't matter since you are looking for a steady solution.'' | :''Also for Stokes flows, you probably want to use the fully-implicit diffusion solver to avoid potential oscillations in time in the solution which can appear when using the default Crank-Nicholson diffusion solver. This decreases the time-accuracy from second-order to first-order but it doesn't matter since you are looking for a steady solution.'' | ||
Revision as of 00:03, 8 February 2008
Often, you're not particularly interested in how a flow or stream develops over time, but only how the constant flow behaves if it exists long enough to have all initial reactions and changes settled. While Gerris isn't optimised for such calculations, a few simplifications and speed-ups exist.
Contents |
Getting rid of advection calculations
In a mailing list thread people agree, a steady-state solution behaves equally to a pure Stokes flow and advection terms are negligible. You can switch them off:
GfsAdvectionParams { scheme = none }
For an example, see the Couette flow test case.
To give the removal of advection evidence, I've run the example from An engineer's pipe flow with the viscosity of water and up to time t = 1.1 (with advection it's divergent at t = 1.107) with and without advection:
With advection, the calculation time was 4436 seconds. Without advection, this shortened to just 77 seconds.
As you can see, there are pretty big differences.
A tenth of fluid domain time later, the advection version appeard to "explode". Shortly thereafter, the timestep goes down to almost zero and stays there forever.
Just for Info, the same flow without advection a lot later.
End the simulation when the state is steady
In the same mailing list thread, Stéphane Popinet shows how to stop simulation as soon as a steady state is reached. This optimisation won't decrease computing time of the simulation, but will end it automatically without watching you how the flow develops.
In your calculation script, remove the end time and insert an GfsEventStop. The result could look like this:
GfsTime { } GfsEventStop { istep = 1 } U 1e-3 DU
-
Uis the variable to watch. Variables other than velocity should work as well. - The number behind this is the threshold (difference to previous value) at which the simulation is stopped when reached.
- The
DUis finally an optional variable where the current difference is put in.
You can also add an additional
GfsOutputScalarNorm { istep = 1 } stdout { v = DU }
to watch this variable and how the velocity changes get fewer and fewer from step to step.
With this optimisation the simulation stops at a fluid domain time of 7.8 or a CPU time of 540 seconds and the results should be within a 1% accuracy of what you can reach.
- Nota Bene: It's a simulation after all and if a simulation would fit reality within a 1% accuracy, this would be stunning.
Pause
The above is wrong. GfsEventStop didn't stop the simulation at all. Because advection was turned off? The Couette flow script isn't a good measure as this simulation has a second stop condition (iend=100).
Using a different solver
The third point Stéphane made in this thread belongs to the type of solver. He writes:
- Also for Stokes flows, you probably want to use the fully-implicit diffusion solver to avoid potential oscillations in time in the solution which can appear when using the default Crank-Nicholson diffusion solver. This decreases the time-accuracy from second-order to first-order but it doesn't matter since you are looking for a steady solution.
Again, it's simple to do so. Remove or comment out your GfsSourceDiffusion lines, then add a:
GfsSourceViscosity {} 1 { beta = 1 }
--Traumflug 15:21, 7 February 2008 (PST) I have yet to re-read what's the difference between GfsSourceDiffusion and GfsSourceViscosity, as only one of both is allowed. Additionally, running the example and comparing the results is yet to be done. In a first test, automatically ending the simulation suddenly worked and everything was done after only 3 time steps. Also, check the second part wether changing the line with GfsTime is neccessary or wether GfsEventStop has a higher precedece.
