Simulations with van Leer convection term
The upwind convection term appeared to help the low concentration simulation work. However, the upwind convection term is inaccurate though. Let's use the van Leer convection term instead.
ID | Notes | Issues | Status | movie | |
267 | base | none | benson, hobson, alice (stopped) | 12 | |
268 | none | renfield, sancho, kato (stopped) | 12 | ||
269 | crashes | luggage (stopped) | 12 | ||
270 | none | luggage (stopped) | 12 |
Simulations with a negligible radial displacement
The radial displacement issue has been troubling me. Most of the simulations have had a radial displacement of dr / 10 and some others have dr. Some simulations don't run at all and an instability can clearly be seen to emanate from the r=0 location. I tested the base simulation with dr * 1e-10 just to figure out why I had trouble in the past. Needless to say the simulation seem to be running fine. I have just launched some more simulations with dr * 1e-10 to try and diagnose.
ID | Notes | Issues | Status | movie | |
264 | base | None | benson, hobson, alice (stopped) | 12 | |
265 | worked with upwind convection term | renfield, sancho, kato (stopped) | 12 | ||
266 | crashed | luggage (stopped) | 12 |
Useful Simulations
ID | Notes | diff | Issues | Status | movie | |
222 | base | diff | benson, hobson, alice (stopped) | 12 | ||
225 | diff | luggage (stopped) | 12 | |||
226 | diff | crashed | renfield, sancho, kato (stopped) | 12 | ||
233 | 222: | diff | cluster 7.0 (stopped) | 4 | ||
240 | 222: | diff | crashed | luggage (stopped) | 12 | |
252 | 243: , shift=dx, | diff | cluster 128 (stopped) | 4 | ||
257 | 251: , , shift=2*dx, | diff | luggage (stopped) | 12 |
Edwin Schwalbach Model
For the last three days Eddie and I have been working on his VLS growth model. We've been trying to implement it in FiPy?. We have successfully implemented a two phase, pure, 1D system. His notes are here
The code is here
Essentially, this is simply the van der Waals model with a free energy of the form
We implement the model using the block matrix approach with , and as the base variables to "solve for". The is linearized with,
where,
Remember,
and
and
Explicitly,
and
Source Terms
Take an equation say,
In general can be implemented explicitly (i.e. where is the previous sweep value. Now, to implement this implicitly, we need to linearize,
or
where
In general for stability reasons, though one can often relax this somewhat if the source is not dominant. If the source is not negative, then should be evaluated entirely explicitly. The reason must be negative is the following. Take,
then the discretized implicit form is
Say is positive, then this equation should increase the value of , but if then we get a negative value of . If is negative, there are no stability criterion. Conversely, if then the explicit scheme,
will drive the solution below for sufficiently negative . For very gentle intro,
Pressure velocity coupling
We use the Rhie-Chow interpolation method to deal with this issue since and are not on staggered grids but collocated. Essentially, the Rhie-Chow interpolation scheme corrects the face velocities in the continuity equation by the use of a corrected velocity that approximates solving the momentum equation on the faces. Let's take the discretized form of the x-momentum equation:
where is a cell value. For small enough grid, we would like
that is to say that we would like the residual of the momentum equation evaluated at the face to be equal to the residual of the averaged residual over the neighboring cells. We assume that the terms are unimportant and say that,
We approximate and the we get,
The continuity equation can be written,
Substituting in gives a diffusion term for , which acts to stabilize the solution. See source:trunk/vls/input.py@1031#L78.
Parsitic Currents
Discretize using rather than . This induces dissipation assoicated with momentum. See source:trunk/reactiveWetting/paper/jacqmin.pdf@1031.