Update: The mesh2DCoupled example did work, but I had to change the grid dimensions make it look like the pictures online. However, it's also incredibly slow. I left it running overnight and it only reached elapsed time of about 0.6. It being so slow for a simple system may explain why it can't deal with my more complicated coupled system. Is this expected behavior? Is there any way to speed things up so that my system has a chance of running at all?
On Mon, Jan 13, 2014 at 2:11 PM, Jane Hung <[email protected]> wrote: > Yes, restricting the time step works. However, whenever I split up the > equation (like d(phi)/dt = Xi, Xi= laplacian(phi)), it is never able to run. > > Also, when I run the Cahn-Hilliard mesh2DCoupled example, the results are > that the concentration becomes more and more homogeneous rather than phase > separation. This is very different than the expected results shown on the > examples page (which is what I get when turning the 3 equations into just 1 > equation) > > On Jan 11, 2014, at 9:07 AM, Guyer, Jonathan E. Dr. < > [email protected]> wrote: > > It looks to be stable up to time steps of about 25. You are using the > exponentially increasing stepper from our Cahn Hilliard examples, which are > unconditionally stable (and we have them top out at 100). Because of the > explicit terms in your splitting, you should keep your time steps below the > stability limit. > > FYI: dropbox is completely blocked from our DNS servers at NIST. I > happened to see your message at home, so could download the movie > independent of the NIST network, but that's not normally true. If you have > large files to share with us in the future, let us know and we can provide > a place to put them. > > > On Jan 10, 2014, at 11:23 AM, Jane Hung <[email protected]> wrote: > > I tried to start with a simpler system, and it seems like I get the same > problem if I split up the equations at all. > > Anyway, I started with a 1 equation system http://pastebin.com/X5tT1RUBand > would like to see the phase separation, but after time ~2000 (see the > video https://www.dropbox.com/s/nocwmh8x1f5b6rw/1_order_parameter.mp4), > the error increases a lot. I'd like to see what happens after more > iterations, so is there a way to keep the error small? > > > On Mon, Dec 30, 2013 at 10:50 AM, Daniel Wheeler < > [email protected]> wrote: > On Sun, Dec 29, 2013 at 6:28 PM, Jane Hung <[email protected]> wrote: > > I'm also getting RuntimeError. To get over this, is there a way to > represent > the system a different way or does the system itself too complicated? > > > You can also represent the system in an entirely uncoupled manner. > That would reduce the size of memory and provide an alternative > result. If the time step is small enough the uncoupled and coupled > formulations should be the same. > > What do you mean by know the answer? > > > I just meant some analytical result or behavior such as bounded values > or conserved quantities. A demonstrable logical inconsistency makes > debugging easier. > > I have an idea of what the time > evolution of the variables should look like in the 2D case, but I don't > have > an analytical solution. > > > That helps. Could you hold some of the variables fixed (by changing > coefficient values or time steps for some equations) and then evolve > only one or two of the equations for example. > > -- > Daniel Wheeler > _______________________________________________ > fipy mailing list > [email protected] > http://www.ctcms.nist.gov/fipy > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] > > > > -- > Jane Hung > Graduate Student | MIT Department of Chemical Engineering > Hatton Lab 66-325 | Doyle Lab E18-509 > [email protected] | 415.952.6325 > _______________________________________________ > fipy mailing list > [email protected] > http://www.ctcms.nist.gov/fipy > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] > > > > _______________________________________________ > fipy mailing list > [email protected] > http://www.ctcms.nist.gov/fipy > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] > > > -- Jane Hung Graduate Student | MIT Department of Chemical Engineering Hatton Lab 66-325 | Doyle Lab E18-509 [email protected] | 415.952.6325
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