The vector formulation is still rather slow (much much slower than with
just one equation). Is that expected?
 On Jan 14, 2014 12:10 PM, "Guyer, Jonathan E. Dr." <[email protected]>
wrote:

> Coupled Cahn Hilliard has known problems:
> http://matforge.org/fipy/ticket/582
>
> I don't know whether the issues described in that ticket are the source of
> what you're seeing, but it can't help. For your problem, you may want to
> base what you're doing on the vector formulation in that example.
>
> On Jan 14, 2014, at 11:31 AM, Jane Hung <[email protected]> wrote:
>
> > 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/X5tT1RUB and 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
> >>> _______________________________________________
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> >>>
> >>>
> >>>
> >>> --
> >>> 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
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> >>
> >>
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> >
> >
> >
> >
> > --
> > 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
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> > http://www.ctcms.nist.gov/fipy
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