I posted a reply focusing on the parts of this thread which are in the
original question (and thus on the SO site). Feel free to edit/suggest
edits.

Ray

On Mon, Apr 4, 2016 at 7:19 PM, Raymond Smith <[email protected]> wrote:

> Thanks, Jon.
>
> I'll post something to StackOverflow in the next few days.
>
> Also, that makes sense about the steady state ignoring the initial
> condition and finding the zero solution. I'd forgotten seeing that in the
> example.
>
> Ray
>
> On Mon, Apr 4, 2016 at 10:06 AM, Guyer, Jonathan E. Dr. (Fed) <
> [email protected]> wrote:
>
>> Ray -
>>
>> Thanks for your very complete and very correct answers to Dario.
>>
>> If you wouldn't mind transcribing your answer to Dario's question on
>> StackOverflow, I'd be happy to up-vote it.
>>
>>
>> In answer to *your* questions:
>>
>> > On Apr 3, 2016, at 11:09 AM, Raymond Smith <[email protected]> wrote:
>> >
>> > Actually, I'm not sure how FiPy treats the steady-state initial guess
>> for Laplace's equation with no flux boundary conditions like yours here.
>> The governing equation + BC's without an initial condition admits any
>> uniform profile as a solution.
>>
>>
>> > I'm still unsure about the treatment of the initial phi values in this
>> sense as mentioned above.
>> > However, the direct-to-steady approach merits a few words of caution.
>> First, there isn't really a good numerical way of directly computing steady
>> state solutions for general systems. Often, your best bet is actually to
>> solve the transient equation by time stepping from some initial condition
>> until you reach steady state, as that's actually probably the most robust
>> algorithm for solving for steady state profiles.
>>
>> The situation is as you expect. We talk about this toward the end of
>>
>>
>> http://www.ctcms.nist.gov/fipy/examples/diffusion/generated/examples.diffusion.mesh1D.html
>>
>> (search for "Fully implicit solutions are not without their pitfalls").
>> Basically, a steady-state diffusive problem will "lose" its initial
>> condition and should instead be solved by relaxation. The timestep can be
>> made very large; there just needs to be a TransientTerm.
>>
>>
>> Note, also, that it's not necessary to constrain the gradient to zero to
>> get no-flux. FiPy is a cell-centered finite volume code, so no-flux is the
>> natural boundary condition if nothing else is specified.
>>
>> - Jon
>> _______________________________________________
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>>
>
>
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