Looks great, thanks.

> On Apr 5, 2016, at 4:22 PM, Raymond Smith <[email protected]> wrote:
> 
> 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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