There's no zero-flux BC on C3 because there's no such thing as C3 as far as 
FiPy is concerned. The boundary conditions on C3 are entirely determined by the 
boundary conditions on C1 and C2 (Dirichlet on the right and Robin on the 
left). The solution obtained satisfies the equations and boundary conditions 
given to FiPy. 

> On Jun 12, 2019, at 2:19 PM, Scott Calabrese Barton <s...@msu.edu> wrote:
> 
> Jon, thanks for catching that typo.  I wish it were the problem!
> 
> The solution with grad phi=0 does not satisfy the zero-flux boundary 
> condition on species 3.  In the absence of a potential gradient, that species 
> would need to also have zero gradient (like species 2 in the current 
> solution).
> 
> So the question becomes how to enforce that zero-flux BC.  Any suggestions? I 
> could drop the conservation equation and replace it with something that 
> enforces zero-flux everywhere, but I’d prefer to use a boundary condition as 
> that would be more applicable in higher dimensions.
> 
> ☘
> 
> 
>> On Jun 12, 2019, at 1:36 PM, Guyer, Jonathan E. Dr. (Fed) via fipy 
>> <fipy@nist.gov> wrote:
>> 
>> Scott -
>> 
>> Eq2 appears to have a typo:
>> 
>> -Eq2 = DiffusionTerm(coeff=z2*C1, var=Phi) + DiffusionTerm(coeff=1.0, var=C2)
>> +Eq2 = DiffusionTerm(coeff=z2*C2, var=Phi) + DiffusionTerm(coeff=1.0, var=C2)
>> 
>> Eq3 has (much) better coupling if written like this:
>> 
>> -Eq3 = DiffusionTerm(coeff=z3*C3, var=Phi) + (C3.faceGrad).divergence 
>> +Eq3 = DiffusionTerm(coeff=z3*C3, var=Phi) - DiffusionTerm(coeff=-z1/z3, 
>> var=C1) - DiffusionTerm(coeff=-z2/z3, var=C2)
>> 
>> [Note that this way you don't need to evaluate .faceGrad at the boundaries, 
>> so your issue #650 doesn't come up. We don't upwind at the boundaries 
>> because it's complicated and expensive to do right and it's unusual to care.]
>> 
>> With these changes, the solution converges in one sweep, but does not agree 
>> with the Analytical Solution you give from West. 
>> 
>> I don't understand a couple of things though. As posed, what governs \Phi? I 
>> get \Phi = 0 and see no reason why it would be otherwise. Typically, I would 
>> expect Poisson's equation to be obeyed. Since you assert charge 
>> electroneutrality, this reduces to Laplace's equation, but in that case, the 
>> slope of \Phi should be constant (unless the permittivity is non-uniform, 
>> but you don't have a permittivity). In the Analytical plot, \Phi has 
>> definite curvature.
>> 
>> My guess is you don't need Eq3 (it'll get taken care of automatically) and 
>> you need some form of Poisson's equation.
>> 
>> - Jon
>> 
>>> On Jun 11, 2019, at 4:48 PM, Scott Calabrese Barton <s...@msu.edu> wrote:
>>> 
>>> I’ve had some trouble using fipy for the 1D, steady-state ternary 
>>> electrolyte problem, which involves coupled, nonlinear migration and 
>>> diffusion.
>>> 
>>> A text version of the model is listed below.  A more complete development 
>>> is at 
>>> https://gcc01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fbit.ly%2F2wJDXob&amp;data=02%7C01%7Cjonathan.guyer%40nist.gov%7C76b3f81e57154ae5f33f08d6ef62b1ed%7C2ab5d82fd8fa4797a93e054655c61dec%7C1%7C1%7C636959604508701127&amp;sdata=IVWC4t%2F3V908aQtRyOmUCUHFVxMn96%2BZfyE457gURv0%3D&amp;reserved=0=
>>>  
>>> 
>>> from fipy import *
>>> 
>>> # Parameters
>>> nx=50
>>> C20=4.0/3.0
>>> z1, z2, z3= 2.0, -2.0, 1.0
>>> 
>>> # Mesh
>>> mesh = Grid1D(nx=nx, dx=1.0/nx)
>>> 
>>> # Variables
>>> C1= CellVariable(mesh = mesh, value = 1.0)
>>> C2= CellVariable(mesh = mesh, value = 4.0/3.0)
>>> Phi = CellVariable(mesh = mesh, value = -0.5)
>>> 
>>> # Electroneutrality
>>> C3 = -1/z3 * (z1*C1 + z2*C2)
>>> 
>>> # Boundary Conditions
>>> C1.constrain(1.0, mesh.facesRight)
>>> C1.constrain(0.0, mesh.facesLeft)
>>> C2.constrain(C20, mesh.facesRight)
>>> Phi.constrain(0, mesh.facesRight)
>>> 
>>> # Governing Equations
>>> Eq1 = DiffusionTerm(coeff=z1*C1, var=Phi) + DiffusionTerm(coeff=1.0, var=C1)
>>> Eq2 = DiffusionTerm(coeff=z2*C1, var=Phi) + DiffusionTerm(coeff=1.0, var=C2)
>>> Eq3 = DiffusionTerm(coeff=z3*C3, var=Phi) + (C3.faceGrad).divergence 
>>> 
>>> Eqns = Eq1 & Eq2 & Eq3
>>> 
>>> # Solution
>>> res = 1e+10
>>> restol= 1e-3
>>> 
>>> while res > restol:
>>>  res = Eqns.sweep()
>>>  print(res)
>>> 
>>> 
>>> However, this system does not converge. I suspect the issue is with 
>>> boundary conditions. I’ve tried zeroing out the diffusion coefficients at 
>>> the boundary, but that does not seem to make a difference here. I am able 
>>> to use this approach for the analogous binary problem: 
>>> https://gcc01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fbit.ly%2F2wOzxfK&amp;data=02%7C01%7Cjonathan.guyer%40nist.gov%7C76b3f81e57154ae5f33f08d6ef62b1ed%7C2ab5d82fd8fa4797a93e054655c61dec%7C1%7C1%7C636959604508701127&amp;sdata=fPKk1duJaGEmdPa5zgSW4KPZmLzjp%2FRZ4mPi5xNMAcE%3D&amp;reserved=0=
>>> 
>>> Any insights or suggestions would be welcome.
>>> 
>>> Cheers,
>>> Scott☘
>>> 
>>> 
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