Hi Dmitry,

to follow up on your bug report, I opened an issue 
https://git.iws.uni-stuttgart.de/dumux-repositories/dumux/-/issues/892 
<https://git.iws.uni-stuttgart.de/dumux-repositories/dumux/-/issues/892>.
There is a simple fix here:
https://git.iws.uni-stuttgart.de/dumux-repositories/dumux/-/merge_requests/2146 
<https://git.iws.uni-stuttgart.de/dumux-repositories/dumux/-/merge_requests/2146>

Can you try if this improves your convergences / fixes your problem?

The problem with this solution is that it significantly increases the runtime 
for models where it is known that there is no dependence
of the scv volume variables on the other dofs of the same element. It might be 
possible to deduce this somehow.

Timo

-- 
_________________________________________________

Timo Koch                                      phone: +49 711 685 64676
IWS, Universität Stuttgart                  fax:   +49 711 685 60430
Pfaffenwaldring 61         email: timo.k...@iws.uni-stuttgart.de
D-70569 Stuttgart             url: www.iws.uni-stuttgart.de/en/lh2/
_________________________________________________

> On 26. May 2020, at 17:13, Dmitry Pavlov <dmitry.pav...@outlook.com> wrote:
> 
> Hello,
> 
> I am trying to do a 1D porous medium flow simulation where one of the 
> components is a surfactant that affects krw and krn. The effect of the 
> surfactant depend on pressure gradient.
> 
> Earlier, an attempt [1] was made to apply CC method for this kind of problem. 
> It turned out that DuMux API does not easily allow to estimate a gradient in 
> TPFA, and, following Timo Koch's advice, I gave a try to Box method.
> 
> I think I am having some trouble with derivatives now. Looking at this 
> comment in boxlocalassembler.hh, I am beginning to understand why.
> 
>         // Calculate derivatives of all dofs in stencil with respect to the 
> dofs in the element. In the //
>         // neighboring elements we do so by computing the derivatives of the 
> fluxes which depend on the //
>         // actual element. In the actual element we evaluate the derivative 
> of the entire residual.     //
> 
> Why the trouble? Well, I am calculating the pressure gradient (by calling 
> evalGradients) inside this method
> 
>     MaterialLawParams materialLawParams(const Element& element,
>                                         const SubControlVolume& scv,
>                                         const ElementSolution& elemSol) const
> 
> Here, I store the needed numbers for krw and krn calculation in 
> MaterialLawParams, and they are properly downstream at MaterialLaw::krw and 
> MaterialLaw::krn.
> 
> Now, let my have two neighbor boxes, 0 and 1. Pressure in box 1 affects the 
> krw/krn in box 1. evalGradients, when called, duly calculates pressure 
> gradient in box 0 depending, among others, on the pressure value in box 1. 
> That is good.
> 
> But it turns out that the numerical differentiation algorithm does not bother 
> to call materialLawParams() for scv-s in box 0 when it calculates the 
> derivatives of fluxes in box 0 w.r.t. pressure in box 1. I suppose that it 
> has to do with the comment above. I suppose that it takes into account only 
> the "transmissibility" part of the effect of pressure in box 1 to flux in box 
> 0, and skips the part that comes from krw/krn sensitivity to the pressure 
> gradient.
> 
> Also this comment in boxlocalassembler.hh may be relevant too.
> 
>                 // TODO additional dof dependencies
> 
> 
> I will very much appreciate answers to the following questions:
> 
> 1. Am I correct about the behavior of the numerical Jacobian assembler, or it 
> should be all right and there is a bug somewhere in my code or DuMux's?
> 
> 2. In case I am correct, is there an easy (or not) way to force DuMux into 
> recalculating the material law parameters for scv-s that belong to DOFs 
> w.r.t. which we take the derivative? Or take some other approach?
> 
> 3. If not, will the hand-made analytic Jacobian help? Or it will fail due to 
> some other assumption in the DuMux engine that is not true for my problem?
> 
> (I actually have the analytic Jacobian implemented, but not quite sure it is 
> correct, partially because, well, I never had a chance to test it against a 
> correct numeric Jacobian).
> 
> 
> Thank you for your time.
> 
> Best regards,
> 
> Dmitry
> 
> 
> 
> [1] https://listserv.uni-stuttgart.de/pipermail/dumux/2020q2/002516.html
> 
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