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-   -   Factors for the cubic inerpolation scheme in OpenFOAM (https://www.cfd-online.com/Forums/openfoam-programming-development/184766-factors-cubic-inerpolation-scheme-openfoam.html)

 Hoshang March 10, 2017 11:36

Factors for the cubic inerpolation scheme in OpenFOAM

Dear all,

I have a question regarding the used factors for the cubic interpolation scheme in OpenFOAM. Below you can see a part of the code for the cubic interpolation scheme:
Code:

virtual bool corrected() const {     return true; } //- Return the explicit correction to the face-interpolate virtual tmp<GeometricField<Type, fvsPatchField, surfaceMesh>> correction (     const GeometricField<Type, fvPatchField, volMesh>& vf  ) const {       const fvMesh& mesh = this->mesh();       // calculate the appropriate interpolation factors       const surfaceScalarField& lambda = mesh.weights();       const surfaceScalarField kSc       (                 lambda*(scalar(1) - lambda*(scalar(3) - scalar(2)*lambda))          );       const surfaceScalarField kVecP(sqr(scalar(1) - lambda)*lambda);       const surfaceScalarField kVecN(sqr(lambda)*(lambda - scalar(1)));       tmp<GeometricField<Type, fvsPatchField, surfaceMesh>> tsfCorr       (             new GeometricField<Type, fvsPatchField, surfaceMesh>             (                     IOobject                     (                         "cubic::correction(" + vf.name() +')',                         mesh.time().timeName(),                         mesh,                         IOobject::NO_READ,                         IOobject::NO_WRITE,                         false                     ),                     surfaceInterpolationScheme<Type>::interpolate(vf, kSc, -kSc)             )       );       GeometricField<Type, fvsPatchField, surfaceMesh>& sfCorr = tsfCorr.ref();       for (direction cmpt=0; cmpt<pTraits<Type>::nComponents;cmpt++)       {             sfCorr.replace             (                 cmpt,                 sfCorr.component(cmpt)             + (                     surfaceInterpolationScheme                     <                           typename outerProduct                           <                                 vector,                                 typename pTraits<Type>::cmptType                           >::type                       >::interpolate                       (                             fv::gaussGrad                             <typename pTraits<Type>::cmptType>(mesh)                             .grad(vf.component(cmpt)),                             kVecP,                             kVecN                       ) & mesh.Sf()                   )/mesh.magSf()/mesh.surfaceInterpolation::deltaCoeffs()               );         }
The cubic interpolation is done using the linear interpolated term plus a correction term which is defined above in the code. As I understand from the Code the correction uses the factor kSc for the owner point value and -kSc for the neighbor point value. In addition, the gradient of the owner point is added with the factor kVecP and the gradient of the neighbor point with the factor kVecN. With this we get for the value at the surface the following correlation:

Here phi_P and phi_N are the values at the owner and neighbor point and gradphi_P and gradphi_N the gradients at the mentioned points.
But by the use of a normal cubic polynomial function (f(x)=ax³+bx²+cx+d) for the interpolation of the surface value with given values and gradients for the owner and neighbor points as conditions I get another correlation with the defined factors in the above code:

The differences are the opposite signs and the exchange of the factors.
I have tried lot of other numerical interpolation ways to come on the same correlation as used in OpenFOAM but i wasnt sucessful till yet.
Does anyone knows how one gets the correlation which is used in OpenFOAM respectively which interpolation technique gives this correlation with the given values and gradients at the owner and neighbor point?

 sahas March 28, 2017 13:16

I have no deep look into the problem but I am also interesting in that. When lambda is equal to 0.5 both formulas give the same result. Could you post your derivation of the formula please? Of course if it does not cause you any inconvenience :)

 chengyu August 2, 2017 08:26

Cubic scheme derivation

Hey, guys. I have found the same problem as Hoshang met. I post my derivation of cubic interpolation here, if someone can find any errors, plz feel free to point out.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Given the value of the variable and its gradient at point P and N, assume a cubic polynomial variation in the section PN, derive the variable value at the face f.
https://github.com/Daniel-UCAS/image...e.jpg?raw=true     thus a,b,c,d can be solved,   then the variation of in PN can be expressed as     %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

The last equation is what exactly Hoshang gave, which is not the same implemented in OpenFOAM.

Best wishes
Yu Cheng

 sahas August 2, 2017 10:54

Hello, Yu Cheng!
I have checked your derivation and found it to be correct, except one misprint in the formula for : it should be equal to .

I think one should report the bug (https://bugs.openfoam.org/bug_report_page.php).

 chengyu August 2, 2017 22:03

Change the mis-spelling

Yes, you are right, I have changed the original formula, and I think I should better report this to the OpenFOAM official. Thank you.

Best wishes.

Yu Cheng

 sahas August 4, 2017 12:37

Bug report: https://bugs.openfoam.org/view.php?id=2650

 chengyu August 6, 2017 04:25

Hi Alexander,
Thank you for the report.

Best wishes,

Yu Cheng

 lac September 15, 2017 12:05

Hello everyone!

This is my first post in this awsome forum. I hope this question would not be considered as off-topic, as it is related to the cubic scheme.
I started to use openFoam recently, and I'm sure, it is possible to find the answer from the code, but I can't.
Therefore I'd gratefull, if anyone could tell me how the gradients are calculated for the cubic scheme. I mean, are the schemes used from fvSchemes, or are they 'hard wired' in the code for this interpolation scheme.

 sahas September 15, 2017 15:20

Quote:
 Originally Posted by lac (Post 664486) Therefore I'd gratefull, if anyone could tell me how the gradients are calculated for the cubic scheme. I mean, are the schemes used from fvSchemes, or are they 'hard wired' in the code for this interpolation scheme.
Hello!
The scheme for gradient evaluation is hard-coded for cubic interpolation and it is Gauss.

 lac September 16, 2017 04:58

Quote:
 Originally Posted by sahas (Post 664513) Hello! The scheme for gradient evaluation is hard-coded for cubic interpolation and it is Gauss.
Thank you. I guess it is linear then?

What do you think, is it possible to change it to fourth for instance?
Is it enough to modify the lines:
and
to

?

Or use some limiting somehow?

 sahas September 16, 2017 17:54

Quote:
 Originally Posted by lac (Post 664549) Thank you. I guess it is linear then? What do you think, is it possible to change it to fourth for instance? Is it enough to modify the lines: #include "gaussGrad.H" to #include "fourthGrad.H" and >::interpolate ( fv::gaussGrad to >::interpolate ( fv::fourthGrad ? Or use some limiting somehow?
I think it is possible and quite simple. I tried to change the scheme to leastSquares and I had no problems.

 lac September 17, 2017 07:33

Quote:
 Originally Posted by sahas (Post 664611) I think it is possible and quite simple. I tried to change the scheme to leastSquares and I had no problems.
I also tried the leastSquares and it was easy. But the fourth is not working and I don't know how to limit the gradients.

 sahas September 18, 2017 02:04

Quote:
 Originally Posted by lac (Post 664647) I also tried the leastSquares and it was easy. But the fourth is not working and I don't know how to limit the gradients.
I don't look it in deep but I think that you may create your own scheme cubicGrad with runtime-selectable scheme for gradient as it is done for linearUpwind scheme.

 lac September 20, 2017 04:08

Quote:
 Originally Posted by sahas (Post 664715) I don't look it in deep but I think that you may create your own scheme cubicGrad with runtime-selectable scheme for gradient as it is done for linearUpwind scheme.
It's a good idea, although I don't know how to do it, yet. Anyway, thanks.

 Tobi September 22, 2017 05:19

Hi Sahas,

I read your bug report and the comments. Interesting fact. Right now I could imagine that if you have shock-wave propagation, the results might be different based on the gradients of neighbor/owner which are way much more pronounced in such cases than normal ones. Which cases did you check out for your report?

 lac September 22, 2017 05:51

Quote:
 Originally Posted by Tobi (Post 665236) Hi Sahas, I read your bug report and the comments. Interesting fact. Right now I could imagine that if you have shock-wave propagation, the results might be different based on the gradients of neighbor/owner which are way much more pronounced in such cases than normal ones. Which cases did you check out for your report?

I have also seen that report. However, I'm not completely sure about my derivation, but if you change how λ is defined above, from f(x=1-λ) to f(x=λ), the same coefficients as implemented in openFoam currently can be derived.

 sahas September 22, 2017 06:52

Quote:
 Originally Posted by Tobi (Post 665236) Hi Sahas, I read your bug report and the comments. Interesting fact. Right now I could imagine that if you have shock-wave propagation, the results might be different based on the gradients of neighbor/owner which are way much more pronounced in such cases than normal ones. Which cases did you check out for your report?
Hi, Tobi,

I have tried a simple unsteady case of 1D flow with sinusoidal varying velocity at inlet, using uniform and non-uniform grids. The difference between realizations of the cubic scheme is observed only on non-uniform grid and it is quite small (switching to linear or linearUpwind scheme has greater effect).
As for shock-wave case, due to the fact that cubic scheme is central scheme it would be hard to get non-oscillating solution for this case. And again, differences in realizations can be only seen on non-uniform grids, where other numerical errors begin to play the role.
To summarize, the current implementation gives small errors in a final solution. Perhaps, the effect is strong in the some cases of DNS of turbulence. But DNS is not very suitable to be a simple test case :)

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