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A few simple questions about linearUpwind and limitedLinear 

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September 28, 2011, 13:58 
A few simple questions about linearUpwind and limitedLinear

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Daniel P. Combest
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I am a writing about the schemes that I used in my simulations in my thesis and could use some clarification on the linearUpwind and limitedLinear schemes. I have read second order schemes and Alberto did a good explanation, but I need a little more clarification.
linearUpwind: I know linearUpwind is second order and bounded by a limiter (e.g. cellMDLimited from cellMDLimited vs. cellLimited). This is different than the limiters used in limitedLinear. In Fluent documentation, the definition of second order upwind is given as: where and are the face value of phi and the cell centered values of phi in the upstream cells respectively. I am reading through the code of linearUpwind and I see: Code:
GeometricField<Type, fvsPatchField, surfaceMesh>& sfCorr = tsfCorr(); const surfaceScalarField& faceFlux = this>faceFlux_; const labelList& owner = mesh.owner(); const labelList& neighbour = mesh.neighbour(); const volVectorField& C = mesh.C(); const surfaceVectorField& Cf = mesh.Cf(); GeometricField <typename outerProduct<vector, Type>::type, fvPatchField, volMesh> gradVf = gradScheme_().grad(vf); forAll(faceFlux, facei) { if (faceFlux[facei] > 0) { label own = owner[facei]; sfCorr[facei] = (Cf[facei]  C[own]) & gradVf[own]; } else { label nei = neighbour[facei]; sfCorr[facei] = (Cf[facei]  C[nei]) & gradVf[nei]; } } When is the sfCorr used to correct the value of the face? I guess I am just interested in generating a discussion and confirming or clarifying my thoughts. limitedLinear This again is second order and is bounded using a sweby limiter (second order schemes post 16). I am just a little fuzzy on what the final simplified form of the equation is for limitedLinear (I admit I haven't looked at it as much as linearUpwind). I am out of my office and will look through Richard Pletcher, John Tannehill and Dale Anderson when I get a chance. Laslty, correct me if I'm wrong but the parameter following a definition of a limitedLinear declaration is passed to the limiter, where 1 uses the limiter and 0 does not (with anything in between being a blend). Sorry for the massive post, and any clarification would be fantastic and if I find an answer, I will post the result here. And for those interested on how I did the math in the forum, look at (Guide: Writing Equations in LaTeX on the CFD Online Forums) Dan Last edited by chegdan; September 29, 2011 at 13:24. 

September 28, 2011, 19:05 

#2 
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Daniel P. Combest
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on the limitedLinear, it seems that my knowledge of limiters is lacking and it may turn out to be a simple answer. Looking in Dr. Jasak's thesis (pg 98), I found that:
where is the value of phi at the face for a higher order scheme. For limitedLinear, it is just the central difference scheme as the "HO" and the limiter () is a Sweby limiter (http://www.cfdonline.com/Forums/ope...arscheme.html). if there is more to add here or there are corrections then please do. Dan 

September 29, 2011, 04:48 

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Chris
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Yes you are right. limitedLinear is using the Sweby limiter [1]. If you want further information about TVD Schemes and different limiters, I think [2] might be interesting to get a first brief impression.
About linearUpwind I don't know much. Till now I just thought it is something like linear upwind differencing but reading your post seems like its only half the story. [1] P.K. Sweby. High resolution schemes using flux limiters for hyperbolic conservation laws.SIAM Journal on Numerical Analysis, (Vol. 21):pp. 995–1011, 1984. [2] H. K. Versteeg and W. Malalasekera. An Introduction to Computational Fluid Dynamics: The Finite Volume Method. Pearson, 2007. 

September 29, 2011, 14:37 

#4 
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Daniel P. Combest
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@caramelo : I found a mistake in my first post concerning the linearUpwind definition and just corrected it (sorry about that). I did have a chance to look at the Sweby paper and also a few other sources on TVD schemes, very interesting. Thanks for the sources.
I see throughout the forum that the linearUpwind is bounded, but Ferziger and Peric' note that second order upwind is unbounded. My question is that if one uses Gauss linear as a grad scheme for linearUpwind, will this approach the traditional second order upwind and therefore unbounded? Also, is Gauss linear just the arithmetic average of the two cells or is it the distance weighted average similar to the linear divScheme for advection? Lastly, is the linearUpwind scheme only bounded if limited versions of the gradient scheme are used, i.e. limited linear, cellLimited, faceMDLimited etc.? Dan 

October 1, 2011, 15:51 
[Solved] A few simple questions about linearUpwind and limitedLinear

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Daniel P. Combest
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Quote:
Quote:
In the end I think that I have the answer that I was looking for. Dan 

October 3, 2011, 03:45 

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Florian Krause
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Hi Dan,
Quote:
Apart from this, as far as I understand, linearUpwind scheme is unbounded as long as you don't specify one of the limiters cellLimited, faceLimited etc. Best, Florian 

October 3, 2011, 12:55 

#7  
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Daniel P. Combest
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Quote:
and of course: Quote:
Dan 

October 18, 2013, 23:49 
How can you find out which file contains the source code implementing the 'linearUpwi

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yehanyu
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Quote:


October 21, 2013, 09:57 

#9 
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Daniel P. Combest
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Linux commands to search for file names and within files are your friend. To look for the linearUpwind source, try
Code:
cd $FOAM_SRC grep R 'linearUpwind' . Code:
cd $FOAM_SRC find . name 'linearUpwind.C' 

October 26, 2013, 22:44 

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yehanyu
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Thank you very much.


January 10, 2014, 18:51 

#11  
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Anne Gerdes
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Quote:
I found your post which is very interesting for me. Could you please tell me how one can derive the equation above? I found this equation implemented in OpenFOAM, and in Fluent it is obviously the same. But I have problems in understanding this equation. For LUDS (linear upwind) we discretize the face value as How is the implemented formula connected to that? Thank you very much for an answer in advance! Anne 

April 10, 2015, 03:47 

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Taylor Expansion around P gives you this formula: Now for upwind the flux over the east surface of a 2D CV for a flow from west: The rest of the equation is the truncation error, thus first order. If you also calculate the first truncated term your scheme will become second order and you will get this expression for your flux over face e: CDS for the gradient gives: For You get: That equals your expression: Hope that helps Last edited by Bazinga; April 13, 2015 at 03:41. 

April 10, 2015, 04:54 

#13 
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Anne Gerdes
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Thank you very much for your answer! Meanwhile I have also been able to understand the formula, but it is nice to see the answer here as well.
Have a nice day! Anne 

October 10, 2015, 11:52 

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Davi Barreira
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October 11, 2015, 02:29 

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October 11, 2015, 10:17 

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Davi Barreira
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One thing got me confused though, in the OpenFOAM website (http://cfd.direct/openfoam/userguide/fvschemes/), it's written "Some TVD/NVD schemes require a coefficient ψ,0 ≤ ψ ≤ 1 where ψ = 1 corresponds to TVD conformance, usually giving best convergence and ψ = 0 corresponds to best accuracy. Running with ψ = 1 is generally recommended."
So this implies that using ψ = 0 would give the higher order scheme (central difference), which is the opposite stated in dr. Jasak's thesis. I created a new thread with some more questions related to the topic. TVD schemes, questions about limitedLinear Any thoughts? 

October 13, 2015, 03:59 

#17 
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Anne Gerdes
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Dear Bazinga and Davi,
I try to derive the implemented formula once again: Two cell centers in upwind flow direction ( and ) are taken into account. The Taylor series leads to the approximation of at cells and and, subsequently, at face where denotes the distance from to . The first order upwind approximation is numerically very stable, as the upwind term stabilizes the diagonal of the matrix. Therefore, we use the implicit term of an upwind discretization as a matrix coefficient and add the remaining terms as explicit correction terms on the righthand side of the equation system. The numerical approximation for the LUDS discretization thus transforms to The second term is the explicit correction term. This equals the implemented formula. 

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limitedlinear, linearupwind 
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