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Source terms in epsilon equation (kEpsilon RANS) |
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#1 |
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Dear all,
I'm somewhat experienced in using openFoam, but mostly I've been using already existing stuff so far. Now I'm looking into implementing other things, in this case turbulence model. But before I do that, I have a question about the existing implementation of kEpsilon model. Why are source terms treated differently? Equation: Code:
// Dissipation equation tmp<fvScalarMatrix> epsEqn ( fvm::ddt(epsilon_) + fvm::div(phi_, epsilon_) - fvm::laplacian(DepsilonEff(), epsilon_) == C1_*G*epsilon_/k_ - fvm::Sp(C2_*epsilon_/k_, epsilon_) ); This is maybe a silly question, but I would like to understand it. Thanks for reading! ![]() |
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#2 |
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OK, what I know so far is that G is evaluated explicitly due to the fvc::grad:
nut_*2*magSqr(symm(fvc::grad(U_)) But the epsilon_ could still be treated implicitly? Or? Thank you (and please help) |
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#3 |
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anonymous
Join Date: Aug 2014
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All the therms that have fvm:: are treated as implicit. What I'm not sure about is the term:
Code:
C1_*G*epsilon_/k_ Code:
fvm::Sp(C1_*G/k_,epsilon_) |
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#4 |
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ali alkebsi
Join Date: Jan 2012
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Total agree with your reasoning here. Why explicit?
Maybe the epsilon generation term is taken as a function of the last epsilon Like saying the amount of epsilon that we had is the cause of the generation. but then why is the destruction term implicit? maybe both were chosen like this for stability reasons? |
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#5 | ||
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Quote:
![]() Quote:
![]() Thanks for your answers!
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#6 | |
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Gerhard Holzinger
Join Date: Feb 2012
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Quote:
The difference between the two source terms is the sign. Both depend on epsilon, so you could in theory handle them both implicitely. However, the sign determines whether the implicit handling improves numerical behaviour or degrades it. A negative term on the RHS is a positive term if brought to the LHS. Further, implicit terms go into the main diagonal of the system matrix of the discretized equation system. So, by treating negative source terms (on the RHS) implicitely, we add to the main diagonal of the system matrix. Thus we increase the so called diagonal dominance of the matrix which in turn helps numerical iterative solution procedures. |
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#7 |
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Thank you.
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