
[Sponsors] 
difference between kOmegaSST (OF1.7.x) and kOmegaSST_lowRe (OF1.6ext) 

LinkBack  Thread Tools  Search this Thread  Display Modes 
June 9, 2011, 09:05 
difference between kOmegaSST (OF1.7.x) and kOmegaSST_lowRe (OF1.6ext)

#1 
Senior Member
Florian Krause
Join Date: Mar 2009
Location: Munich
Posts: 103
Rep Power: 17 
Dear all,
I know there are already two threads existing where the kOmegaSST_lowRe model from OF1.5dev is discussed. Anyway, my issue is not how to set the boundary condition or how to compile the model... Recently I had a closer look at both the kOmegaSST (OF1.7.x) and kOmegaSST_lowRe (OF1.6ext) and try to figure out the differences and thus the need for the kOmegaSST_lowRe model. Both versions calculate the nearwall omega correctly as (below fromOF1.7.x omegaVis) 00207 scalar omegaVis = 6.0*nuw[faceI]/(beta1_*sqr(y[faceI])); The only difference is, that in OF1.7.x omega is calculated as the magnitude of omegaLog and omegaVis, which for y+ approx 1 is omegaVis. The production term G is calculated as (below fromOF1.7.x) 00211 G[faceCellI] = 00212 (nutw[faceI] + nuw[faceI]) 00213 *magGradUw[faceI] 00214 *Cmu25*sqrt(k[faceCellI]) 00215 /(kappa_*y[faceI]); which seems to be exactly the same than in OF1.6ext. Now, the main difference I encountered is the averaging of G and omega in case of multiple boundary faces. In OF1.7.x there is no averaging (only TODO note), whereas in OF1.6ext the averaging is performed. I have no clue why its not yet implemented in OF1.7.x (seems to be fairly easy) but in general it shouldnt affect the result that much. To conclude, you can ONLY use the kOmegaSST_lowRe (OF1.6ext) model in case you are sure that you have a wall resolving grid everywhere in your domain (straight forward to test). On the other hand you can use the kOmegaSST (OF1.7.x) model more general for both, wall resolving grid everywhere in the domain and grids, where the gridpoints normal to the wall are sometimes in the loglayer and sometimes in the viscous sublayer. I think I dont have to mention that both models are no lowRe RANS models in the sense that they don't employ any nearwall damping terms... I would appreciate any comments, especially if I missed anything there or misunderstood parts! Best, Florian 

May 14, 2012, 09:31 

#2 
Senior Member
Anne Gerdes
Join Date: Aug 2010
Location: Hamburg
Posts: 168
Rep Power: 16 
Hey Florian,
do you have an answer to my question, also located in this thread http://www.cfdonline.com/Forums/ope...tml#post360960 I do not understand if the computation of the production term is also valid for low Reynolds turbulence models. My problem is the computation of u_tau in the production term, which is according to the log law, namely u_tau = (c_mu)^(1/4) * sqrt(k). Do you have an idea? Best Regards Anne 

May 15, 2012, 03:44 

#3  
Senior Member
Florian Krause
Join Date: Mar 2009
Location: Munich
Posts: 103
Rep Power: 17 
Quote:
not too much time at the moment, but I just had a quick look again at omegaWallFunctionFvPatchScalarField.C (OF2.0.1). As far as I understand, the idea of this specific wall function is to have reasonable results in case you resolve your boundary layer and in case you have your first cell in the loglaw region. As it is mentioned in the other thread, the production term is correctly calculated for the loglaw region (I didn't verify that again, but assume its correct as you state there). Now, if the viscous layer is resolved and the first cell is at y^+ approx 1, the turbulence production should be very very small (practically zero), right?! This is accomplished by using the loglaw formulation for G as well: In the viscous sublayer, turbulent kinetic energy k is very small and since G ~ sqrt(k), the production term will be very small in case y^+ approx. 1. (as it should be) You can find the same "trick" in the omega boundary conditions: omegaLog ~ sqrt(k) and thus omega = omegaVis and omegaLog is very small in case of y^+ approx. 1. EDIT: The above explanation is specifically for the kOmegaSST RANS model in conjunction with omegaWallFunction. In case you use a "real" lowRe RANS model, you won't use any wall functions of course. Regards, Florian Last edited by florian_krause; May 16, 2012 at 03:42. 

May 16, 2012, 09:02 

#4 
Senior Member
Anne Gerdes
Join Date: Aug 2010
Location: Hamburg
Posts: 168
Rep Power: 16 
Thank you for the explanation, Florian. That makes sense!


Thread Tools  Search this Thread 
Display Modes  

