
[Sponsors] 
September 16, 2009, 05:44 
the differences between turbulence models

#1 
New Member
agung wulan piniji
Join Date: Apr 2009
Posts: 12
Rep Power: 15 
hi guys,
as we know that there are any several turbulence models to simulate physical problems. it couldn't use one turbulence model to simulate all of the problems. i hope you are could explain to me the differences between the turbulence models. such as kepsilon standard and rng, komega standard and sst, spallartallmaras. thank you very much 

September 16, 2009, 07:18 

#2 
Member
TonyD
Join Date: Apr 2009
Posts: 85
Rep Power: 15 
Uhm. This is basic CFD. get yourself a good handbook or usermanual for these type of things... Such questions are not likely to get answered on a forum


September 16, 2009, 07:37 

#3 
Senior Member
teguh hady
Join Date: Aug 2009
Location: Saga, Japan
Posts: 222
Rep Power: 16 
you can find it in CFD book!!!
it can be downloaded free CFD book on this site http://avaxhome.ws/ebooks/science_bo...070016852.html http://avaxhome.ws/ebooks/science_bo...540318003.html 

April 19, 2010, 18:04 

#4 
Senior Member
Join Date: Feb 2010
Posts: 148
Rep Power: 16 
Good question. I have been wondering this myself.
SST is a good default choice SparlartAllmaras: Eeconomical for large meshes. Performs poorly for 3D flows, free shear flows, flows with strong separation. Suitable for mildly complex (quasi2D) external/internal flows and boundary layer flows under pressure gradient (e.g. airfoils, wings, airplane fuselages, missiles, ship hulls). Standard kepsilon : Robust. Widely used despite the known limitations of the model. Performs poorly for complex flows involving severe pressure gradient, separation, strong streamline curvature. Suitable for initial iterations, initial screening of alternative designs, and parametric studies. RNG kepsilon : Suitable for complex shear flows involving rapid strain, moderate swirl, vortices, and locally transitional flows (e.g. boundary layer separation, massive separation, and vortex shedding behind bluff bodies, stall in wideangle diffusers, room ventilation). Realizable kepsilon : Offers largely the same benefits and has similar applications as RNG. Possibly more accurate and easier to converge than RNG. Standard komega : Superior performance for wallbounded boundary layer, free shear, and low Reynolds number flows. Suitable for complex boundary layer flows under adverse pressure gradient and separation (external aerodynamics and turbomachinery). Can be used for transitional flows (though tends to predict early transition). Separation is typically predicted to be excessive and early. SST komega : Offers similar benefits as standard k–ω. Dependency on wall distance makes this less suitable for free shear flows. Reynolds Stress : Physically the most sound RANS model. Avoids isotropic eddy viscosity assumption. More CPU time and memory required. Tougher to converge due to close coupling of equations. Suitable for complex 3D flows with strong streamline curvature, strong swirl/rotation (e.g. curved duct, rotating flow passages, swirl combustors with very large inlet swirl, cyclones). 

June 29, 2018, 17:34 

#5 
New Member
Lucas Gasparino
Join Date: Feb 2018
Posts: 3
Rep Power: 7 
Well, that's a HUGE question... Honestly, I'd recommend Wilcox's book for a good description, and Fluent's user manual is pretty detailed as well. Still, here's a quick summary:
Most of these models are based on the Boussinesq assumption that turbulent stresses act as an additional dissipation term, which is isotropic. Essentialy, instead of having transport equations for the Reynolds stresses, which would result in at least 6 new equations, the usual models focus on creating empirical transport equations for scalars such as turbulence dissipation rate and kinetic energy. A few are actually algebraic, that means they don't rely on PDEs for the modelling. What happens then is that models with more terms are, in general, more capable of capturing complex behaviour such as secondary flows, reattachment of shear layers and boundary layer separation. For example, the standard ke model stands for 2 transport equations: TKE (k) and turbulent energy dissipation (e). It's rather good enough for capturing free shear flows, but it's really poor near solid boundaries, and, for curved geometries, it has poor separation prediction. The SST model combines the simpler ke with the ko model through blending functions, the later model being better at dealing with near wall behaviour. The SpallartAlmaras model is a rather simplistic one equation model that focus on modelling airfoils at normal flight conditions. If stall is to be modelled, the SST model would be a better option. In 3D cases, or cases with very strong swirling, the Boussinesq assumption fails, so the previous models are generally not recommended. In this cases, Reynolds Stress models such as the OmegaRSM are more adequate at capturing the inherent turbulence anisotropy. They are still RANS models tough, so they are quite limited. In practice, RSMs are VERY stiff, so much so that the SST model is the standard recommendation, unless you're studying cyclones or excessive vortex streching. Finally, there's always the option of the scaleresolving models: those are based on length scale filtering, that allows large eddies to be resolved and small ones to be modeled. LES, DES and SAS models are focused on resolving flow structures accurately, so of course they are pretty ressourceintensive. They are inherently transient (although you CAN use SAS in a steady sim, I don't recommend it) and 3D (even though you can enable them in 2D, don't put too much trust in the answers in a quantitative sense), and results become very sensitive to small details, such as mesh structuredness, geometry representation and timestep size. For filtered models, the ONLY spatial discretisation that can be trusted is the Central Difference, as it introduces no extra dissipation. That means looking out for the Courant and Peclet numbers, in order to avoid spurious oscillations in the results. LES is for sure the most intensive model available, so I recommned reserving it for when you've got time to spare, a REALLY powerful computer and a case worth it (don't use it for first design evaluations for example, save it for the last one). DES and SAS are less demanding, as they actually blend LES and URANS approaches, with LES being triggered by the mesh size and turbulence parameters. So, make sure to mesh adequatedly the downstream region, in particular in the free stream shear layers. To close these remarks, RANS and URANS models usually wall function options to better model boundary layers when the y+ value exceeds a certain criterion, and possess different sensitivity to this important parameter. In general, try to get smaller y+ possible/feasible when using more complex models, and definitely avoid Y+ > 300 for ANY case, if wall effects and results are important (Cd and wall heat transfer, for example). For filtered approaches, there is NO wall function, so you'll need this value to be at MOST 1; as well, you'll need at least 15 nodes inside the boundary layer regions to get a decent description, in particular of the viscous sublayer (this is why LES is so demanding for wallbounded flows, even at low Re). Keep in mind that, for LES, it is a good idea to make more than one run with small differences between each, in general small variations to inlet conditions, so you can do some ensemble averaging and prove that your case is ergodic (statistically static for a certain time step). I hope that helps... as everyone said, the subject is quite exhaustive, so if you really are into CFD, get those references mentioned and study, study, and study untill your brain burns out! Some references: Fluent Theory Guide Turbulence Modelling for CFD (D. Wilcox) Multiscale and Multiresolution approaches in Turbulence (P. Sagaut) Basically, any book by P. Sagaut is great for LES references Those are focus on modelling methods and techniques, but I'd suggest you to read a bit about turbulence itself, so the books by Yaglom and Monin are pretty much obligatory, as well as anything by Hunt and Vassilicos. Hinze and Kolmogorov are also mandatory, and P. Davies has an excellent introductory book in turbulence theory. Finally, books on chaos theory and dynamic systems evolution provide a nice and modern view on why turbulence is so complex. Have fun reading and testing!!! 

July 1, 2018, 03:41 

#6 
New Member
Join Date: Jul 2018
Posts: 11
Rep Power: 6 
Hi, In summary it is related to type of your problem and sometimes is kind of experimental choice! In my experience, if I don't know the most appropriate model for a problem I usually start with kepsilon model. For more information about models see the User Fluent Guide or other sources that are available (There are a lot of books and videos. Just google it!).


July 1, 2018, 04:02 

#7 
New Member
Lucas Gasparino
Join Date: Feb 2018
Posts: 3
Rep Power: 7 
Yeah, you're kinda on the right way...
Just keep in mind that all RANS models are quite deficient in some way, and most will be pretty innacurate if you have strong swirling, even the RSMs. Be extra careful with the ke model: it's all too common to use it and not perceive it's flaws. What I can suggest you is that you do a comparison study, maybe in 2D if you PC is not a monster... The wall mounted square is well documented, and at Re=25000 exhibits enough turbulence to be interesting. The only general rule is: avoid algebraic models if you can't calibrate the closure coefficients beforehand. They are brutally dependant on those. Finally, Google is fine enough to gather some ideas, but turbulence modelling is a pretty serious subject, so please check some of the literature. Stuff like production limiters, curvature correction and even coefficient values can be pretty important, and require deep understanding of the model to become useful. In the end though, Menters SST model takes care of most normal flows. If the Reynolds number is not too high, use the intermittency model, preferably in a transient sim. There's no correct answer, no universally better model: you have to find the one that fits your constraints of data quality and sim time. And don't forget to check your numerics: your discretisation method for time and space can have a huge influence in the end results, if you even get them that is. I'll take this little space here to complain that neither FLUENT nor CFX offer an RK4 time stepping scheme... I really miss having a 4th order scheme for time, at least for LES... HAVE FUN! 

Thread Tools  Search this Thread 
Display Modes  


Similar Threads  
Thread  Thread Starter  Forum  Replies  Last Post 
Discussion: Reason of Turbulence!!  Wen Long  Main CFD Forum  3  May 15, 2009 10:52 
Turbulence Models and external flow.  Alan  FLUENT  3  November 22, 2005 05:46 
How to set phase dependent turbulence models?  J.Yang  CFX  2  August 29, 2002 16:39 
Why Turbulence models are not universal.  Senthil  Main CFD Forum  4  July 5, 2000 05:34 