Periodic Pipe Flow LES
I need some advice on modeling a fully developed pipe flow with periodic boundary conditions using LES.
My goal is to get a realistic transient inlet BC for my problem. That's how I'm trying to achieve this:
1. Consider a circular pipe (5*D long) with periodic BCs (mass flow rate).
2. Obtain a steady state solution with RANS (I used SST).
3. Run LES using the RANS solution as initial conditions.
4. Import transient boundary profile as an inlet BC for the LES of my actual problem.
I'm using a hexa-mesh with Y+ at wall around 1, growth ratio around 1,1. Re = 8400, Courant number < 1.
The major problem is that I can't get a converged (judged by residuals) solution with periodic BCs both in transient and steady state. When I run the same model with mass flow inlet and pressure outlet it does converge, but the velocity profile looks unphysical. The other problem is that the flow pattern doesn't become turbulent, even if I add significant velocity fluctuations for the initial velocity field, they tend to damping. So, I would like to ask the following:
1. What are the possible reasons of convergence problems?
2. Probably different convergence criteria should be used with periodic BCs?
3. What kind of grid is better for LES? As far as I know it should be as uniform as possible and have aspect ratios around 1. But what type of mesh is more preferable - tetra or hexa? And why? CFX Reference Guide says it should be isotropic, so tetra is better (18.104.22.168.2. Meshing). I've also seen a post by Mr. Horrocks, where he recommended to use hexa. When I use a tetrahedral mesh with approximately the same sizes I get the same results.
4. What is the reason of the turbulence damping?
Residuals plot for steady state:
Residuals plot for transient:
Velocity profile with mass flow inlet and pressure outlet:
Velocity profile with periodic BCs with specified mass flow rate:
Thanks to everyone in advance! Any help will be greatly appreciated.
High quality grids have less numerical dissipation, converge easier, use less memory (for hex grids) and can handle aspect ratio changes better.
Your comment about not getting turbulent structures confirms you have too much dissipation, so this is a problem for you. You will need central differencing and second order time differencing.
Thanks a lot for your answers! I'm now trying to get the steady state problem converged. To do this I started with agressive physical time scale, then I switched to local timescale factor, and it does converge that way (incredibly slowly though). The text on the link you gave me says not to run with local timescale all the way to convergence. So I switch back to physical time scale, and all important residuals and imbalances (characterizing flow-aligned coordinate) begin to oscillate. And, if you don't mind, I would like to ask some more questions:
1. Is it necessary to get the final convergence without local time scale factor and why?
2. If it is, how to determine how many iterations are sufficient?
3. Will it be possible to reduce the amplitude of residuals/imbalances oscillations on the final iterations with physical timescale if I achive tighter convergence with local time scale factor? (I surely can try it myself, but it takes really long with my available hardware)
4. Probably I still go wrong somewhere? (convergence seems too tough for such a primitve steady-state problem)
5. Concerning LES: how else could I avoid dissipation you mentioned if I was already using central differencing / Euler second order backward and a "structured" hexa mesh?
Thank you again! Sorry for asking too much.
1) Yes, there has been some posts on this on the forum, search for them.
2) Not sure. I would suggest until things settle out. To be completely sure do a sensitivity analysis.
3) Possibly. But if the oscillations are physical then it will not make a difference.
4) You will need quite a large physical time step for this to work. Also be careful about making your mesh too fine for the RANS model.
5) Then you have done the main things. There are also some other options to consider regarding the detailed numerical approach such as Rhie-Chow and interpolation schemes (and others).
Thank yor for your answers!
Oh yes, and I forgot the main way to reduce dissipation - finer mesh and smaller time steps.
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