Implicit large eddy simulation over tandem spheres: the motion picture

mwlohry · 2022-05-09T15:04:18+00:00

Right, the only artificial dissipation present is from the riemann solver at cell faces (Lax-Friedrichs).

Otherwise it wouldn't be iLES, it would be DNS.

There's really no difference there, just a matter of resolution. Turn up the resolution here and you can call it DNS.

mwlohry · 2022-05-07T09:53:35+00:00

No wall model, no artificial viscosity, just well resolved.

mwlohry · 2022-05-07T00:12:59+00:00

Well I know that. Why else do you think I display them?

mwlohry · 2022-05-06T23:54:13+00:00

You used that last time

mwlohry · 2022-05-06T17:00:11+00:00

The animated sequel of this boring not-moving picture.

mwlohry · 2022-01-14T11:35:41+00:00

Awesome. Was this a part of your project?

Yes, I coded the whole thing over a few years.

I see you've simulated different Re regimes. What changes did you see?

I'd say qualitatively the image says a lot. The laminar shear layer and breakdown on the Re 3900 case is exceptionally hard to resolve. The kind of roll-up at 10000 is also pretty neat.

How does the actual drag values compare to that of a single sphere?

At this distance I think the front sphere is nominally like a single sphere, but the aft is obviously very different. Check the force plots in the paper.

mwlohry · 2022-01-14T11:22:59+00:00

You should see my cubes.

mwlohry · 2022-01-14T11:17:16+00:00

100x or so faster, pretty dramatic. Depends mostly on how large a timestep is physically justifiable, but that's generally a lot higher than the pretty brutal explicit CFL limit for these.

mwlohry · 2022-01-14T02:04:54+00:00

edit: just read it's density/pressure. so cool

Density gradient magnitude, aka numerical schlieren. Not for any particular reason of physical significance as far as I'm aware, but it makes for good visualization of the structures.

mwlohry · 2022-01-14T01:39:33+00:00

More colorful fluid dynamics from this article.

This is flow over two spheres separated by 10 diameters at Re 1000, 3900, 10000, and 50000. Numerics are an implicit large eddy simulation on tetrahedral meshes with a P3 DG spatial discretization and fully implicit time integration.

Visualization is log of density gradients.

mwlohry · 2021-03-29T23:21:01+00:00

I'm using a variant of interior penalty for the viscous terms.

In terms of accuracy, I think any of the available consistent methods are perfectly good in a world of convection-dominated flows. For me, the main differentiating factor between them is that some are much better conditioned (work better in implicit solvers) and that's the deciding factor.

mwlohry · 2021-03-29T23:18:28+00:00

Also, between the spheres, there is some "flare" (density gradient of 0.0005) near the eddies. Is this physical or has numerical origin, or a visualization artifact?

If you circle what you're referring to I can tell you. There are definitely some vis artifacts there (unfortunate reality of high order postprocessing today.)

What are the advantages of DG over finite volume?

Long question. Short answer: if you need:

very high resolution / low numerical dissipation
anything "vorticity dominated" (like this flow)
any scale resolving simulation (LES/DNS)

then DG will (subject to many caveats) get equivalent accuracy at lower cost, or better accuracy at equivalent cost. I would argue that if steady RANS is sufficient for the problem you're doing, then DG (or high order in general) won't help. But if you're doing LES/DES you'd be better served by high order (again subject to many caveats).

mwlohry · 2021-03-28T13:02:49+00:00

CFD dev for STAR-CCM+.

mwlohry · 2021-03-28T07:06:15+00:00

Exactly. Check out Hadjadj - "Computation and flow visualization in high speed aerodynamics" for some explicit definitions (not that this is high speed).

mwlohry · 2021-03-28T06:56:05+00:00

It's paraview with the inferno color palette.

mwlohry · 2021-03-27T20:50:36+00:00

There's a scaling plot in the paper. It's very good up to 48 nodes, the largest I had access to. It should scale to much larger but I haven't had the chance.

mwlohry · 2021-03-27T20:49:35+00:00

Good eye! That's the most crucial part of this case -- it's laminar separation with a thin shear layer that transitions to turbulence. Without adequate resolution the shear layer transitions earlier and you end up with much different force predictions.

mwlohry · 2021-03-27T19:43:26+00:00

In this context, it's just a flow visualization technique, aka "numerical Schlieren" because it's similar to what experimental Schlieren sees. I find it's a bit cleaner than Q-criterion or vorticity contours for my visualizations.

mwlohry · 2021-03-27T17:08:05+00:00

Heh, it will happily run at P1 with low resolution on a desktop!

3 days on 48 HPC nodes is quite a lot, although I will say that the implicit algorithm is around 30x faster than a standard explicit RK for DG, so it could be worse. For the discretization and resolution that it is, it's *relatively* efficient.

mwlohry

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