Truck Simulation – Boundary Conditions

[TamasBalogh]

Dear OpenLB Users and Developers!

I’ve been trying to simulate the external aerodynamics around a small truck. The truck is about 9 meters long, and the boundary box is about 42 * 17 * 28 meters (the whole STL is in meters).

EDIT: If you’re using Chrome right-click on “Open image in new tab” to see the images.

Working from the “cylinder3d” sample model, I’ve defined the input parameters for the model as you can see below:

My STL mesh is fully enclosed and there are no overlaps. But I cannot get past these boundary condition errors (the setup above yields about 1 million cells):

I do see that the Mach number is way off, but I do not think this is the main cause of the problem, as this seems to come from purely the mesh. I tried increasing the model density up to 1000, then I get about 700 million cells which ate my RAM. For low resolution it does not run, but I’d wish to see OpenLB dealing with the more accurate geometry of the truck.

Is this only the matter of mesh density to fix the issue with boundary conditions ? How should I proceed ?

Any contribution is appreciated!

Many thanks,
Tamas

• This topic was modified 4 years, 1 month ago by TamasBalogh. Reason: - grammar and images not showing

[mgaedtke]

Hi Tamas,

this looks a lot like a problem which is resolution dependent. Keep in mind that those are only warnings (falling back into regular bounce back boundary for these cells), the simulation will still run if the Mach number is realistic.

You can either try to find a compromise for the resolution, for which the mesh still fits your RAM, or run this case on a cluster computer. For 700 million cells I recommend at least 100 cores, better would be 2000.

Best,
Max

[TamasBalogh]

Hello Max!

Thank you for your suggestions! I’ve noticed that the UnitConverter has to be manually set to adapt the Mach Number (this is very counter-intuitive, as with all the input data it should be defined exactly.)

I will experiment a bit further with my setup.

Thanks again,
Tamas

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