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Make modifications on the Lagrangian stochasticDispersionRAS model

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Old   August 10, 2018, 06:40
Default Make modifications on the Lagrangian stochasticDispersionRAS model
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Dear all,

I'm using the Lagrangian stochasticDispersionRAS model to simulate the dispersion of particles suspended in turbulence. But the stochasticDispersionRAS model in OpenFOAM just describes homogeneous flows. In inhomogeneous flows, it needs to add a drift correction. The total equation describing the stochastic dispersion model is shown in the figure in the attachment.

But now I have problems with programming because, in the Lagrangian codes, all the parameters we got are scalars or vectors, but the last term in the equation needs velocity of volVectorField. I don't know how to solve this now.

Anyone has the idea of the programming?

Thanks in advance.

Maria
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Old   August 10, 2018, 06:42
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The equation is in the attachment, sorry for forgetting it.
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Old   February 15, 2020, 20:26
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Hi marialhm!
I believe you are trying to incorporate the Langevin equations in your turbulent dispersion model.
Did you succeed in getting it to work with OpenFOAM? If yes, then can you share how you went about coding the drift correction term?

Thanks
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Old   February 16, 2020, 10:54
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I found a reference,
On this webpage:
http://www.tfd.chalmers.se/~hani/kurser/OS_CFD/
search:
Modification of Stochastic Model in Lagrangian Tracking Method
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Old   February 16, 2020, 11:02
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Thanks for your reply zhangyan!
I have seen that reference before. But I believe that is just a modification of the current isotropic dispersion model in OF to account for anisotropy. That does not solve for the Langevin equations.
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Old   November 23, 2022, 09:36
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My GitHub repository has implemented the Langevin equation in OpenFOAM for LES. We have given a test case of decaying homogeneous isotropic turbulence. It would be simple to adapt it for RAS turbulence if necessary.


Importantly, the closures we use in this repository for drift and diffusion are inferred from machine learning models. But, it is also simple to adapt for theoretical closures for drift and diffusion (e.g. Pope's simplified Langevin model)
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