[Nek5000-users] turbChannel example

[nek5000-users at lists.mcs.anl.gov]

Hi Tanmoy,

thank you for your reply. I did find the correlation in the reference you provided.

I have one more question regarding the implementation of the gradient model:
the gradient model consists of computing \tau defined as proportional to the tensor product \grad u \dot \grad u. Then, once \tau is computed, \grad \tau is added to the momentum equation as a source term. Should I add \grad \tau to the momentum equation using userf function in the user file?

Thanks,
Marco


On Mar 21, 2017, at 9:07 PM, nek5000-users at lists.mcs.anl.gov<mailto:nek5000-users at lists.mcs.anl.gov> wrote:

Hi Marco,

For the gradient model, you can use gradm1() subroutine to calculate the gradient of vx, vy, and vz individually and then the implementation is straightforward.
For the turbChannel example check for the grid (genbox) and the Reynolds number used, such that it matches the paper., param(2) in negative is basically the inverse of dynamic viscosity. So, a properly defined scale, to generate the Reynolds number relationship for you. Eg, if your bulk flow streamwise velocity is 1, and the channel half width is 1, then Re_Delta = param(2), (Reynolds number based on half channel width). The relationship between Re_tau and Re_delta, can be found from Dean's correlation, that is provided in the seminal paper of Kim and Moin (1987) for DNS of Re_tau = 180.

Best Regards,
Tanmoy

On Tue, Mar 21, 2017 at 12:25 PM, <nek5000-users at lists.mcs.anl.gov<mailto:nek5000-users at lists.mcs.anl.gov>> wrote:
Hello,

I am trying to reproduce some of the turbChannel results that were published with Nek5000 in the paper that can be found in the following link:
https://arxiv.org/pdf/math/0205264.pdf

In this paper, two turbulent models are tested: the gradient model and the static Smagorinsky model. The paper also shows results from a coarse DNS for comparison.

The implementation of the static Smagorinsky model is easily done when starting from the turbChannel example but I am not sure how to implement the gradient model since it involves a tensor product \grad u \dot \grad u. Can anyone point me to an example that has a similar implementation or explain how to implement the gradient model in Nek5000?

Is it correct to assume that the current setup of the turbChannel example in Nek5000 should allow to reproduce the coarse DNS results presented in the paper?

What is the relationship between Re_tau and the Reynolds number (param(2)) set in the rea file?

Any help will be appreciated.

Thanks,
Marco
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