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Problem with implementation LES Clark model

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Old   October 13, 2016, 16:45
Default Problem with implementation LES Clark model
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Lorenzo
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Hi everyone,

I'm trying to implement the LES Clark model which is well described in the book of Pope "Turbolent Flows" at page 628.I am using OF 2.4.0.

My current problem is defining in Foam the Leonard contribution L_ij of the SGS tensor.
In my opinion this quantity should be written as fvc::grad(U()) & (fvc::grad(U())).T() but foam complains about the fact that this is not a volSymmTensorField. The SGS tensor contains in a sum L_Ij (Germano decomposition) so also L_ij must be symmetric.

1)Is the implementation fvc::grad(U()) & (fvc::grad(U())).T() in accordance with the thoery of this model in your view?

2)Is fvc::grad(U()) & (fvc::grad(U())).T() a symmetric Tensor or am I wrong also with this issue?

If there is anyone with more experience than me in programming in foam please help me , I really got confused with this matter.

Thanks in advance
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Old   October 18, 2016, 17:55
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Ehsan Asgari
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Quote:
Originally Posted by Lorenzo92 View Post
Hi everyone,

I'm trying to implement the LES Clark model which is well described in the book of Pope "Turbolent Flows" at page 628.I am using OF 2.4.0.

My current problem is defining in Foam the Leonard contribution L_ij of the SGS tensor.
In my opinion this quantity should be written as fvc::grad(U()) & (fvc::grad(U())).T() but foam complains about the fact that this is not a volSymmTensorField. The SGS tensor contains in a sum L_Ij (Germano decomposition) so also L_ij must be symmetric.

1)Is the implementation fvc::grad(U()) & (fvc::grad(U())).T() in accordance with the thoery of this model in your view?

2)Is fvc::grad(U()) & (fvc::grad(U())).T() a symmetric Tensor or am I wrong also with this issue?

If there is anyone with more experience than me in programming in foam please help me , I really got confused with this matter.

Thanks in advance
Hi,

take a look at HomogeneousDynamicSmagorinsky in 2.3.1 version to find how Leonard stress is calculated.

Syavash
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