7.3
general documentation
Functions
cs_les_mu_t.h File Reference
#include "cs_base.h"
+ Include dependency graph for cs_les_mu_t.h:

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Functions

void cs_les_mu_t_smago_dyn (cs_real_33_t *gradv)
 Calculation of turbulent viscosity for a dynamic Smagorinsky LES model. More...
 
void cs_les_mu_t_smago_const (cs_real_33_t *gradv)
 Calculation of turbulent viscosity for a Smagorinsky LES model. More...
 
void cs_les_mu_t_wale (cs_real_33_t *restrict gradv)
 Compute the turbulent viscosity for the WALE LES model. More...
 

Function Documentation

◆ cs_les_mu_t_smago_const()

void cs_les_mu_t_smago_const ( cs_real_33_t *  gradv)

Calculation of turbulent viscosity for a Smagorinsky LES model.

\[ \mu_T = \rho (C_{S} l)^2 \sqrt{2 S_{ij}S_{ij}} \]

\[ S_{ij} = \dfrac{\der{u_i}{x_j} + \der{u_j}{x_i}}{2}\]

Parameters
[out]gradvthe computed velocity gradients !

\[ \mu_T = \rho (C_{S} l)^2 \sqrt{2 S_{ij}S_{ij}} \]

\[ S_{ij} = \dfrac{\der{u_i}{x_j} + \der{u_j}{x_i}}{2}\]

Parameters
[out]gradvcomputed velocity gradients (may be used by caller) !

◆ cs_les_mu_t_smago_dyn()

void cs_les_mu_t_smago_dyn ( cs_real_33_t *  gradv)

Calculation of turbulent viscosity for a dynamic Smagorinsky LES model.

\[ smago = \dfrac{L_{ij}M_{ij}}{M_{ij}M_{ij}} \]

\[ \mu_T = \rho smago L^2 \sqrt{2 S_{ij}S_{ij}} \]

\[ S_{ij} = \dfrac{\der{u_i}{x_j} + \der{u_j}{x_i}}{2}\]

Parameters
[out]gradvthe computed velocity gradients !

Calculation of turbulent viscosity for a dynamic Smagorinsky LES model.

\[ smago = \dfrac{L_{ij}M_{ij}}{M_{ij}M_{ij}} \]

\[ \mu_T = \rho smago L^2 \sqrt{2 S_{ij}S_{ij}} \]

\[ S_{ij} = \dfrac{\der{u_i}{x_j} + \der{u_j}{x_i}}{2}\]

Please refer to the dynamic Smagorinsky model section of the theory guide for more informations.

Parameters
[out]gradvthe computed velocity gradients !

◆ cs_les_mu_t_wale()

void cs_les_mu_t_wale ( cs_real_33_t *restrict  gradv)

Compute the turbulent viscosity for the WALE LES model.

The turbulent viscosity is: $ \mu_T = \rho (C_{wale} L)^2 * \dfrac{(\tens{S}:\tens{Sd})^{3/2}} {(\tens{S} :\tens{S})^(5/2) +(\tens{Sd}:\tens{Sd})^(5/4)} $ with $ \tens{S} = \frac{1}{2}(\gradt \vect{u} + \transpose{\gradt \vect{u}})$ and $ \tens{Sd} = \deviator{(\symmetric{(\tens{S}^2)})}$

Parameters
[out]gradvthe computed velocity gradients !