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Rahman-Siikonen-Agarwal Model

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== Introduction ==
== Introduction ==
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The Rahman-Agarwal-Siikonen (RAS) Turbulence model is a one-equation eddy viscosity model based on <math>k-\epsilon</math> closure.  The R-transport equation along with the Bradshaw and other empirical relations are used to solve for the turbulent viscosity.  A damping function, <math>f_\mu</math>, is used to represent the kinematic blocking by the wall. To avoid defining a wall distance, a Helmholtz-type elliptic relaxation equation is used for <math>f_\mu</math>. The model has been validated against a few well-documented flow cases, yielding predictions in good agreement with DNS and experimental data.
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The Rahman-Siikonen-Agarwal (RSA) Turbulence model is a one-equation eddy viscosity model based on <math>k-\epsilon</math> closure.  The R-transport equation along with the Bradshaw and other empirical relations are used to solve for the turbulent viscosity.  A damping function, <math>f_\mu</math>, is used to represent the kinematic blocking by the wall. To avoid defining a wall distance, a Helmholtz-type elliptic relaxation equation is used for <math>f_\mu</math>. The model has been validated against a few well-documented flow cases, yielding predictions in good agreement with DNS and experimental data.
== RAS Model ==
== RAS Model ==
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The turbulent eddy viscosity is given by
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'''The turbulent eddy viscosity is given by'''
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:<math>
:<math>
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</math>
</math>
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The R-transport equation is
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'''The R-transport Equation:'''
:<math>
:<math>
\begin{matrix}
\begin{matrix}
-
\frac{\partial \rho R}{\partial t} + \frac{\partial \rho u_j R}{\partial x_j} & = & \frac{\partial}{\partial x_j} [ (\mu +\frac{\mu_t}{\sigma})\frac{\partial R}{\partial x_j} ] +C_1 \rho \sqrt{P \tilde{R}} - C_2 \rho (\frac{\partial \tilde{R}}{\partial x_k})^2  
+
\frac{\partial \rho R}{\partial t} + \frac{\partial \rho u_j R}{\partial x_j} = \frac{\partial}{\partial x_j} \biggl[ \left(\mu +\frac{\mu_t}{\sigma}\right)\frac{\partial R}{\partial x_j} \biggr] +C_1 \rho \sqrt{P \tilde{R}} - C_2 \rho \left(\frac{\partial \tilde{R}}{\partial x_k}\right)^2  
\end{matrix}
\end{matrix}
</math>
</math>
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 +
 +
'''Realizable Time Scale:'''
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 +
:<math>
 +
T_t = \frac{k}{\epsilon} \sqrt{1+\frac{C_t^2}{Re_T}}, \quad Re_T = \frac{k^2}{\nu \epsilon}
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</math>
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 +
 +
'''Coefficient <math>C_\mu</math>:'''
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 +
:<math>
 +
C_\mu = \frac{3(1+\eta^2)\alpha_1}{3+\eta^2+6\eta^2\xi^2+6\xi^2}
 +
</math>
 +
 +
:<math>
 +
\eta = \alpha_2 T_t S, \quad \xi = \alpha_3 T_t W
 +
</math>
 +
 +
:<math>
 +
\alpha_1 = g\left(\frac{1}{4}+\frac{2}{3}\Pi_b^{1/2}\right), \quad \alpha_2 = \frac{3}{8\sqrt{2}}g
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</math>
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:<math>
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\alpha_3 = \frac{3}{\sqrt{2}}\alpha_2, \quad g = \left( 1+2\frac{P}{\epsilon} \right) ^{-1}
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</math>
 +
 +
:<math>
 +
\Pi_b = C_\nu \frac{P}{\epsilon}, \quad \frac{P}{\epsilon} = C_\nu \zeta^2
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</math>
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:<math>
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C_\nu = \frac{1}{2(1+T_t S \sqrt{1+\Re^2})}, \quad \zeta = T_t S max(1,\Re)
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</math>
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:<math>
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S_{ij} = \frac{1}{2}\left(\frac{\partial u_i}{\partial x_j} + \frac{\partial u_j}{\partial x_i}\right), \quad S = \sqrt{2S_{ij} S_{ij}}
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</math>
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 +
:<math>
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W_{ij} = \frac{1}{2}\left(\frac{\partial u_i}{\partial x_j} - \frac{\partial u_j}{\partial x_i}\right), \quad W = \sqrt{2S_{ij} S_{ij}}
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</math>
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 +
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'''Damping Function:'''
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 +
:<math>
 +
-L^2 \nabla^2f_\mu + f_\mu = 1
 +
</math>
 +
 +
:<math>
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L^2 = \zeta(2\zeta+C_\mu Re_T)\sqrt{\frac{\nu^3}{\epsilon}}, \quad (f_\mu)_{wall} = 0
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</math>
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'''Other Model Coefficients:'''
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 +
:<math>
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C_1 = 2C_\mu \zeta (1-C_\mu \zeta), \quad C_2 = min \Biggl[ 2C_\mu,\; \tilde{C}_\mu \sqrt{1+\left( \frac{C_1}{6 \tilde{C}_\mu}\right)^2}\;\Biggr]
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</math>
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:<math>
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\sigma = C_\mu + \frac{f_\mu}{C_T}
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</math>
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'''<math>k</math> and <math>\epsilon</math>:'''
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:<math>
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k = \sqrt{\tilde{k}^2 + k_\alpha ^2}
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</math>
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:<math>
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\tilde{k} = f_\mu^{0.8}\sqrt{C_\mu}R S_k, \quad k_\alpha = \nu S_\alpha
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</math>
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 +
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:<math>
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\epsilon = \sqrt{\epsilon_w^2+\tilde{\epsilon}^2+\epsilon_\alpha^2}
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</math>
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:<math>
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\tilde{\epsilon} = \frac{k^2}{R+\nu}, \quad \epsilon_\alpha = \nu S_\alpha^2, \quad \epsilon_w=2A_\epsilon\nu(\frac{\partial u}{\partial y})_w^2\approx 2A_\epsilon \nu S_k^2
 +
</math>
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 +
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:<math>
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S_k = \sqrt{\tilde{S}^2+S_\alpha^2},
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</math>
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:<math>
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\tilde{S} = f_k\left(S-\frac{\vert\eta_1\vert - \eta_1}{C_T}\right), \quad \eta_1 = S-W, \quad f_k=1-\frac{f_\alpha}{C_T}\sqrt{max(1-\Re,0)}
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</math>
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:<math>
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S_\alpha = \frac{2C_\alpha f_\alpha}{3\nu}\left(\frac{\sqrt{u_i^2/2}}{1+\mu_T/\mu}\right)^2, \quad C_\alpha=\sqrt{C_\mu^2+\frac{\nu}{R+\nu}}, \quad f_\alpha = 1 - exp\left(-\frac{\mu_T}{36\mu}\right)
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</math>
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'''Constants:'''
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:<math>
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C_T = \sqrt{2}, \quad \tilde{C}_\mu = 0.09
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</math>
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:<math>
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0.05\;<\;A_\epsilon\;<\;0.11 \quad Commonly \;A_\epsilon = \tilde{C}_\mu
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</math>
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==References ==
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 +
* {{reference-paper|author=Rahman, M. M., Siikonen, T., and Agarwal, R. K.|year=2011|title=Improved Low Re-Number One-Equation Turbulence Model|rest=AIAA Vol. 49, No.4, April 2011}}
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[[Category:Turbulence models]]

Revision as of 00:11, 18 August 2012

Introduction

The Rahman-Siikonen-Agarwal (RSA) Turbulence model is a one-equation eddy viscosity model based on k-\epsilon closure. The R-transport equation along with the Bradshaw and other empirical relations are used to solve for the turbulent viscosity. A damping function, f_\mu, is used to represent the kinematic blocking by the wall. To avoid defining a wall distance, a Helmholtz-type elliptic relaxation equation is used for f_\mu. The model has been validated against a few well-documented flow cases, yielding predictions in good agreement with DNS and experimental data.

RAS Model

The turbulent eddy viscosity is given by



\mu_t = C_\mu f_\mu \rho \tilde{R} = C_\mu f_\mu \rho k T_t


The R-transport Equation:


\begin{matrix}
\frac{\partial \rho R}{\partial t} + \frac{\partial \rho u_j R}{\partial x_j} = \frac{\partial}{\partial x_j} \biggl[ \left(\mu +\frac{\mu_t}{\sigma}\right)\frac{\partial R}{\partial x_j} \biggr] +C_1 \rho \sqrt{P \tilde{R}} - C_2 \rho \left(\frac{\partial \tilde{R}}{\partial x_k}\right)^2 
\end{matrix}


Realizable Time Scale:


T_t = \frac{k}{\epsilon} \sqrt{1+\frac{C_t^2}{Re_T}}, \quad Re_T = \frac{k^2}{\nu \epsilon}


Coefficient C_\mu:


C_\mu = \frac{3(1+\eta^2)\alpha_1}{3+\eta^2+6\eta^2\xi^2+6\xi^2}

\eta = \alpha_2 T_t S, \quad \xi = \alpha_3 T_t W

\alpha_1 = g\left(\frac{1}{4}+\frac{2}{3}\Pi_b^{1/2}\right), \quad \alpha_2 = \frac{3}{8\sqrt{2}}g

\alpha_3 = \frac{3}{\sqrt{2}}\alpha_2, \quad g = \left( 1+2\frac{P}{\epsilon} \right) ^{-1}

\Pi_b = C_\nu \frac{P}{\epsilon}, \quad \frac{P}{\epsilon} = C_\nu \zeta^2

C_\nu = \frac{1}{2(1+T_t S \sqrt{1+\Re^2})}, \quad \zeta = T_t S max(1,\Re)

S_{ij} = \frac{1}{2}\left(\frac{\partial u_i}{\partial x_j} + \frac{\partial u_j}{\partial x_i}\right), \quad S = \sqrt{2S_{ij} S_{ij}}

W_{ij} = \frac{1}{2}\left(\frac{\partial u_i}{\partial x_j} - \frac{\partial u_j}{\partial x_i}\right), \quad W = \sqrt{2S_{ij} S_{ij}}


Damping Function:


-L^2 \nabla^2f_\mu + f_\mu = 1

L^2 = \zeta(2\zeta+C_\mu Re_T)\sqrt{\frac{\nu^3}{\epsilon}}, \quad (f_\mu)_{wall} = 0


Other Model Coefficients:


C_1 = 2C_\mu \zeta (1-C_\mu \zeta), \quad C_2 = min \Biggl[ 2C_\mu,\; \tilde{C}_\mu \sqrt{1+\left( \frac{C_1}{6 \tilde{C}_\mu}\right)^2}\;\Biggr]

\sigma = C_\mu + \frac{f_\mu}{C_T}


k and \epsilon:


k = \sqrt{\tilde{k}^2 + k_\alpha ^2}

\tilde{k} = f_\mu^{0.8}\sqrt{C_\mu}R S_k, \quad k_\alpha = \nu S_\alpha



\epsilon = \sqrt{\epsilon_w^2+\tilde{\epsilon}^2+\epsilon_\alpha^2}

\tilde{\epsilon} = \frac{k^2}{R+\nu}, \quad \epsilon_\alpha = \nu S_\alpha^2, \quad \epsilon_w=2A_\epsilon\nu(\frac{\partial u}{\partial y})_w^2\approx 2A_\epsilon \nu S_k^2



S_k = \sqrt{\tilde{S}^2+S_\alpha^2},

\tilde{S} = f_k\left(S-\frac{\vert\eta_1\vert - \eta_1}{C_T}\right), \quad \eta_1 = S-W, \quad f_k=1-\frac{f_\alpha}{C_T}\sqrt{max(1-\Re,0)}

S_\alpha = \frac{2C_\alpha f_\alpha}{3\nu}\left(\frac{\sqrt{u_i^2/2}}{1+\mu_T/\mu}\right)^2, \quad C_\alpha=\sqrt{C_\mu^2+\frac{\nu}{R+\nu}}, \quad f_\alpha = 1 - exp\left(-\frac{\mu_T}{36\mu}\right)

Constants:


C_T = \sqrt{2}, \quad \tilde{C}_\mu = 0.09

0.05\;<\;A_\epsilon\;<\;0.11 \quad Commonly \;A_\epsilon = \tilde{C}_\mu


References

  • Rahman, M. M., Siikonen, T., and Agarwal, R. K. (2011), "Improved Low Re-Number One-Equation Turbulence Model", AIAA Vol. 49, No.4, April 2011.
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