Fundamentals of turbulence modeling

RANS models II

Andre Weiner, Institute of Fluid Mechanics

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Outline

  • RANS model overview
  • $k$-$\varepsilon$ model
  • $k$-$\omega$ model
  • $k$-$\omega$-SST model

RANS model overview

model categories

  1. eddy viscosity models
    1. linear, algebraic
    2. linear, PDE-based
    3. non-linear, PDE-based
  2. stress models
    1. algebraic (3 PDEs)
    2. Reynolds stresses (7 PDEs)

historical perspective II

$k$-$\varepsilon$ model

transport equation of (specific) turbulence kinetic energy

  1. trace of Reynolds stress transport equation
  2. multiplication of Navier-Stokes and RANS equations and with velocity fluctuations; summation of components; subtraction; rearrangement

starting point

$$\nu_t \propto l_c u_c$$

velocity scale $u_c = k^{0.5}$

length scale $l_c = k^{1.5}/\varepsilon$

$\rightarrow \nu_t = C_\mu k^2/\varepsilon$

additional modeling

  • $k$ equation terms
  • $\varepsilon$ transport equations and terms

boundary conditions (high $Re$)

  • $\nu_t$ - log-law, Spalding's function
  • $k$ - zero gradient ($\nabla k \cdot \mathbf{n}=0$)
  • $\varepsilon$ - fixed value ($\varepsilon_{log} = C_\mu k^{1.5}/\nu_t$)

inlet conditions

  • ideally from experiments
  • estimate $k = 1.5 (IU_{in})^2$
  • estimate $\varepsilon = C_\mu^{0.75}k^{1.5}/l_c$

favorable attributes

  • simple and numerically robust
  • only free stream conditions needed
  • good accuracy in many cases
  • extensively validated

bad performance in certain flows

  • flows in which wall functions are not applicable
  • unconfined flows (jet)
  • flows with large extra strain (curved boundaries, swirls - think tornados)
  • rotating flows (fans, turbo machinery)
  • flows driven by anisotropy of Reynolds stresses (fully developed flows in square duct)

$k$-$\omega$ model

starting point

$$\nu_t \propto l_c u_c$$

velocity scale $u_c = k^{0.5}$

turbulence frequency $\omega = \varepsilon / k$

length scale $l_c = k^{0.5}/\omega$

$\rightarrow \nu_t = k/\omega$

favorable attributes

  • similar to $k$-$\varepsilon$ model
  • integration of wall layer possible

unfavorable attributes

  • similar weaknesses as $k$-$\varepsilon$ model
  • sensitivity to free stream values

$k$-$\omega$-SST model

starting point $\nu_t = k/\omega$

observation: plugging definition of $\varepsilon = k\omega$ into transport equation of $\varepsilon$ yields $\omega$ transport equation with additional terms

idea: combine favorable attributes of both models

favorable attributes

  • combines the best of $k$-$\varepsilon$ and $k$-$\omega$ models
  • very well validated

$\rightarrow$ default model of most practitioners

unfavorable attributes in certain flows remain

summary

  • based on mixing length idea
  • mostly empirical modeling of transport equations
  • many weaknesses related to assumption of isotropic eddy viscosity
  • many variants exist $\rightarrow$ check implementation and/or documentation before usage