Theory for Turbulence in Porous Media
Since Darcian flow is not compatible with the character of a turbulent flow, only Non-Darcian flow is available in Porous Medium domains as a Flow model option when a two-equation turbulence model is activated. The turbulence equations are fully active in a Porous Medium and are modified according to the theory below. Currently, the algebraic turbulence models do not change the formulation of the momentum equation in porous domains and the Spalart-Allmaras model prohibits them.
averaging in porous media
A detailed description of turbulence in porous media can, in principle, be achieved by employing common turbulence modeling in the corresponding complex geometries. However, heavy computations would be needed when a characteristic size of the porous matrix cavities, or pores, is much smaller than the geometry dimensions. A characteristic size of the pores, the porous length scale, is given by , where κ and εp are the medium’s permeability and porosity, respectively. For this reason, a simplified framework for turbulence modeling in porous media has been developed. It is based on taking the turbulence equations in the interstitial space and averaging them over the whole combined volume of fluid and porous matrix (Ref. 30), a so called Representative Elementary Volume (REV). In such a way a detailed information about gradients of velocity and other quantities on the lpore-scale is not available, but its influence is modeled by introducing extra terms which depend on the REV-smoothed quantities.
For example, the averaging (or REV-smoothing) rule for the mean velocity is
(3-169)
Here is Reynolds-averaged microscopic velocity, ΔV is the REV-cell volume (large enough to guarantee sufficient smoothing, but not larger than a fraction of the mean gradient scale) while ΔVf is the fluid part of the REV-cell, u is the REV-averaged mean velocity (mean Darcy velocity, or volume flow velocity, essentially) and ui is the REV-averaged mean interstitial velocity. Note that for all our purposes it is sufficient to define ui as ui = up. For the velocity gradients we assume
(3-170)
where deviations from this expression (Ref. 30) are lumped into the modeled extra contributions. Turbulence kinetic energy and turbulence dissipation rate obey the same averaging and scaling rules as mean velocity
(3-171)
At the same time, for turbulence specific dissipation rate and turbulence viscosity we take by definition
(3-172)
This happens because ω and μT do not have a reasonable volumetrically spread interpretation. Next, turbulence friction velocity is scaled by definition as
(3-173)
because this is consistent with common scalings and .
Pressure entering the equations is REV-smoothed pressure,
(3-174)
and preserves the gauge invariance property.
The set of equations
The momentum equation is essentially a Brinkman equation for the mean REV-averaged velocity but the viscous stress now includes turbulence viscosity:
(3-175)
The formal modification of the k-equation involves changing convective term as and adding production by the porous matrix Pk,pm to the shear production Pk → Pk + Pk,pm
(3-176)
while the shear production is modified as
(3-177)
For ε−equation the changes are completely analogous: convective term is modified according to and turbulent dissipation rate production by the porous matrix Pε,pm is added to the right-hand side
(3-178)
For ω-based models the convective term changes as and turbulent specific dissipation rate production by the porous matrix is added Pω,pm
(3-179)
The above modifications have been illustrated for the k-ε model and ω-equation of the k-ω model, but are generally applicable to any two-equation turbulence model.
Calculation of turbulent viscosity via assumes that the following scaling should be applied
(3-180)
or
(3-181)
The realizable k-ε model needs redefinition .
For the Low Reynolds number k-ε model .
For the k-ω model . Analogously,
modifications to coefficients of the SST model require substitution k → kp.
The modifications to the ζ-equation of the v2-f model are the following: change convective term as , change Pk → Pk + Pk,pm in both terms on the right-hand side which contain Pk, and limit variable L by lpore
(3-182)
Wall Distance is now computed treating Wall and Interior wall adjacent to porous domains as usual solid walls.
Porous medium turbulence model
Porous medium turbulence model complements a basic turbulence model providing modeling for the above declared terms Pk,pm and Pε,pm, and Pω,pm. The available modeling approaches are: Default, Nakayama–Kuwahara, and Pedras–de Lemos. Default and Nakayama–Kuwahara (Ref. 31) employ the following form of the porous production Pk,pm of turbulence kinetic energy
(3-183)
(where β is the non-Darcian coefficient from the Brinkman equation) while Pedras-de Lemos (Ref. 30) relies on
(3-184)
For ε-based equations, Default and Pedras-de Lemos model the turbulence dissipation rate Pε,pm as
(3-185)
while Nakayama–Kuwahara gives
(3-186)
For the k-ω and SST models, Default and Pedras–de Lemos model porous production of the specific turbulent dissipation rate Pω,pm as
(3-187)
while Nakayama–Kuwahara as
(3-188)
For ε-based models Cε2,pm is always the corresponding Cε2 coefficient entering ε-equation (that is for v2-f ). Default and Pedras-de Lemos have for k-ω and for SST, while Nakayama–Kuwahara has for k-ω and for SST.
Essentially, Default uses Pk,pm in the form proposed by Nakayama–Kuwahara and Pε,pm or Pω,pm in the form proposed by Pedras–de Lemos. Since ρβ|u|3 essentially is turbulence dissipation in the porous matrix, Default and Nakayama–Kuwahara are conservative models so that the k-equation guarantees that in a dense porous medium the specific turbulence dissipation achieves its limiting value
(3-189)
The ε-equation, and ω-equation, of all the three models as well as the k-equation of Pedras-de Lemos ensure that the turbulence frequency in a dense porous matrix would approach its limiting value
(3-190)
Thus, Default and Nakayama–Kuwahara also ensure that in a dense porous matrix
(3-191)
However, Pedras–de Lemos then becomes a degenerate model with two identical equations, and the limiting values of k and ε might depend on the initial and boundary conditions in an uncontrollable way.
The coefficient Cstpm, which we call a Coefficient of subgrid turbulence generation by porous matrix, is equal to 0.212 by default as given in Ref. 31. However for Pedras-de Lemos it can be set to predefined Original value or Recalibrated value 0.18. Both are based using Equation 3-190 to match limiting values of ε/k, obtained using pore resolving simulations in dense porous matrix at different εp, with Cstpm. Original refers to Ref. 30 usage while Recalibrated refers to the current convention when Cstpm is considered as independent of porosity.
Wall treatment
Wall treatment essentially inherits wall treatment of a corresponding basic turbulence model. The main modification is due to the need to determine if at δw = hw/2 the turbulent log-layer still dominates (pores are resolved) or the limit of the dense porous matrix is reached (pores not resolved). The intermediate cases should be blended properly. In the current approach it is achieved by introducing an indicator function indpmLL,which quantifies porous matrix dominance over the log-layer and is modeled as
(3-192)
Thus, at the wall (or rather the lift-off position) a variable (like traction, turbulence dissipation rate or turbulence specific dissipation rate) is determined as
(3-193)
where and are log-layer and dense porous matrix expressions, respectively.
Formally, the non-porous flow expression for traction should be multiplied by because traction in the porous matrix is negligible due to homogenization of the gradients.
Wall Functions
The modifications are:
(3-194)
where for the Realizable k-ε and for k-ω (also in expressions below), while expression for the friction velocity uτ is the same, and the traction is
(3-195)
The wall value of ε is now
(3-196)
representing blending of a log-layer value with a dense porous matrix value. The analogous expression for ω is:
(3-197)
and also models transition from an asymptotic log-layer asymptotic to the dense porous matrix value.
Automatic Wall Treatment
Now uτlog and δw+ are modified as
(3-198)
while the definitions of uτvisc, u∗, log, uτ, and u remain the same.
The traction is written as
(3-199)
For the Low-Reynolds Number model further modifications are
(3-200)
(3-201)
For v2-f model the further modifications are
(3-202)
(3-203)
For k-ω and SST models ωvisc does not change and the further modifications are
(3-204)
(3-205)
Low-Re Wall Treatment
Low Reynolds number treatment is formally identical to the usual clear flow Low Re treatment. Strictly speaking, it is applicable only in case if the pore cell is fully resolved by the mesh. Otherwise the first computational cell is in the porous matrix but common clear flow conditions are applied. Thus, the behavior in several near-wall cells would be not correct.
Buoyancy-induced turbulence
The two definitions of the production of turbulence kinetic energy by buoyancy, User defined and Automatic from multiphysics, become modified in porous domains as
(3-206)
Since , so
(3-207)
A general remark on scaling with porosity
All the equations in porous medium presented above can be rewritten in terms of the mean interstitial quantities . If we assume constant εp and multiply k-equation and ε-equation by εp, then porosity εp would disappear from all the equations and they would look identical to the original clear flow equations. The additional terms (Darcy and Forchheimer in the momentum equation, and the above introduced extra productions in the turbulence equations) would contain the geometrical information about porous medium only via lpore. This reasoning is naturally extended to all the boundary conditions. Also, all the numerous non-dimensional intermediate variables which enter turbulence equations, for example Rt in the Low-Re k-ε model, should be scaled properly. Then, since scaling does not effect length and time, all the intermediate lengths, frequencies and viscosities should be physical.
For example, the Burke–Plummer model follows this rule, while an approach introducing Forchheimer coefficient is consistent if the scaling
(3-208)
is assumed with being considered as a constant.