[Tensian]

Dear all,

I have a question regarding porous media model in FLUENT. Well, to be fair, more than one question.

I would like to compute pressure drop in a filter in 3D(in the complete geometry and across the filter) using porous media approach in FLUENT. So I need permeability in order to obtain viscous resistance (porosity epsilon is available).

I have available the lineal velocity vs pressure drop curve (find attached the graph) for a type of coal.

I would like to carry out simulations of a filter based on this material. So I have used the pressure drop and velocity of this curves, and also the dynamic viscosity to obtain permeability via Darcy's law:

delta_P= (mu.U)/alpha where delta_P is pressure drop, mu is dynamic viscosity of the material (water in my case) , U is the velocity in the porous media and alpha is the permeability.

So, here are my questions:

1, For the computations:
For a T=25 ºC and lineal velocity of 12 m/h, pressure drop is about 3169 Pa/m, so if I have a porous media with length 0.998 m, then my delta_P=3169*0.998=3162.662 Pa.

I obtain U dividing flow rate by cross sectional area of the filter.

So, for the computation of permeability,should I use...

alpha=(lineal_velocity*dynamic viscosity)/deltaP per meter

or

alpha=(velocity obtained from flow rate and cross sectional area*dynamics viscosity)/(deltaP_per meter*length of porous media)

2. The most important thing. If I do...

surface integrals---Area weighted average---Pressure in the inlet plane of the porous media=Pin_porous
surface integrals---Area weighted average---Pressure in the outlet plane of the porous media=Pout_porous

delta_P_CFD=Pin_porous-Pout_porous

Then,

delta_P_CFD should be equal (or very similar) to deltaP_permeter*length of porous media????

I am not sure if I a m computing well permeability and I am worried about the way to use the curves attached to validate my FLUENT model.

Really interested in your comments. I am sure the most of you have already used something similar...

Thanks in advance,

Tensian