CFD MODELLING OF PRESSURE DROP AND FLOW DISTRIBUTION

IN PACKED BED FILTERS

K Taylor & AG Smith - S&C Thermofluids Ltd

S Ross & MW Smith - DERA Porton Down

OVERVIEW

• Packed bed filters remove toxic agents from contaminated airstreams

• CFD potential design tool for predicting the flow and pressure drop

• Mathematical model for predicting radial voidage distribution in bed

• Non-uniform voidage distribution included in CFD model • Validated against measurements of pressure drop and

velocity distribution• Potential for CFD modelling of adsorption process also

investigated

GEOMETRY OF FILTER BED

VOIDAGE DISTRIBUTION IN CYLINDRICAL FILTER BEDS

• Radial voidage distribution in ‘snowstorm’ packed filter beds is a function of the ratio: particle size/bed diameter

• Affects the velocity distribution within the filter bed

• Measurements made of voidage distribution for range of particle sizes

• Fitted to modified ‘Mueller’ model

Radial voidage distribution - 4mm beads

0

0.2

0.4

0.6

0.8

1

1.2

0

1.96

3.92

5.88

7.84 9.

8

11.8

13.7

15.7

17.6

19.6

21.6

23.5

26.5

30.4

34.3

38.2

42.1

46.1

distance from the edge of the bed (mm)

Void

age

= b + (1-b)e-brJo(ar*)

GEOMETRY OF FILTER BED

CFD MODEL

• 2-d axi-symmetric BFC model• Grid distribution determined from voidage distribution

to ensure adequate grid resolution near walls• Local voidage distribution coupled to Ergun-Orning

equation for pressure loss through bed:

p/L = 5 So2(1-)2U/3 + 0.29 So(1-

)U2/3 |

| viscous loss

turbulent loss

• Substantial improvement in predictions compared to model using average voidage

PRESSURE DROP - 3mm PARTICLES

predicted and measured pressure drops - comparison of uniform voidage and modified Mueller model

0

1000

2000

3000

4000

5000

6000

7000

0 1 2 3 4 5 6 7 8 9 10

inlet centreline velocity (m/s)

Pre

ss

ure

dro

p (

Pa

)

exp data CFD data - uniform voidage CFD data - Mueller model

PRESSURE DROP VS GRID DENSITY

predicted and measured pressure dropsfor a 20cm cone

0

1000

2000

3000

4000

5000

6000

7000

8000

0 1 2 3 4 5 6 7 8 9 10inlet centreline velocity (m/s)

pre

ssu

re d

rop

(P

a)

exp data - 2mm bead exp data -3mm bead exp data -4mm beadcfd data - 2mm bead cfd dat - 3mm bead cfd data - 4mm beadcfd fine data- 2mm bead cfd fine data- 3mm bead cfd fine data- 4mm bead

VELOCITY DISTRIBUTIONS

predicted and measured velocity profiles - 2-layer modelcentreline velocity 4m/s, 3mm bead and 20cm cone

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0.000 0.005 0.010 0.015 0.020 0.025 0.030 0.035 0.040 0.045 0.050radius (m)

velo

city

(m

/s)

exp data - u/s velocity profile exp data - d/s velocity profilecfd data- u/s velocity profile - k-e model cfd data- d/s velocity profile - k-e modelcfd data- u/s velocity profile- 2-layer model cfd data- d/s velocity profile- 2-layer model

ADSORPTION MODEL

• Transient model to predict ‘breakthrough’• Steady state flowfield used as initial conditions• Adsorption rate source term:

-C/t = 1/ So k (C - Ci)

• Rate of uptake in adsorbent: m/t = /(1-) (-C/t)/z

• Maximum uptake from isotherm equation:mmax = a.b.RH/(1 - RH)

VAPOUR UPTAKE IN FILTER BED

VAPOUR PENETRATION

IMPLEMENTATION WITHIN PHOENICS

• Pre-processor - interprets voidage distribution and basic input parameters - outputs Q1 file

• Additional Q1 commands for adsorption model• GROUND coding for -

porosity from voidage distributioninlet boundary conditions

source terms for pressure loss and

adsorption rate

CONCLUDING REMARKS

• Method for prediction of pressure and flow distribution validated for range of parameters

• Implemented within PHOENICS user routines• Potential for adsorption model demonstrated• Areas for further work:

improvement and validation of asdorption model improved user interface

turbulence modelling within the filter bed