Prediction of heat and mass transfer in canister filters
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Prediction of heat and mass transfer in canister filters. Tony Smith S & C Thermofluids Limited PHOENICS User Conference Melbourne 2004. Co-authors - Martin Smith, Dstl, Porton Down Kate Taylor, S & C Thermofluids. Overview. Introduction to S & C Thermofluids Canister filters

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Prediction of heat and mass transfer in canister filters

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Prediction of heat and mass transfer in canister filters

Prediction of heat and mass transfer in canister filters

Tony Smith

S & C Thermofluids Limited

PHOENICS User Conference

Melbourne 2004

Co-authors -

Martin Smith, Dstl, Porton Down

Kate Taylor, S & C Thermofluids


Overview

Overview

  • Introduction to S & C Thermofluids

  • Canister filters

  • Porous media modelling

  • Voidage distribution

  • Geometry

  • Pressure drop calculation

  • Adsorption

  • Results

  • Conclusion and recommendations


S c thermofluids

S & C Thermofluids

  • Formed in 1987

  • Research into fluid (gas/liquid) flow and heat transfer

  • Based in BATH, U.K.

www.thermofluids.co.uk


S c thermofluids1

S & C Thermofluids

Use combination of analysis (mainly CFD) and experimental validation and demonstration

RR Gnome engine test rig

CFD prediction of Gnome exhaust


Experimental facilities

Experimental facilities

  • RR Gnome turbojet and turboshaft engines

  • Universal jet flow rig

  • Water tunnel

  • JPX turbojet

  • Ejector performance test rig

  • Catalyst research engines


Cfd modelling

CFD modelling

  • External aerodynamics

  • Propulsion system (nozzle flows)

  • Exhaust plume mixing

  • Exhaust reactions

  • Interactions

  • Catalytic converters

  • Filters


From vacuum cleaners to supersonic aircraft

From vacuum cleaners to supersonic aircraft


From green houses to nuclear reactors

From green houses to nuclear reactors


From leaf blowers to rockets

From leaf blowers to rockets


Canister filters for respirators

Canister filters for respirators


Drivers for porous media modelling

Drivers for porous media modelling

  • Pressure drop

  • Flow distribution

  • Performance

    • Adsorption

    • Break-through

    • Conversion (reactions)

    • Minimise use of materials


Modelling approach

Modelling approach

Porous media such as catalytic converters and packed bed filters often contain very high surface areas which are difficult to represent in detail whilst modelling the bulk flowfield

Typical filter monolith


Modelling philosophy

Modelling philosophy

  • Continuum approach

    • macroscopic model of complete system

  • Single channel

    • detailed model of one flow path


Continuum methodology

Continuum methodology

  • Solving gas and solid (adsorbed) species separately but within the same computational space with mass transfer

  • Gas and solid energy can also solved separately with heat transfer

  • This methodology has been described in earlier papers relating to filter performance prediction


Canister geometry

Impregnated granular

activated carbon

Glass Fibre

Filter

Air Flow

Canister geometry


Voidage distribution in cylindrical filter beds

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


Voidage distribution

Voidage distribution

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


Geometry

Geometry

  • Canister key dimensions converted to FEMGEN geometry input

  • Mesh generated in FEMGEN

  • Output as PHOENICS 2D, axisymmetric BFC mesh using Phirefly

  • PHOENICS Q1 file written out


Voidage distribution canister

Voidage distribution - canister

  • Grid fixed by geometry

  • Voidage calculated locally according to modified Mueller equation

  • Voidage set in ground coding


Pressure drop

Pressure drop

  • Local voidage distribution coupled to Ergun-Orning equation for pressure loss through bed:

    Dp/L = 5 So2(1-e)2mU/e3 + 0.29 So(1-e)rU2/e3|| viscous loss turbulent loss

  • This pressure drop is applied to both axial and radial velocities

  • Earlier work using this equation have given rise to good agreement with experimental data for pressure drop.


Pressure drop1

Pressure drop

Flowrate 30l/min

Predicted pressure drop 275Pa

Measured pressure drop 110Pa

Filter paper section pressure drop 40Pa


Adsorption model

Adsorption model

  • Transient model to predict ‘breakthrough’

  • Steady state flowfield used as initial conditions

  • Adsorption rate source term:

    -¶C/¶t = 1/e So k (C - Ci)

  • Sh = 1.15 (Rep/e)0.5 Sc0.33 for Rep >1

  • Sh = k dp/D


Adsorption model1

Adsorption model

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

  • Maximum uptake from isotherm equation

  • Cumulative uptake is calculated :

    S ¶m/¶t. /¶t

  • Uptake value stored

  • Interface concentration Ci set to be in local equilibrium with uptake value


Velocity distribution

Velocity distribution


Predicted uptake of contaminant after 10 minutes

Predicted uptake of contaminant after 10 minutes


Conclusions

Conclusions

  • A CFD model of a canister filter has been produced

  • The model provides predictions of pressure drop, flow distribution and adsorption in transient conditions

  • The model uses PHOENICS as the main solver with additional ground coding for voidage distribution, pressure drop and adsorption


Conclusions 2

Conclusions (2)

  • FEMGEN is used to create the BFC grid for use in PHOENICS

  • Pressure drop predictions show some discrepancy with measurement – unlike earlier packed bed filter work

  • Early predictions of contaminant adsorption look realistic but require validation


Recommendations

Recommendations

  • Investigate pressure drop prediction discrepancies

  • Improve adsorption model

  • Include heat of adsorption

  • Provide axial variations of voidage

  • Modify aspects of canister model (eg gap at rear wall)

  • Provide full transient input of contaminant concentration as well as flowrate

  • Provide validation


Acknowledgements

Acknowledgements

  • Martin Smith, Dstl, Porton Down

  • Kate Taylor, S & C Thermofluids


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