modelling drying and particle formation in spray towers

vapour bubble formation

water removed by evaporation

‘blown shell’

modelling drying and particle formation in spray towers

Christopher Handscomb

Wednesday 9th May 2007

Christopher Handscomb(csh33@cam.ac.uk)

outline

• Introduction to spray drying

• Modelling approach

• Continuous phase gas flow

• Single particle drying

• Conclusions and further work

Christopher Handscomb(csh33@cam.ac.uk)

• An important technology in industry

• Used to produce, for example:– Pharmaceuticals– Food stuffs (e.g. milk powder and coffee)– Detergents

• Unique drying technology combining moisture removal and particle formation

what is spray drying?

Christopher Handscomb(csh33@cam.ac.uk)

what is spray drying?

Feed

Atomisation

rotary atomizer pressure nozzle

Spray-Air Contact

co-current mixedcounter-current

Spray EvaporationPowder

Separation

product discharge from chamber and

separation unit

total product discharge from separation unit

Christopher Handscomb(csh33@cam.ac.uk)

motivation

A computational model would…

• predict the effect of process conditions on final product properties

• guide the operator towards safe and efficient operating conditions

• facilitate the design of new plant based on physics, rather than correlations

Christopher Handscomb(csh33@cam.ac.uk)

modelling approach

Co

nti

nu

ou

s P

ha

se

(C

FD

)Sub Models

Particle Drying

Particle-Particle Interaction

Particle-Wall Interaction

• Adopt an Eulerian-Lagrangian framework

Christopher Handscomb(csh33@cam.ac.uk)

continuous phase

• Commercial CFD package – STAR CD – used to model the continuous phase– Well known in industry– Easy to test different geometries– Relatively simple to incorporate sophisticated

user defined sub models

• Test geometry developed representing a generic spray dryer

• Counter current dryer• Single spray nozzle• Height: 22m• Diameter: 4m• 118,807 cells in CFD mesh

Christopher Handscomb(csh33@cam.ac.uk)

continuous phase

• Can fairly easily produce plots of the flow field

z=0.5m

z= 4m

• Consider a single droplet

Christopher Handscomb(csh33@cam.ac.uk)

• Consider the drying sub-model

• Modelling assumptions:– Three component system:

A – solvent; B – solute; D – solid

– Spherical particles, 1D model– Small Biot number uniform particle temperature– Allow for a single centrally located bubble

single particle drying

Assumed ideal binary solution

time

drop

let t

empe

ratu

re

Christopher Handscomb(csh33@cam.ac.uk)

time

drop

let t

empe

ratu

resingle particle drying

wet bulb temperature

boiling temperature

Cheyne, A., Wilson, I., and Bridgewater, J. (2002).

Christopher Handscomb(csh33@cam.ac.uk)

single particle drying

• Spherical symmetry reduce to 1-D

• Solve for the moments of this equation

internal coordinates external coordinates

advection terms diffusion terms source term

• Population balance for solids

Cheyne, A., Wilson, I., and Bridgewater, J. (2002).

Christopher Handscomb(csh33@cam.ac.uk)

single particle drying

• Variable of interest is solids volume fraction

• Related to the moments of the population balance equation by:

• Obtained by solving the moment system:

assumed independent of internal coordinate (particle size)

Christopher Handscomb(csh33@cam.ac.uk)

evolution advection diffusion crystallization

single particle drying

• Volume averaged transport equations for the continuous phase

• Advection velocity calculated from volume conservation considerations

• Diffusion coefficient from measurements

Volume AveragesSuperficial

Intrinsic

Total

R(c)

S

z

Christopher Handscomb(csh33@cam.ac.uk)

single particle drying

• Population balance boundary conditions

• Solute boundary conditions

Christopher Handscomb(csh33@cam.ac.uk)

moving boundary

• Moving boundary handled through a standard coordinate transformation r z:

• This adds a ‘virtual flux’ to all equations

virtual flux

Christopher Handscomb(csh33@cam.ac.uk)

solution method

• Problem is a system of PDEs

and coupled ODEs

• Solved using Numerical Algorithms Group (NAG) library routines for convection-diffusion type equations

• Finite Volume approach with user-defined flux function

Christopher Handscomb(csh33@cam.ac.uk)

new drying model – example

• Model described so far can simulate

up to the point of shell formation

• e.g. Consider a system:– Initial 14wt% sodium sulphate solution – no solids– Crystallisation model from Rosenblatt et al. (1984):

‘Kinetics of Phase Transitions in the System Sodium Sulphate-Water’

– Droplet diameter = 1.78mm– Drying air T = 373K– Droplets initially well mixed

Christopher Handscomb(csh33@cam.ac.uk)

new drying model – example

0 20 40 60 80 100 1200

0.5

1

1.5

2

2.5

3

3.5Simulated vs. Experimental Mass of the Drying Droplet

Time/s

Dro

plet

Mas

s/m

g

Experiment

Model

• Compare with experimental data from Nesic and Vodnik (1990) Kinetics of Droplet Evaporation Chem. Eng. Sci.

Experimental data from Nesic and Vodnik (1990) Kinetics of Droplet Evaporation Chem. Eng. Sci.

Christopher Handscomb(csh33@cam.ac.uk)

new drying model – example

0 20 40 60 80 100 12020

30

40

50

60

70

80

90

100

110Simulated vs. Experimental Temperature of the Drying Droplet

Time/s

Dro

plet

Tem

pera

ture

/C

Experiment

Model

Experimental data from Nesic and Vodnik (1990) Kinetics of Droplet Evaporation Chem. Eng. Sci.

But the new model can give us much more…

Christopher Handscomb(csh33@cam.ac.uk)

new drying model – example

0 20 40 60 80 100 1200

0.5

1

1.5

2

2.5

3Simulated Evolution of the Solvent, Solute and Solids Masses

Time/s

Mas

s/m

g

Solvent Mass

Solute MassSolids Mass

Christopher Handscomb(csh33@cam.ac.uk)

new drying model – example

0 1 2 3 4 5 6 7 8

x 10-4

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1Simulated Continuous Phase Solvent Mass Fraction in a Drying Droplet

Radial Position/mm

Sol

ute

Mas

s F

ract

ion

[-]

Christopher Handscomb(csh33@cam.ac.uk)

new drying model – example

0 1 2 3 4 5 6 7 8

x 10-4

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7Simulated Solids Volume Fraction in a Drying Droplet

Radial Position/mm

Sol

ids

Vol

ume

Fra

ctio

n [-

]

Christopher Handscomb(csh33@cam.ac.uk)

new drying model – example

0 20 40 60 80 100 1200

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2x 10

-5Simulated Evolution of moments integrated over the drying droplet

Time/s

Inte

grat

ed N

orm

alis

ed M

omen

tsZeroth Moment

First MomentSecond Moment

Christopher Handscomb(csh33@cam.ac.uk)

conclusions…

• Introduction to spray drying and the associated modelling challenges

• Results of continuous phase simulation

• Overview of a new drying model

• Comparison with experiments for a ‘simple’ case…

Christopher Handscomb(csh33@cam.ac.uk)

…work not shown…

• Drying after shell formation

• Simulation of detergent droplets drying with experimental comparison

• Simplified drying models implemented in CFD code

Christopher Handscomb(csh33@cam.ac.uk)

…and further work

• Obtain data and validate model for high temperature drying

• Couple (simplified) model to CFD simulation

• Compare with existing drying models when used in CFD

Christopher Handscomb(csh33@cam.ac.uk)

acknowledgements