Spray Drying Technology.pdf - National University of Singapore

f
( X − X
eq
)
( X − X )
n
⎡ ⎤
= ⎢ ⎥ , X ≤ X
cr
⎢⎣
cr eq ⎥⎦
f = 1 , X > X
cr
On the other hand, the REA visualizes the drying process as an activation
process in which an ‘energy’ barrier has to be overcome for moisture removal
to occur [51] . The drying rate then takes the following form,
d m
dt
h
A
( k P ( T ) − P )
m
= −
v, sat d v,
∞
ms
(5)
The core of this model lies in modelling the fracitonality term, k , which should
progressively reduce as moisture is being removed. This fractionality is
expected to be a function of moisture and temperature, which can be
approximated by,
⎛ ∆EV
⎞
k = exp ⎜−
⎟
(6)
⎝ RT ⎠
where ∆E v is the apparent activation energy, which is likely to be dependent
on the ‘mean’ or ‘average’ moisture. The original authors proposed the
following function to be taken as the fingerprint of a material applicable to all
drying conditions,
∆E
∆E
v
v,
∞
= a e
−b
( X −X
) c
∞
(7)
At high moisture content
∆ E
∆ E
V
V , ∞
→ 0
, k →1
(8)
At low moisture content
∆ E
∆ E
V
V , ∞
→1
, 0 < minimal K value<
1
(9)
Application of the REA model in CFD simulations can be found [21][26][27] .
Good comparison was obtained with experimental data. A general
comparison between the two approaches, CDC and REA, can be found in the
review by Chen [52] . With application to CFD simulations, Woo et al. [27] further
showed that both approaches response differently to the initial droplet
moisture. It is important for the reader to assess these differences and
behaviour of the models when applying them in their CFD simulations.
Woo, Huang, Mujumdar, Daud – CFD modeling of spray dryers 15