Chemical Engineering December 2014 - 51

Solids Processing
Solids Handling:
Using Flowsheet
Simulation to Improve
Process Design
This tool provides advantages when it comes to modeling
operations involving granular solids
Jennifer Dyment and Claus Reimers
Aspen Technology
U
sing flowsheet simulation
to model processes
involving granular solids
- either those that are
entirely separate from fluid processes
or those that are combined
with them - has many advantages
for improving the process design.
These include avoiding unplanned
downtime, reducing costs, improving
throughput and maintaining
product quality.
Modeling processes that involve
solids adds an extra level of complexity
to process simulation, as it
requires the consideration of distributed
properties, such as particle-size
distribution (PSD). Granular
solids are described this way,
whereas fluid processes are generally
described using concentrated
properties, such as vapor fraction,
composition, temperature and so
on. Additionally, many other parameters
that describe the particles
depend on the particle size. For instance,
when particles are being
dried, the moisture content inside
a particle may be higher for larger
particles than for smaller particles,
thus moisture content is also a distributed
parameter in this case.
10
7.60
Solution
Crystal
S1
S4
Decanter
Crystallization
0.63
S8
48
0.94
Crystals
48
S6
0.94
48
0.94
S9
B7
11
0.63
49
0.94
S23
160
1.75
55
0.82
Recycle
Screen2
Product
49
2.98
Cyclone
Press
104
0.87
Screen
50
1.35
56
6.95
Dewatering and drying
S45
Dryair
Hydrocyc
Compacting and sizing
Capacity constraints
104
2.36
54
Pres-out
7.42
FIGURE 1. Shown here a potassium chloride process as modeled in a flowsheet
simulator
In some cases, secondary distributed
parameters are not important
and can be averaged, but in others,
they may significantly affect the
process performance. As one would
imagine, considering distributed
parameters may increase the number
of variables by an order of magnitude,
if not more [1].
It is still common practice in industry
to use averages to consider
distributed parameters. An example
could be the simulation of classification
in a sifter. Here, the density
of the particles may be assumed to
be homogenous, but in some cases
this might not be a good assump50
ChemiCal engineering wwww.Chemengonline.Com DeCemBer 2014
tion and different particle types in
addition to the PSD may need to be
considered to describe the actual
classification effect [1].
To address these issues, simple
models may not suffice for solidsprocessing
equipment. Instead,
more advanced models that allow
for multiple particle types and multiple
distributed parameters may
provide a more accurate depiction
of what is actually happening inside
a certain piece of equipment.
Many process simulators offer outof-the-box
models for solids-processing
equipment. These are typically
programmed by experts using
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Chemical Engineering December 2014

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