(557a) Continuous Mixing Technology: Process Design with Discrete Element Method (DEM) Simulations | AIChE

(557a) Continuous Mixing Technology: Process Design with Discrete Element Method (DEM) Simulations

Authors 

Siegmann, E., Research Center Pharmaceutical Engineering
Trogrlic, M., RCPE
Jajcevic, D., RCPE
Khinast, J. G., Research Center Pharmaceutical Engineering
Doshi, P., Worldwide Research and Development, Pfizer Inc.
Blackwood, D. O., Pfizer Worldwide Research and Development
am Ende, M. T., Worldwide Research and Development, Pfizer Inc.

Continuous Mixing Technology: Process
Design with Discrete Element Method (DEM) Simulations

Peter Toson1, Eva Siegmann1,
Martina Trogrlic1, Dalibor Jajcevic1, Johannes Khinast1

&

Pankaj Doshi2, Daniel Blackwood2,
Mary T. am Ende2

 

1 Research Center Pharmaceutical
Engineering, Inffeldgasse 13, 8010 Graz, Austria

2 Worldwide Research and Development,
Pfizer Inc. Groton CT, USA

 

Keywords:
Pharmaceutical Manufacturing; Mixing; Process Design & Development

The
pharmaceutical industry is currently transforming from batch to continuous
production processes. Advantages of continuous manufacturing include better
control of process parameters and product quality as well as lower down-times
compared to batch processing. One of the unit operations in a continuous
process is powder mixing.

An overview of
the Continuous Mixing Technology (CMT) design is given shown in Figure 1a. Feeders
provide a constant inlet material flow to the CMT device. The top region is a
de-lumping zone that breaks up agglomerates that may have formed upstream. The
mixing happens in the bottom conical region of the CMT – the mixing zone. The
mass throughput is actively controlled by upstream feeders and hold-up mass in
the CMT is controlled by changing the exit valve opening. Therefore, the mean
residence time of particles in the mixer, which is defined by ratio of hold up
mass to mass throughput, is also constant. The main advantage of this vertical
CMT design is that the shear rate can be controlled independently by changing
the impeller speed without changing the residence time. This presents more
opportunities for process design.

In this work, the
CMT device has been modeled with discrete element method (DEM) simulations. The
cohesive contact model of the DEM particles has been calibrated with
compression, spring back, and shear cell tests. The calibrated contact model is
then used in simulations of the CMT device.

The DEM
simulations allow the analysis of particle trajectories, velocity profiles, powder
bed shape, mixing behavior, as well as residence time distribution and travel
distance distribution (Figure 1b). To understand the influence of process parameters,
such as impeller speed, hold-up mass, and mean residence time on these quantities,
a full factorial virtual design of experiments (DoE) with 4 impeller speeds and
5 hold-up masses has been performed. The mass throughput has been kept constant
at 10kg/h. The highest examined hold-up mass (500g) has been modeled with 4.1
million DEM particles.

DEM simulation
results show that the powder bed shape changes significantly with impeller
speed. At impeller speeds of up to 450rpm the mixing zone is filled with powder
and narrow valve openings are required to keep the hold-up mass constant. However,
high impeller speeds >500rpm exert high centrifugal forces to the particles,
lifting the powder bed at the bottom away from the valve. High valve openings
are required in this case to ensure a constant material outflow.

One of the most important
parameter which defines the extent of mixing is the residence time distribution
(RTD) of particles in CMT. It has been evaluated directly from DEM particle
data and mimics a tracer impulse experiment (Figure 1c). A set of particles
created over the course of one second of simulation are defined as tracer
particles (tracer impulse input). For each particle, the time between entering
and exiting the CMT is stored. A histogram of these residence times yields then
the RTD.

Based on the calculation
of residence time distributions for all operating conditions, process maps have
been developed which display regions with near-perfect exponential distribution
as described by the ideal continuous stirred tank reactor (CSTR) model, and
regions with less-than-ideal mixing.

The data –
particle trajectories, powder bed shape, and residence time distribution – are
available at each of the 20 operating points defined by the virtual DoE, making
DEM simulations a valuable tool to design the continuous mixing process.

Figure 1. (a) CMT
overview. (b) A cut through the CMT to reveal the powder bed shape in the
mixing zone at 350 rpm. (c) Tracer particles (red) used to determine the
residence time distribution. Snapshot taken 2s after insertion of the tracer impulse.