(503e) Hysteresis in Solid-Liquid Suspensions in Optimax®: Using CFD Simulations and Experiments With FBRM

Title: Hysteresis
in solid-liquid suspensions in OPTIMAX^®: Using CFD simulations and
experiments with FBRM

Authors:
Vedantam, S., Ranade, V.V.*

Affiliation:
Industrial Flow Modeling Group (iFMg), CEPD Division, National Chemical
Laboratory (NCL), Pune, INDIA

*corresponding
author: vv.ranade@ncl.res.in

ABSTRACT

Introduction:

Crystallization
is the most widely used separation and purification process employed throughout
the chemical and pharmaceutical industry for chemical products that are solids
at room temperature and pressure. Today, crystallization modeling tools are
limited by the availability of methods to reliably predict solubility and super
saturation for chemical systems of industrial importance. There is also limited
capability for describing nucleation and crystal growth, and mixing and design
scale-up for industrial crystallizers. Tools are needed to model and optimize
crystallizer process performance with respect to product quality, throughput
and efficiency. It is essential to understand and relate key thermodynamic,
kinetic and hydrodynamic aspects to crystallizer performance not just in terms
of yield but also in terms of product quality (characterized by particle size
distribution, morphology, polymorphism and the amount of strain as well as the
uptake of solvent or impurities in the crystal lattice). Process Analytical
Technology (PAT) tools are also on the rise in these applications and published
in the literature (Daneau and Steele., 2005; Samad et al., 2013).

Hydrodynamic
modeling, one of the key aspects, is the focus of the work presented in this
abstract. In literature, Joshi et al (2011), presented a comprehensive review
on CFD modeling studies in stirred tanks, stating that it is worth noting that
dense suspensions require a correct modeling of both solid?liquid and particle?
particle interactions. However, as an initial step, an automated reactor called
OPTIMAX^® (launched by Mettler-Toledo Ltd.,) is being used for
the study of various aspects of crystallization and the quantitative effect of
all key aspects on the process. OPTIMAX^® (OM), a synthesis
workstation provides a platform for product and process development and is
coming into use in bio-pharmaceutical synthesis applications. OM is typically
an automated reactor, offering heating electrically and cooling on the basis of
Peltier technology. Crystallization is one of the wide hopes
of applications to be carried out in this particular workstation. In this
particular set-up, OM is designed to accommodate internals such as Focused Beam
Reflectance Measurement (FBRM) probe (used for estimating the Chord Length
Distributions (CLD) and thus, Crystal Size Distributions (CSD)); Temperature
probe (Tr probe), Fourier-Transform Infra Red (FTIR) spectroscopy probe;
turbidity probe; pH probe; impeller and baffles as well. However, as for this
study, the internals used are FBRM probe; Tr probe and 4-bladed down-pumping
PBT as impeller are used. It is understandable that the reactor geometry,
operating conditions and the flow characteristics govern the hydrodynamic
aspects of the crystallization process thus subsequently also affecting the
kinetic aspects. Solid-liquid suspension studies on solids distribution and the
effect of operating conditions has been simulated and experimentally verified.

Methodology,
flow characterization and mixing time:

Commercial
software Ansys Fluent (14.0) has been used for all CFD simulations. Multiple
Reference Frame (MRF) approach is used for modeling the impeller. Multiple
phases have been simulated using Eulerian approach. 1000 mL reactor volume has
been used as the domain for simulations and experiments, with an inner diameter
of 0.101 m, and a height of 0.137 m. The impeller used is a 45⁰,
four-bladed, down pumping PBT. A mesh size of 4, 60,000 cells has been used for
the entire domain. Simulations are carried out for impeller speed ranging from
100 to 1000 rpm, and varying solids hold-up of the particles used. The geometry
indicating the internals, tank and inner and outer regions of the domain, clearly
demarked for MRF approach are shown in the Figure 1. The commonly used
validation check points such as Power number (N_P, from turbulent
energy dissipation rate and moments), Pumping number (N_Q) are
estimated from the CFD predictions, and satisfactory validation has been
obtained, which gives a go ahead for further studies on crystallization in this
reactor.

Experiments are carried out using
FBRM to estimate the distribution of particles, and verify the hysteresis
likely to occur with the variation in impeller speed. Neutrally buoyant
particles of 350 micron are used as solid particles. Hold-up has been varied
from 1 % to 10 % in the reactor. Impeller speeds are varied from 100 rpm to
1000 rpm and the particle size distribution has been tracked using FBRM.
Similar conditions have been simulated using CFD.

Conclusions:

Solid-liquid
suspension studies in OPTIMAX^®are carried out
using simulations as well as experiments. The CFD study is validated with the
established parameters such as N_P (from estimated turbulent energy
dissipation rate and the torque), N_Q from the CFD predictions. Possibility
of hysteresis has been verified using FBRM and CFD simulations.

References:

Samad, N.A.F.B.A., Sin, G., Gernaey, K.V., Gani., R.
2013, ?A systematic framework for design of process monitoring and control
(PAT) systems for crystallization processes?, Computers & Chemical
Engineering, 54, 8-23. http://dx.doi.org/10.1016/j.compchemeng.2013.03.003

Buwa, V. V. and Ranade, V. V., 2003a Characterization
of dynamics of gas-liquid flows in rectangular bubble columns, AIChEJ, 50,
2394.

Deneau, E., Steele, G, 2005, An in-line study of
oiling out and crystallization, Org. Proc. Res. Dev., 9, 943-950.

Joshi, J.B., Nere, N.K., Rane, C.V., Murthy, B.N.,
Mathpati, C.S., Patwardhan, A.W., Ranade, V.V., 2011, CFD Simulation of Stirred
Tanks: Comparison of turbulence models (Part II: Axial Flow Impellers, Multiple
Impellers and Multiphase Dispersions), The Canad. J. of Chem. Eng., 89,
754-816.

Ranade, V. V., Bourne, J. R. and Joshi, J. B., 1991.
Fluid mechanics and blending in agitated tanks. Chem. Eng. Sci., 46, 1883.

Figures:

Figure 1. Computational domain showing inner and outer
regions of MRF approach