4 Dynamic Simulation of Technical Precipitation Processes
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the localized reaction zone. The solids formation does not take place in the full STR
domain due to the low τ sf . It is, instead, limited to a small volume around the feed
pipe. This volume is also designated as the reaction zone. The local mixing conditions in this reaction zone have a significant impact on the final product PSD and,
therefore, must be considered for simulation. It is often required to perform numerically expensive computational fluid dynamics (CFD) simulations for information
about the local mixing process. This aspect is aggravated by the fact, that even while
using CFD, the definition of the exact reaction volume is unclear and, thus, can often
only be roughly estimated.
Flowsheet simulation simplifies process development and optimization and is
widely applied in process engineering, but it requires short-cut modeling of the different unit operations involved. To date, commercial flowsheet frameworks, such as
Aspen Plus or gProms, enable the steady-state and dynamic simulation of precipitation, but the underlying models are restricted to processes with only low levels
of supersaturation. As they rely on the mixed-suspension, mixed-product-removal
(MSMPR) concept (τ mix /τ sf < 1), neither different zones in the reactor nor the influence of mixing on the PSD are considered. Therefore, it has not been possible to
simulate sparingly soluble salts on a process flowsheet level yet. Although numerically reduced models for semi-batch precipitation exist in literature, these models do
not reach the numerical efficiency required for process flowsheet simulation. Consequently, new short-cut models must be developed to allow the process flowsheet
simulation of semi-batch precipitation of sparingly soluble salts.
The aim of this project is the development of a dynamic model for precipitation
which operates on time scales suitable for process flowsheet simulation. We use the
knowledge gained by investigating the influence of mixing on precipitation by CFD
methods [1–4] to develop a numerically efficient model for steady-state precipitation in confined impinging jet mixers (CIJMs). The latter are simple static mixing
geometries in comparison to the complex dynamic STRs. The steady-state model
is selectively validated by simple and complex process flowsheet simulations [5]
and, furthermore, applied to investigate different mixing models from literature. The
dynamic semi-batch model is developed according to the current state of the art in
literature, as a considerable amount of literature exists on the modeling of mixing
influenced precipitation in STRs (Fig. 1).
The models with highest computational cost fully resolve the dynamic fluid flow
with CFD (a), coupled with population balance equation (PBE) approaches, to track
the solids formation [6–14]. These studies, supported by experimental work [15–
17], offered further insights into the complex dynamics of precipitation processes
in stirred tanks. Of course, these models are numerically intense and, therefore, not
suitable for process flowsheet simulation.
Zone models (b) use distinct reactor zones instead of CFD simulations to depict the
fluid dynamics. Consequently, these models are much faster to calculate [8, 18–23].
Mechanistic models (c) are even further reduced. They combine a well-mixed
bulk fluid (BF) with a plug flow reactor (PFR) which represents the mixing and
reaction zone in the stirred tank. One of the most significant mechanistic models
for semi-batch precipitation was presented by Bałdyga and Bourne [24], who used
113
the localized reaction zone. The solids formation does not take place in the full STR
domain due to the low τ sf . It is, instead, limited to a small volume around the feed
pipe. This volume is also designated as the reaction zone. The local mixing conditions in this reaction zone have a significant impact on the final product PSD and,
therefore, must be considered for simulation. It is often required to perform numerically expensive computational fluid dynamics (CFD) simulations for information
about the local mixing process. This aspect is aggravated by the fact, that even while
using CFD, the definition of the exact reaction volume is unclear and, thus, can often
only be roughly estimated.
Flowsheet simulation simplifies process development and optimization and is
widely applied in process engineering, but it requires short-cut modeling of the different unit operations involved. To date, commercial flowsheet frameworks, such as
Aspen Plus or gProms, enable the steady-state and dynamic simulation of precipitation, but the underlying models are restricted to processes with only low levels
of supersaturation. As they rely on the mixed-suspension, mixed-product-removal
(MSMPR) concept (τ mix /τ sf < 1), neither different zones in the reactor nor the influence of mixing on the PSD are considered. Therefore, it has not been possible to
simulate sparingly soluble salts on a process flowsheet level yet. Although numerically reduced models for semi-batch precipitation exist in literature, these models do
not reach the numerical efficiency required for process flowsheet simulation. Consequently, new short-cut models must be developed to allow the process flowsheet
simulation of semi-batch precipitation of sparingly soluble salts.
The aim of this project is the development of a dynamic model for precipitation
which operates on time scales suitable for process flowsheet simulation. We use the
knowledge gained by investigating the influence of mixing on precipitation by CFD
methods [1–4] to develop a numerically efficient model for steady-state precipitation in confined impinging jet mixers (CIJMs). The latter are simple static mixing
geometries in comparison to the complex dynamic STRs. The steady-state model
is selectively validated by simple and complex process flowsheet simulations [5]
and, furthermore, applied to investigate different mixing models from literature. The
dynamic semi-batch model is developed according to the current state of the art in
literature, as a considerable amount of literature exists on the modeling of mixing
influenced precipitation in STRs (Fig. 1).
The models with highest computational cost fully resolve the dynamic fluid flow
with CFD (a), coupled with population balance equation (PBE) approaches, to track
the solids formation [6–14]. These studies, supported by experimental work [15–
17], offered further insights into the complex dynamics of precipitation processes
in stirred tanks. Of course, these models are numerically intense and, therefore, not
suitable for process flowsheet simulation.
Zone models (b) use distinct reactor zones instead of CFD simulations to depict the
fluid dynamics. Consequently, these models are much faster to calculate [8, 18–23].
Mechanistic models (c) are even further reduced. They combine a well-mixed
bulk fluid (BF) with a plug flow reactor (PFR) which represents the mixing and
reaction zone in the stirred tank. One of the most significant mechanistic models
for semi-batch precipitation was presented by Bałdyga and Bourne [24], who used