XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 1987
that closely spaced inclined channels will promote density-
based separation of particles of smaller size but would be
detrimental for size-based separation of particles of similar
density.
Many studies have been conducted to understand
the hydrodynamics and transport mechanisms of the RC
and how they influence its performance (Doroodchi et
al., 2006 Galvin et al., 2005 Galvin &Nguyentranlam,
2002 Nguyentranlam &Galvin, 2001). Recently Starrett
and Galvin (2023) carried out an experimental study to
classify a feed suspension as a function of particle size in a
Reflux Classifier. A secondary inflow of water (spilt fluidi-
sation) was applied in the experiment for achieving control
on the separation size and to provide sharp separation at
high throughputs. This investigation demonstrated that the
hydrodynamics of the fluidised bed delivers control over
separation size whilst the precise velocity field within the
inclined channels yields sharp separation. Studying the
hydrodynamics experimentally of a device like the Reflux
Classifier is a complicated task because of difficulties in
measuring shear rates, observing velocity fields and/or par-
ticle trajectories in 3D. In addition, challenges associated
with sample preparation with precisely controlled physical
properties, as well as the scale-up process, can limit a solely
empirical approach, rendering experiments expensive and
time consuming. Computational fluid dynamics (CFD)
provides an alternative avenue to study and analyse Reflux
Classifier hydrodynamics, at significantly reduced cost and
time. CFD has been proven to be effective in predicting
the local and global hydraulic characteristics inside devices
without affecting the working conditions (Diba, Karim, &
Naser, 2022 Zhou et al., 2017). CFD has been applied for
studying the hydrodynamics and flow behaviour of various
equipment, including fluidised beds, conventional flota-
tion cells, sedimentation tanks, and inclined plate settlers
(Diba, Karim, &Naser, 2020a, 2020b Islam &Nguyen,
2021 Peng, Galvin, &Doroodchi, 2019 Salem, Okoth,
&Thöming, 2011 Tarpagkou &Pantokratoras, 2014).
These investigations have shown that CFD is an effective
tool in understanding the flow dynamics and the influ-
ence of operating conditions on the overall performance
of the equipment. Doroodchi, Galvin and Fletcher (2005)
investigated the influence of inclined plates on expansion
behaviour of solid suspensions in a two-dimensional flui-
dised bed and found reasonable agreement with experimen-
tal results. Peng, Galvin and Doroodchi (2019) conducted
computational studies on the liquid-solid flow behaviour
in a fluidised bed, as well as the influence of inclined plates
on the flow characteristics of the bed. Some investigations
have also been conducted using a segregation-dispersion
model to study the Reflux Classifier (Syed et al., 2018
Syed, Galvin, &Moreno-Atanasio, 2019). The present
work builds upon the most recent experimental work and
understanding, especially the basis for controlling the sepa-
ration size.
In this study, we examine the hydrodynamics of a lab-
oratory-scale Reflux Classifier using CFD simulations. A
three-dimensional Eulerian-Eulerian model is formulated
to explore the impact of particle size on hydrodynamics
and transport mechanisms. The numerical investigations
were performed in two stages. Firstly, a batch mode flui-
dised bed is simulated and validated against experimental
results. Subsequently, a continuous flow model is applied to
generate a simulated partition curve for specific operating
conditions drawn from published literature. This simulated
curve is then compared with experimental data, revealing
that the CFD simulations accurately capture key features
of the experiments. This validation affirms the reliability
of the developed computational model, enabling computa-
tional exploration of the hydrodynamic behaviour underly-
ing these observable phenomena.
METHODS AND MATERIALS
Numerical Method
The simulation of multiphase flow was performed using the
Eulerian-Eulerian two-fluid model (TFM) approach. This
widely-used method is common in modelling fluidised bed
hydrodynamics, treating the fluid (gas/liquid) as the con-
tinuous phase and the solid as the dispersed phase (Diba,
Karim, &Naser, 2020a Islam &Nguyen, 2021 Peng et
al., 2021). In this approach, phases are considered as inter-
penetrating continua, with conservation equations solved
independently for each phase and source terms used for
phase coupling (Anderson &Jackson, 1967). Governing
equations for mass and momentum conservation account
for spatial pressure gradients, stress tensors for both solid
and fluid phases, gravitational forces, and interphase
momentum transfer through a drag force. The kinetic
theory of granular flow (KTGF) model captures solid
phase behaviour (Gidaspow, 1994), with the Gidaspow
drag model estimating the crucial drag force facilitating
momentum exchange between fluid and solid phases. Bed
pressure drop within dense solid regions is determined
using the Ergun equation (Ergun &Orning, 1949), while a
modified Stokes law (Bouillard, Lyczkowski, &Gidaspow,
1989) is employed for low concentration regions. The drag
coefficient is calculated based on the solid Reynolds num-
ber (Gidaspow, Seo, &Ettehadieh, 1983). Turbulence is
another important aspect in CFD multiphase modelling.
For modelling turbulent flow, the k-epsilon turbulence
that closely spaced inclined channels will promote density-
based separation of particles of smaller size but would be
detrimental for size-based separation of particles of similar
density.
Many studies have been conducted to understand
the hydrodynamics and transport mechanisms of the RC
and how they influence its performance (Doroodchi et
al., 2006 Galvin et al., 2005 Galvin &Nguyentranlam,
2002 Nguyentranlam &Galvin, 2001). Recently Starrett
and Galvin (2023) carried out an experimental study to
classify a feed suspension as a function of particle size in a
Reflux Classifier. A secondary inflow of water (spilt fluidi-
sation) was applied in the experiment for achieving control
on the separation size and to provide sharp separation at
high throughputs. This investigation demonstrated that the
hydrodynamics of the fluidised bed delivers control over
separation size whilst the precise velocity field within the
inclined channels yields sharp separation. Studying the
hydrodynamics experimentally of a device like the Reflux
Classifier is a complicated task because of difficulties in
measuring shear rates, observing velocity fields and/or par-
ticle trajectories in 3D. In addition, challenges associated
with sample preparation with precisely controlled physical
properties, as well as the scale-up process, can limit a solely
empirical approach, rendering experiments expensive and
time consuming. Computational fluid dynamics (CFD)
provides an alternative avenue to study and analyse Reflux
Classifier hydrodynamics, at significantly reduced cost and
time. CFD has been proven to be effective in predicting
the local and global hydraulic characteristics inside devices
without affecting the working conditions (Diba, Karim, &
Naser, 2022 Zhou et al., 2017). CFD has been applied for
studying the hydrodynamics and flow behaviour of various
equipment, including fluidised beds, conventional flota-
tion cells, sedimentation tanks, and inclined plate settlers
(Diba, Karim, &Naser, 2020a, 2020b Islam &Nguyen,
2021 Peng, Galvin, &Doroodchi, 2019 Salem, Okoth,
&Thöming, 2011 Tarpagkou &Pantokratoras, 2014).
These investigations have shown that CFD is an effective
tool in understanding the flow dynamics and the influ-
ence of operating conditions on the overall performance
of the equipment. Doroodchi, Galvin and Fletcher (2005)
investigated the influence of inclined plates on expansion
behaviour of solid suspensions in a two-dimensional flui-
dised bed and found reasonable agreement with experimen-
tal results. Peng, Galvin and Doroodchi (2019) conducted
computational studies on the liquid-solid flow behaviour
in a fluidised bed, as well as the influence of inclined plates
on the flow characteristics of the bed. Some investigations
have also been conducted using a segregation-dispersion
model to study the Reflux Classifier (Syed et al., 2018
Syed, Galvin, &Moreno-Atanasio, 2019). The present
work builds upon the most recent experimental work and
understanding, especially the basis for controlling the sepa-
ration size.
In this study, we examine the hydrodynamics of a lab-
oratory-scale Reflux Classifier using CFD simulations. A
three-dimensional Eulerian-Eulerian model is formulated
to explore the impact of particle size on hydrodynamics
and transport mechanisms. The numerical investigations
were performed in two stages. Firstly, a batch mode flui-
dised bed is simulated and validated against experimental
results. Subsequently, a continuous flow model is applied to
generate a simulated partition curve for specific operating
conditions drawn from published literature. This simulated
curve is then compared with experimental data, revealing
that the CFD simulations accurately capture key features
of the experiments. This validation affirms the reliability
of the developed computational model, enabling computa-
tional exploration of the hydrodynamic behaviour underly-
ing these observable phenomena.
METHODS AND MATERIALS
Numerical Method
The simulation of multiphase flow was performed using the
Eulerian-Eulerian two-fluid model (TFM) approach. This
widely-used method is common in modelling fluidised bed
hydrodynamics, treating the fluid (gas/liquid) as the con-
tinuous phase and the solid as the dispersed phase (Diba,
Karim, &Naser, 2020a Islam &Nguyen, 2021 Peng et
al., 2021). In this approach, phases are considered as inter-
penetrating continua, with conservation equations solved
independently for each phase and source terms used for
phase coupling (Anderson &Jackson, 1967). Governing
equations for mass and momentum conservation account
for spatial pressure gradients, stress tensors for both solid
and fluid phases, gravitational forces, and interphase
momentum transfer through a drag force. The kinetic
theory of granular flow (KTGF) model captures solid
phase behaviour (Gidaspow, 1994), with the Gidaspow
drag model estimating the crucial drag force facilitating
momentum exchange between fluid and solid phases. Bed
pressure drop within dense solid regions is determined
using the Ergun equation (Ergun &Orning, 1949), while a
modified Stokes law (Bouillard, Lyczkowski, &Gidaspow,
1989) is employed for low concentration regions. The drag
coefficient is calculated based on the solid Reynolds num-
ber (Gidaspow, Seo, &Ettehadieh, 1983). Turbulence is
another important aspect in CFD multiphase modelling.
For modelling turbulent flow, the k-epsilon turbulence