optimization of bath mixing and steel cleanliness during
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Optimization of bath mixing and steel cleanliness during steel refiningthrough physical and mathematical modeling
PRANAV KUMAR TRIPATHI* , D SATISH KUMAR, AMIT SARKAR and S C VISHWANATH
JSW Steel Ltd, Vijayanagar Works, Toranagallu, Bellary, Karnataka, India
e-mail: [email protected]
MS received 27 January 2021; revised 13 May 2021; accepted 16 June 2021
Abstract. During ladle refining process, argon gas is purged into the ladle for stirring the molten steel bath to
eliminate thermal and composition gradients and to achieve inclusion flotation. Operating parameters like
purging location, porous plug configuration and argon flow rate primarily affect liquid steel refining. The
efficiency of ladle processing is often quantified through mixing time. To optimize the mixing time and the
associated process parameters for improved bath homogenization and inclusion flotation under different oper-
ating conditions, water modeling studies using 0.2 scale perspex model and computational fluid dynamics
studies using ANSYS CFX v14.5 have been carried out through fluid profile assessment and mixing time
comparison. Comparative study was made between single plug, dual plug and top lance purging configurations.
The studies helped in identifying the optimum argon purging rates and configurations under normal operational
practices. Under abnormal operating conditions involving purging failure from either of the two porous plugs,
usage of a top lance along with the single working porous plug has been investigated and found to improve
mixing and inclusion flotation in the ladle equivalent to dual plug operation. The lab scale studies have been
validated on plant scale through inclusion mapping and found to be in close agreement.
Keywords. Ladle treatment; water modeling; argon purging; mixing time; steel cleanliness.
1. Introduction
During secondary stage of steelmaking, argon purging is
carried out from ladle bottom to enhance reaction rates,
eliminate thermal and composition gradients and remove
non-metallic inclusions from the steel. In such a process,
argon gas bubbles formed in the molten steel move up to
the slag-metal interface under the action of buoyant forces
and finally reach the top layer of slag phase. The rising gas
bubbles push the liquid steel up at local area, thereby
inducing a turbulent re-circulatory flow enhancing the rate
of chemical and thermal homogenization as well as accel-
erating the absorption of harmful non-metallic inclusions
into an overlying slag phase. Under industrial conditions,
typically moderate gas flow rates are applied to achieve
thermal and chemical homogenization, although intense
stirring conditions are also practiced for accelerating slag-
metal reactions. Consequently, depending on the specific
objectives of a ladle refining operation, a wide range of gas
flow rates are applied to maximize alloy recovery through
proper dissolution and refining operations during ladle
treatment along with removal of non-metallic inclusions to
produce ‘clean’ steel.
The physical characteristics of the gas-liquid or air-water
plumes of relevance to ladle processing have been inves-
tigated extensively by a number of researchers. Mazumdar
and Guthrie have extensively reviewed the physical and
mathematical modeling systems useful for gas purging
systems [1]. The effect of different ladle designs on bath
mixing have been reported by Mazumdar et al. They have
reported that a flat ladle bottom accounts for fastest mixing
in the ladle [2]. Castello-Branco and Schwerdtfeger have
studied the characteristics of bubble plumes and measured
the profiles of gas concentration, bubble frequency, and
liquid and gas velocities through water model studies and
concluded that the bubble plume is not at a fixed position
but wanders away from the vertical vessel axis [3]. Sahai
and Guthrie have studied the hydrodynamics of gas plume
systems and reported that the rising plume generates strong
recirculatory mixing zones in the ladle. They have postu-
lated the plume geometry as a function of gas flowrate,
vessel size and aspect ratio [4]. Geng et al have explained
that there are two types of recirculatory zones in the ladle
for dual plug purging – between two plumes and between
plume and ladle sidewall [5]. Schwarz has demonstrated a
two-fluid model to predict bath recirculation and bubble
plume structure in gas stirred vessels [6]. Haiyan et al havecarried out water model studies with different purging rates
for both the plugs. They found that due to different gas flow*For correspondence
Sådhanå (2021) 46:146 � Indian Academy of Sciences
https://doi.org/10.1007/s12046-021-01663-8Sadhana(0123456789().,-volV)FT3](0123456789().,-volV)
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rates, a stronger and a weaker plume is formed. In such a
case, the interference and collision from the two plumes are
weakened and the dissipation of stirring energy is decreased
leading to a decrease in the mixing time [7].
It has been well accepted that during ladle refining of
steel, in the immediate vicinity of the nozzle, the input gas
kinetic energy as well as the mode of gas injection are
important variables governing the overall mixing rates in
the vessel. The refining mechanisms during a ladle treat-
ment are controlled by transport mechanisms and flow
patterns in the liquid phase which determine the reaction
rate. Bath stirring provided by argon injection helps in
uniform mixing of reagents in the ladle and better reaction
kinetics is achieved. The flow rates of injected argon have
been found to be the major factor controlling the stirring
rate in the ladle. It has been reported that higher gas flow
rates provide good stirring in the ladle whereas mild
purging increases the rate of inclusion flotation in the ladle.
Xie et al have studied the dynamic behavior of bubbles
emerging from various orifice sizes. They have reported
that bubble evolution and dispersion behavior depends
upon orifice sizes and gas flow rates [8]. Cao and Nastac
have studied the effects of the free surface set-up, injected
bubble size, gas flow rate, and slag layer thickness on the
slag-steel interaction and mass transfer behavior and
reported that as the gas stirring rate increases, the mass
transfer coefficient increases. By injecting finer bubbles,
increasing gas flow rate and slag layer thickness, the ladle
refining efficiency can be enhanced significantly [9]. Patil
et al have reported that along with gas flow rate, liquid
depth and vessel radius, thickness of the upper phase liquid
slag has the most significant effect on mixing times. They
have concluded that 95% bulk mixing time in slag covered,
axisymmetrical ladles appropriately represents the mixing
behavior in the ladle [10]. Amaro-Villeda et al have
reported that a thicker slag layer increases the mixing time
as it reduces the average recirculation velocity. An increase
in slag viscosity and a lower gas purging rate reduces the
top slag ‘eye’ opening. Mixing times are also increased by
decreasing the gas flow rate and increasing the number of
nozzles [11]. Gonzalez-Bernal et al have conducted water
model studies on a 1/7th scale model using modified Froude
number criterion and demonstrated that the number, size
and locations of recirculatory zones within the ladle have a
significant effect on the mixing time in the ladle. Increasing
the gas flow rate decreases the mixing time, however an
excess of gas flow results in adverse effects like re-oxida-
tion due to slag eye formation and reduction in the
refractory life of the ladle [12]. Chen et al have reported theeffects of nozzle arrangements, separation angle, radial
position and asymmetry as well as tracer adding position on
the mixing time for a ladle with dual plug purging system.
The most favorable mixing has been reported when the two
nozzles are symmetrically arranged at half radii in the ladle,
with 45� separation angle [13]. Liu et al have found that
eccentric gas injection in the ladle improves the mixing
efficiency. The mixing time decreases with increasing the
gas flow rates and porous plug angles. Shorter mixing times
are achieved in case of dual plug purging when plugs are
located diametrically opposite at mid-bath radius position.
Higher gas flow rates cause slag eye formation at the top
which decreases the mixing time due to higher turbulence
[14]. Ganguly and Chakraborty have examined the effects
of gas flow rate, bottom nozzle configurations and tracer
addition locations on mixing time. They have reported that
the arrangement of bottom nozzles has a great effect on the
mixing behaviour in a gas stirred ladle, with off centric gas
injection producing shorter mixing time. Mixing time is
also sensitive to the tracer addition position, particularly for
the axisymmetric bottom gas injection system [15]. Fan and
Hwang have concluded that the optimal addition location of
a Ca-Si injection wire in a gas stirred ladle is opposite to the
plume as it helps in avoiding the loss of additions through
vaporization [16].
The efficiency of ladle processing is often quantified
through mixing time. The stirring action imparted by the
rising gas in gas stirred ladles causes the movement of melt.
An optimized purging location tends to impart proper and
uniform mixing in the ladle with minimum percentage of
regions with no or ‘‘dead’’ flow. The choice of single or
multi-location purging is highly critical for final steel pro-
cessing. Apart from purging configuration, the purging flow
rates also need to be properly maintained in the ladle
depending upon the treatment being carried out. Gomez
et al have studied the effect of nozzle radial position,
nozzle separation angle, gas flow rate and slag thickness on
mixing time using water model studies. They have reported
shortest mixing time with a nozzle radial position of 0.67R
with 608 separation angle and without top slag layer. For a
radial position of 0.5R, both single and dual purging plugs
were found to be nearly equivalent. They have also reported
that tracer concentration also affects mixing times in the
ladle at low gas flow rates. However at high gas flow rates,
mixing time is independent of tracer concentration [17].
Chattopadhyay et al have measured mixing time on a 0.2
scale aqueous model of a single tapered ladle with different
bottom purging locations. They have reported that two plug
purging gives faster mixing than one plug purging. Also,
faster bath mixing is obtained when the plugs are located at
�R distance from the ladle centre. A higher gas injection
rate yields faster mixing in the ladle [18].
Even though a number of physical modeling and
numerical simulation studies have been carried out by a
number of researchers to study gas-metal dual-phase
interactions in ladle, the effects of different purging con-
figurations for argon injection ranging from multi-point
injection to the usage of a top lance have been scarcely
investigated. Additionally, the published research result
does not suggest any corrective action to be taken when
non-optimal purging configurations prevail during ladle
treatment in practical industrial conditions. In the present
work, different ladle purging configurations have been
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studied by means of physical and mathematical (CFD)
modeling techniques. The aim of the present work is to
identify the best purging configuration for faster bath
homogenization and inclusion flotation. Additionally, a
new purging configuration has been suggested as a pre-
ventive and corrective action when optimal purging con-
ditions are not achieved due to operational issues. The
suggested configuration was subsequently validated
through actual plant trials.
1.1 Ladle argon purging configurations
Steel melting shop II at JSW Steel is equipped with 180 ton
capacity ladles with dual porous plugs at ladle bottom for
argon purging. The normal operational practice at ladle
heating furnace (LHF) stations for ladle treatment involves
usage of two porous plugs for argon purging. These porous
plugs are located asymmetrically in the ladle for argon
purging. All the additions in the ladle are carried out from
the top. Majority of these additions are of lower density
than molten steel. Therefore, for their proper dissolution in
the steel bath vigorous mixing is carried out.
The different simulation conditions are listed in table 1.
Normally, both porous plugs are used for argon purging
(A1). However, due to some operational abnormality, if
argon purging fails from one of the plugs, the treatment is
continued using the other plug essentially reducing it to a
scenario of single plug purging (A3). When purging from
both the plugs fails then as a fail-safe option, a top lance is
introduced from the top into the ladle for argon purging. In
the existing setup, the top lance is used in a slant condition
at an inclination of 6-78 with vertical axis (B1). Unlike the
very fine openings of the plugs, the top lance has a quite big
9 mm opening for argon passage into the ladle. Apart from
these conditions, some additional situations have also been
studied to identify the effect of purging location on mixing
times in the ladle, namely - symmetrically placed dual
plugs (A2), single plug at ladle centre (A4) and top lance in
straight condition at ladle off-centre (B2) and centre (B3).
One additional condition was simulated when only one of
the two porous plugs remains operational viz. usage of top
lance along with the lone operative plug (C).
During ladle treatment, bulk additions (lime, aluminum,
ferro-manganese etc.) are carried into the ladle through
automated addition via hopper or through wire feeding
system. The addition location is fixed in such cases.
However, a majority of the additions like calcined petro-
leum coke (CPC), ferro-alloys and other micro-alloys are
carried out manually into the ladle. In such cases, some
variations in the addition location in the ladle are quite
likely which is expected to affect the mixing time in the
ladle. Thus, tracer addition locations were varied for certain
configurations (A1, A3, B1 and C) as shown by locations a,
b, c and d in figure 1.
2. Experimental
2.1 Physical model
To investigate the effect of different purging configurations
on the mixing time, a reduced scale plexi glass water model
was fabricated having 0.2 scale factor with respect to the
180 ton industrial scale ladle. The water model was
equipped with flow meters, multiple porous plugs at the
base and a top lance system. Water was used to simulate
molten steel whereas compressed air was injected through
porous plugs and top lance to simulate argon purging in the
ladle. Flow meters capable of controlling flow rates
between 0-10 litres/minute (l pm) were used to regulate air
flow into the ladle. Conductivity measurements were car-
ried out using the electrical conductivity measurement
technique through stimulus response of injected salt solu-
tion of known concentration. Flow visualization studies
were carried out using colored KMnO4 solution. The details
of actual ladle and model vessel are given in table 2.
The major forces influencing the flow in an argon purged
industrial ladle include gravitational, buoyancy and drag.
To establish similarity between plant and water model
Table 1. Cases studied through water modeling.
Purging configuration Description Tracer addition location
Dual plugs Same side
Opposite side
(A1)(A2)
1. Over plume
2. Opposite to plumes
3. Between plumes
(a)(b)(c)
Single plug Off-centre
Centre
(A3)(A4)
1. Over plume
2. Opposite to plume
(a)(b)
Top lance Slant & off-centre
Straight & off-centre
Straight and centre
(B1)(B2)(B3)
1. Over plume
2. Opposite to plume
(a)(b)
Top lance with single plug Slant lance with off-centre plug (C) 1. Over plume
2. Opposite to plume
3. Over non-working
plug
(a)(b)(d)
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system, modified Froude number criterion was used as it
can characterize the kinetic similarity between plant ladle
and water model for argon purging conditions
[3, 7, 11–14, 17, 19, 27]. Consequently,
ðF 0rÞmðF
0rÞp ð1Þ
qair:u2water
ðqwater � qairÞ:g:Hm¼ qAr:u
2steel
ðqsteel � qArÞ:g:Hpð2Þ
The characteristic velocity u. is expressed as:
u ¼ 4:Q
p:d2ð3Þ
Equating eg. (1) to (3) based on the data listed in table 3
gives :
Qm ¼ 0:0077195:Qp ð4Þ
Corresponding to the range of argon purging used in
plant (10-50 Nm3/h), the flow rates for compressed air
during water model studies is listed in table 1.
The water model vessel was filled with water up to the
required bath height corresponding to the level of the metal
bath in the plant ladle. The position of the lance and water
level were fixed for the entire set of experiments. The
extent of mixing was determined by conductivity mea-
surements using NaCl salt solution of known density (1.1
g/lt) as tracer and a standard conductivity meter (Eutech
CyberScan COND 600) for measuring the conductance of
the solution. Data generated was captured using a computer
equipped with data acquisition software. The experimental
setup is shown in figure 2. Compressed air was introduced
through the top of the lance or porous plugs at predeter-
mined flowrates using the flow meter and was monitored
continuously during the experiments. A fast speed video
camera was used to record the generation and dissipation
phenomenon of the bubbles in the ladle during the course of
the experiments. When steady state was attained, the tracer
was gently added from the ladle top using a beaker wall just
below the water surface shown as position ‘A’ in figure 3 to
simulate alloying additions in the ladle. The location A was
Figure 1. Experimental Cases.
Table 2. Details of water model and plant scale steel ladle.
Parameter Plant Model
Scale factor 1 0.2
Ladle height (mm) 3500 700
Ladle top diameter (mm) 3460 692
Ladle base diameter (mm) 3205 641
Ladle freeboard (mm) 575 115
Top lance tip diameter (mm) 9 1.8
Blowing Gas Argon Air
Density of Blowing Gas (kg/m3) 1.78 1.29
Density of liquid (kg/m3) 7020 1000
Table 3. Argon flowrates for industrial scale and water model
system.
Argon flowrate Values
Industrial scale ladle (Nm3/h) 10 20 30 40 50
Water model ladle (lpm) 1.3 2.6 3.9 5.1 6.4
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varied as per different addition locations mentioned in
table 3. The steel bath in the ladle was considered ‘ho-
mogenized’ when 95% mixing of tracer was achieved as
reported by Madan et al [10] and Patil et al [20]. There is asignificant difference between the mixing times in the
central volume of the ladle and near walls and hence the
measurement in the slowest flow region is critical for
estimating the bulk mixing time. Through a series of
experiments it was found that the conductivity probe dipped
650 mm into the ladle at 50 mm away from the wall of the
vessel shown as position ‘B’ in figure 3 was the most
suitable location as it took relatively higher time for com-
plete homogenization compared to other locations. 50 ml
tracer was used in each experiment and conductivity of the
solution was recorded continuously thereafter till the
reading becomes constant. The same process was repeated
for all the cases. The internal mixing time (T) was calcu-
lated from the conductivity vs time plots and compared for
all the design cases.
2.2 Mathematical model
Commercially available computational fluid dynamics
(CFD) code ANSYS-CFX 14.5 was used to perform com-
putations on a Dell Workstation with Intel Xeon 12 core
64-bit processor and 72 GB of RAM on Windows platform.
The fluid flow profile during ladle treatment was simulated
under different argon purging configurations and compared
with the water modeling findings. A full scale 3D model
was developed using momentum balance considering
molten steel as a Newtonian and incompressible fluid.
2.3 Governing equations
The following governing equations were used for devel-
opment of CFD model.
2.3a The continuity equation:
oqot
þr � qUð Þ ¼ 0 ð5Þ
where, q is fluid density, t is time and U is the flow velocity
vector field.
In the case of incompressible flows q is a constant,
hence, the above mass continuity equation simplifies to a
volume continuity equation.
r � u ¼ 0 ð6Þ2.3b The momentum equation:
o qUð Þot
þr � qU � Uð Þ ¼ �r pþ r � sþ SM ð7Þ
where, p is the static pressure, s is the shear stress and SM is
the momentum source term. The stress tensor, s, is
described as
s ¼ l rU þ rUð ÞT� 2
3dr � U
� �ð8Þ
where, l is the dynamic viscosity.
2.3c Buoyancy: For simulating the effect of buoyancy
due to difference in densities of the interacting fluids, a
source term is added to the momentum equations as in
Eq. (7).
SM;buoy ¼ q� qref� �
g ð9Þ
Figure 2. Experimental set-up.
Figure 3. Water model measurements
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The density difference q� qref� �
was evaluated using
full buoyancy model for modeling multiphase flow.
2.3d Turbulence model: Due to presence of re-circulatoryzones with high Reynolds number in the continuous fluid
domain, k � e model was used to model turbulence for the
continuous molten steel phase as it offers a good compro-
mise in terms of accuracy and robustness. k is the turbu-
lence kinetic energy and is defined as the variance of the
fluctuations in velocity.
o qkð Þot
þr � qUkð Þ ¼ r � lþ ltrk
� �r k
� �þ Pk þ Pkb
� qe
ð10Þe denotes the rate at which the velocity fluctuations
dissipate.
o qeð Þot
þr � qUeð Þ ¼ r � lþ ltre
� �re
� �
þ ek
Ce1 Pk þ Pebð Þ � Ce2qeð Þ ð11Þ
where, Ce1;Ce2; rk and re are constants.
For dispersed argon gas phase, dispersed phase zero equa-
tionmodel was used. It uses an algebraic equation to calculate
the viscous contribution from turbulent eddies to derive a
constant turbulent eddy viscosity is calculated for the entire
flow domain. The turbulence viscosity (lt) is modeled as the
product of a turbulent velocity scale (Ut) and a turbulence
length scale (lt) as proposed by Prandtl and Kolmogorov.
lt ¼ qflUtlt ð12Þwhere fl is a proportionality constant.
2.4 Modeling and boundary conditions
The model was developed in full scale. No symmetry
planes were considered so as to allow both symmetrical as
well as non-symmetrical flow conditions depending on the
selected turbulent conditions. The present scope of study
includes comparison of fluid flow profile, hence isothermal
conditions were assumed for all the simulations. It allows
for the assumptions that the density of molten steel doesn’t
change appreciably during steady state operating condi-
tions. The simulation involved a multi-phase study with
following two phases, phase 1 – molten steel, and phase 2 –
argon (purging) gas. Molten steel was taken as the con-
tinuous liquid phase with argon gas as the dispersed gas-
eous phase. As both these phases have different material
properties and a distinct flow field, hence, the inhomoge-
neous model was used for simulating multi-phase flow in
the ladle. This allows each fluid to possess its own flow
field with different fluids interacting via interphase transfer
terms. Free surface model was used for simulating
interfacial mass transfer between the continuous and dis-
persed phases. This allows a distinct interface between the
fluids to be modeled in multiphase flows. A drag coefficient
of 0.44 was used to model inter-phase drag on dispersed
fluid phase. A surface tension coefficient of 1.6 N/m was
used for steel-argon interface considering molten steel as
the primary fluid. k � e turbulence model with medium
turbulence intensity was used for continuous phase and
dispersed phase zero equation model was used for dispersed
phase.
The mass flow rate inlet boundary condition was used for
the inlets, and opening boundary condition was used at the top
of the ladle as it is open to atmosphere. As the viscosity of
continuous phase (molten steel) is very high as compared to
that of dispersed phase (argon gas), all the walls were assumed
as no slip walls for the continuous phase and as free slip walls
for the dispersed phase. Argon gas mean bubble size was
considered as 30 mm using Eq. 13 provided by Johansen and
Boysan for the simulations corresponding to the average
purging rates of 20-25 Nm3/hr under plant conditions [21].
db ¼ 0:35Q2
g
� �0:2
ð13Þ
Buoyant conditions were simulated based on density dif-
ference. The density of argon gas was used as buoyant ref-
erence density to avoid round-off errors during calculations.
2.5 Simulation process
During numerical simulations, the whole fluid domain is
divided into multiple small regions or grids, often called as
control volumes wherein the Navier–Stokes equation is
solved iteratively to obtain the approximate solution of the
fluid flow field. The accuracy of the solution and the
computational load depends on the mesh size and quality.
To establish mesh size independency of the results, initial
steady state simulations were carried out with different
mesh sizes of 15, 25, 30, 50 and 100 mm for purging
configuration A1 and A3. The resultant velocities of molten
steel phase were monitored at locations A and B (figure 3)
keeping argon purging rate constant (30 Nm3/h).
It was found that the steel flow velocities under different
conditions slightly increase with increase in mesh size and
become practically constant for mesh size B30 mm as
shown in figure 4. Consequently, a maximum mesh size of
25 mm was finalized to achieve good accuracy with opti-
mum computational load. The minimum mesh size allowed
was 1 mm for ladle domain and 0.5 mm for lance domain.
Three dimensional unstructured mesh was generated for the
fluid domain using a combination of tetrahedral, prism and
pyramid elements. Individual part meshing strategy was
used along with mesh refinement to achieve finer mesh
elements at intricate geometry regions. A minimum mesh
quality of 0.5 was maintained for[95% mesh elements to
ensure good accuracy of results.
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Initially the CFD model was set up for a transient run.
The molten steel in the ladle was considered stationary as
the initial condition. Argon gas was injected through the
purging locations at specified flow rates as per the actual
plant practice. The momentum from the impinging jet stirs
the molten steel bath in the ladle and a fully developed flow
profile gets established after some time (300 secs). The
results so obtained were used as an initial guess and then
solved again iteratively under steady state conditions to
obtain final flow profile in the ladle. The obtained flow
profiles for four different purging configurations (A1, A3,
B1 and C) were compared at a constant argon purging rate
(30 Nm3/h) (table 4).
3. Results and discussion
The rate of mixing in the ladle is affected by the intensity of
stirring which is a function of purging configuration and
argon flowrate. For the same argon flowrate, the purging
configuration which imparts higher stirring over a larger
area in the ladle will give better mixing. Stirring in a ladle
system with purging mechanism is a strong function of the
plume dynamics which causes re-circulation in molten steel
bath. Water modeling experiments were conducted to
measure the mixing time in the ladle for different purging
configurations. Mixing time is an indicator of fluid flow
profile and diffusion characteristics inside the vessel and
should be lower for faster process kinetics. It indicates that
the additions carried out in the ladle during treatment can
be quickly dissolved and thermal and compositional
homogenization is achieved at a faster rate. Figure 5 shows
the time taken for uniform mixing in the ladle under dif-
ferent purging configurations. Dual plugs (A1) yield faster
mixing than single plug (A3). Moreover, in case of dual
plug purging, same-side located porous plugs (A1) give
better mixing as compared to symmetrically located plugs
(A2). Similarly, a single plug located off-centre (A3) gives
better mixing in the ladle as compared to a centrally located
plug (A4). In the case of top lance usage, an inclined lance
(B1) gives a lower mixing time than a vertical one (B2) at
the same location. Similar to the scenario of single plug at
centre (A4), a top lance being used at ladle centre (B3) will
result in highest mixing time among all cases. Krishnaku-
mar et al have also reported that the bath mixing is lower
when purging is carried out from ladle center and gradually
increases as the nozzle is moved to a mid-radius position
[22]. Moreover, the mixing was found to be most sluggish
in case of a top jet
When a top lance is used with a single plug (C), the
mixing time is similar to dual plug purging scenario (A1). It
is evident that purging from off-centre (A1, A3, B1 & B2)
and asymmetric locations (A4) provides faster mixing in
the ladle as compared to central (A4 & B3) or symmetric
(A2) locations. This can be attributed to faster mass transfer
and recirculation rates in these configurations due to the
presence of stronger compositional gradients.
The mixing time studies imply that fastest mixing will be
achieved in the ladle when purging is carried out from two
locations in an asymmetric fashion. The reason for better
performance of these configurations (A1 & C) is demon-
strated in flow visualization studies. As shown in figure 6,
for both these configurations, the tracer gets uniformly
Figure 4. Effect of grid size on velocity measurements.
Table 4. Simulation/solver settings.
Total simulation time (transient run)300 secs
No. of iterations (steady state run) 10000
Advection scheme High resolution
Turbulence numerics High resolution
Transient scheme Second order backward Euler
Convergence criteria Residual type : RMS (target :
0.00001)
Solver scheme Double precision
Figure 5. Effect of different purging configurations on mixing
time.
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mixed at a faster rate as compared to single purging con-
figurations (A3 & B1). Even for a constant argon flow rate,
the mixing is considerably faster in dual purging configu-
rations primarily because of higher momentum being
imparted by the purging gas to the steel bath in the ladle.
This leads to vigorous mixing in the ladle which is reflected
in mixing times for respective configurations.
Flow visualization studies were validated through
mathematical model results by comparing the velocity
vectors for different cases. As shown in figure 7, during
purging from a single plug (A3) or a top lance (B1), the
melt velocities are higher only in the vicinity of the porous
plugs, providing good mixing only near such regions. For
locations away from the purging, the velocities are much
lower making such regions virtually ‘‘dead’’ towards fluid
flow. On the other hand, dual plugs (A1) provide good
recirculation in the ladle both near and away from purging
location. Similar effect is observed in the case when top
Figure 6. Comparison of ladle flow profile.
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lance is used along with a single plug (C). In such a sce-
nario, strong recirculation occurs in the ladle which yields
faster mixing in the ladle.
Even though temperature studies are outside the scope of
present studies, an indication of thermal stratification ten-
dency can be ascertained on the basis of velocities of the
steel melt in the ladle at ‘‘dead regions’’ where very low
mixing takes place. Such regions are located at extreme
ends of the flow streamlines originating from the porous
plugs near ladle walls. Two such locations have been pre-
viously shown in figure 3 as points P1 and P2 located near
ladle walls at half and quarter bath height from the ladle
base. It is imperative to assume that if the downward
velocities at these two locations are higher, faster mixing
will take place in such ‘‘dead regions’’ and hence, the rate
of compositional and thermal homogenization will be
enhanced. Figure 8 shows that velocities at these locations
are much lesser in case of single purging cases (A3 & B1)
but substantially higher in case of dual plug purging (A1).
Top lance with single plug (C) yields highest velocities at
such locations. Hence, fastest bath mixing and
Figure 7. Velocity vectors for different purging configurations (argon purging rate: 30 Nm3/h).
Figure 8. Molten steel downward velocities in dead flow regions
(argon purging rate: 30 Nm3/h).
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homogenization is expected in this case along with lower
thermal stratification.
3.1 Effect of addition location
Figure 9 shows the effect of different locations of the
alloying addition on mixing time for each purging config-
uration. Among all the purging cases, mixing time is lower
when addition is carried out over the plume. It implies that
the alloying additions tend to get ‘carried’ into the steel
melt with a greater momentum thus enabling faster mixing
and homogenization in the ladle. The fastest mixing is
obtained when both plugs operate and addition is done over
the plume over either plug (A1-a). The slowest mixing is
obtained in case of top lance usage with addition opposite
to plume (B1-b). In the case of a top lance being used with
single plug, the mixing times show least variations with
respect to different tracer addition locations (C-a, b, d).
This implies that the rate of mixing is much higher in the
entire volume of the ladle. This is expected to result in
higher alloy dissolution rates irrespective of their addition
location.
3.2 Effect of argon flowrate on bubble size
Argon flow rate plays an important role in governing the
fluid flow dynamics inside the steel ladle as it controls the
size of the generated argon bubbles. Hence, it is an
important criterion for governing the mixing and inclusion
flotation phenomena in the steel ladles during treatment.
There is immense difference in argon bubble formation
pattern between a porous plug (made of refractory block
with fine openings of*0.25 mm) and a top lance due to the
inherent design differences. Compared to the very fine
openings in a porous plug, top lance has a bigger opening
Figure 10. Argon bubble generation for porous plug and top lance.
Figure 9. Effect of tracer injection location on mixing time.
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(*9 mm) for argon injection leading to formation of big
argon bubbles.
Figure 10 compares argon bubble sizes for different
purging rates for a porous plug and a top lance. At lower
argon flow rates (1.3-2.6 l pm), fine sized argon bubbles
are generated and rise upwards in a non-turbulent fashion.
These bubbles provide mild purging to the steel melt and
tend to adhere themselves to the non-metallic inclusions
during ladle treatment and aid in their flotation as reported
by Li et al and Zhang et al [23, 24]. At intermediate
argon flow rates (3.9-5.1 l pm), argon bubbles form a
jacket over the porous plug generating bigger bubbles
which disintegrate into smaller bubbles as they move up.
This phenomenon of disintegration of large gas bubbles
imparts turbulent mixing in the ladle through distribution
of the inherent kinetic energy of rising gas bubbles. It
causes stirring of the steel melt and aids refining reactions
and composition and temperature homogenization. This
range is conducive for providing intermediate stirring in
the bath during later stages of ladle treatment. At higher
argon flow rates ([6 l pm) big bubbles are formed which
impart high momentum to the metal bath resulting in
turbulent mixing and faster homogenization of the steel
melt. Therefore, when high additions are carried out into
the bath and faster mixing is required for quick dissolu-
tion, argon must be purged at high flow rates. However,
too high flow rates don’t provide any additional benefit for
mixing in the ladle as specific consumption of argon is
heavily increased which offsets any additional benefits
[12]. This is because, beyond the critical flow rate, an
invariant flow pattern is established. Mandal et al have
reported that the critical flow rate corresponds to the onset
of the inertial and gravitational force dominated flow
regime [20]. When argon purging is carried out using a
top lance system, only big argon bubbles are formed at
both low and high flow rates. Thus, even though bath
mixing can be achieved, inclusion flotation is expected to
be highly diminished.
Figure 11 compares the argon bubble size distribution for
a porous plug and a top lance highlighting the minimum
and maximum size of the generated bubbles. Effective
bubble size for each case was calculated using the weighted
average from extreme size ranges and their relative con-
centration. It can be noted that the difference between
minimum and maximum bubble sizes is smaller at lower
purging rates. This is because at lower purging rates only
smaller bubbles are formed. At higher purging rates, bigger
bubbles are formed which get dissociated into smaller
bubbles due to the higher turbulent energy of the bath as
also been reported by Zhang et al [24]. This effect is more
pronounced for a top lance where only big bubbles are
observed at lower argon flow rates and both small and big
bubbles at higher purging rates. In such a scenario, even
though small bubbles are generated, their effect on inclu-
sion floatation is minimal due to the highly turbulent con-
ditions in the bath.
During initial stages of treatment, high argon flow rate is
preferable as it allows for faster mixing in the ladle. Con-
sequently, the alloying additions get homogenously mixed
at a faster rate thereby increasing their recovery. It results in
faster reaction kinetics and supports the refining processes.
On the other hand, too high flow rates during later part of
treatment might cause slag emulsification in the ladle and
open eye formation at the top surface of the ladle exposing
the molten steel to atmosphere leading to oxygen and
nitrogen pickup as also reported by Hoang et al and
Krishnapisharody et al [25, 26]. Therefore, lower flow rates
are desirable during later stages of the treatment so as to
generate small argon bubbles which help in inclusion
flotation to obtain ‘‘cleaner’’ steel. Due to the formation of
small bubbles at lower purging rates, porous plugs are
Figure 11. Argon bubble sizes for (a) porous plug and (b) top
lance.
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expected to be more effective for inclusion floatation as
compared to a top lance.
4. Plant scale validation
The industrial process is more complex and has other
additional variables which affect directly or indirectly the
mixing efficiency such as bath depth, temperature, top slag
layer etc. It is therefore important to validate the results at
the plant scale under the operating conditions which helps
in analyzing the limitations regarding the direct application
in practice.
For validation of lab scale studies, plant trials at ladle
heating furnace (LHF) in steel making shop were per-
formed for different purging configurations keeping other
operating parameters unchanged. After ladle treatment was
finished, lollypop samples were collected from the ladles.
Post treatment, the ladles were transferred to continuous
casting station. During continuous casting, at 50% ladle
weight, one additional sample was taken from the tundish
near shroud (metal entry) region. These samples were cut,
fine polished and observed under optical microscope to find
out inclusion area fraction through optical image analysis.
For each sample, a number of frames were captured to
cover the overall sample area. Out of these frames, 10 worst
frames showing the maximum number of inclusions were
selected for further analysis. Figure 12 shows the repre-
sentative frames from LHF lollypop samples showing the
inclusion distribution for different purging configurations at
100 x magnification.
The average inclusion area fraction comparison for each
of the purging configurations shown in figure 13 clearly
suggest that double plug purging has maximum effect on
inclusion flotation in the ladle evident from the lowest
values of inclusion area percentage in LHF as well as caster
samples. The samples with top lance purging show maxi-
mum inclusions indicating a lower degree of inclusion
Figure 12. Micrographs showing steel cleanliness for LHF lollypop samples for different purging configurations (argon purging rate =
20 Nm3/h).
Figure 13. Comparison of inclusion area fraction for different
purging configurations (argon purging rate = 20 Nm3/h).
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flotation in case of top lance purging. In line with water
model experiments, the plant trials also suggested that
usage of top lance along with single plug for argon purging
yields nearly similar effect as obtained from dual plug
purging. Thus faster bath mixing along with good inclusion
floatation can be achieved.
On the basis of plant trials, it was evident that in the case
of purging failure from one of the plugs, the mixing time as
well as inclusion flotation in the ladle can be improved by
using top lance for argon purging along with the single
operative plug.
5. Conclusion
To investigate the role of different configurations of porous
plus and top lance on fluid flow and mixing time in the ladle,
water modeling and CFD studies were carried out. The effect
of argon purging flow rates and relative location of porous
plugs on mixing kinetics in the ladle were studied. The opti-
mum location and conditions for usage of a top lancewere also
investigated.On the basis of the results obtained throughwater
modeling and CFD studies, it was concluded that:-
1. Argon purging through dual porous plugs gives the least
mixing time in the ladle followed by single plug purging.
Usage of a top lance results in highest mixing time
among all cases.
2. Asymmetric location of argon purging gives faster
mixing in the ladle as compared to central location.
3. Additions in the ladle must be carried out over the plume
to achieve lower mixing time and faster dissolution of
alloying additions.
4. Whenpurging fromoneof the porousplugs fails, a top lance
can be used in combination with the lone working plug to
achieve mixing time equivalent to dual plug purging.
5. Purging from two locations is expected to result in faster
compositional and thermal homogenization in the ladle
owing to strong steel melt velocities in relatively dead
flow regions in the ladle.
It is quite evident that the current asymmetric location of
dual plugs yields the best mixing time. The mixing time is
greatly reduced in case purging from one of the plugs fails.
In such a case, for non-critical steel grades, single plug
purging can be sufficient to achieve the desired cleanliness
levels. However, for critical grades, a top lance should be
used along with the lone working plug to achieve faster
mixing in the ladle along with higher levels of steel
cleanliness. Usage of a top lance alone is not recommended
and should be avoided as much as possible.
Symbols
CPC Calcined petroleum coke
LHF Ladle heating furnace
g Gravitational acceleration
t Time
T Temperature
CD Drag coefficient
Re Reynolds number
d Distance or length
db Mean particle diameter of phase bAab Interfacial area density
p Gauge pressure
Pk Turbulence production due to viscous forces
r Location vector
rb Volume fraction of phase bSM Momentum source
SM;buoy Momentum source due to buoyancy
Pkb, Peb Buoyancy production & dissipation terms
(represent influence of the buoyancy forces)
Ce1, Ce2 k � e Turbulence model constants
u Fluctuating velocity component in turbulent
flow
U Vector of velocity Ux;y;z
Ut Turbulent velocity scale
lt Turbulence length scale
a Subscript indicating phase ab Subscript indicating phase bq Density
qref Reference density
rk Turbulence model constant for the k equation
re k � e Turbulence model constant
s Shear stress
d Identity matrix or Kronecker Delta function
k Turbulence kinetic energy per unit mass
e Turbulence dissipation rate
l Molecular (dynamic) viscosity
lt Turbulent viscosity
r Gradient
� Scalar product
� Tensor product
db Bubble diameter
Q Flowrate (Nm3/s)
Acknowledgement
The authors would like to thank secondary steelmaking
operations team at JSW Steel Ltd. Vijaynagar Works for
the help and support extended during this study.
References
[1] Mazumdar D and Guthrie R I L 1995 The Physical and
Mathematical Modelling of Gas Stirred Ladle Systems. ISIJInt. 35: 1–20
Sådhanå (2021) 46:146 Page 13 of 14 146
![Page 14: Optimization of bath mixing and steel cleanliness during](https://reader030.vdocuments.site/reader030/viewer/2022013022/61d186f5b398ab10784cbc86/html5/thumbnails/14.jpg)
[2] Mazumdar N, Mahadevan A, Madan M and Mazumdar D 2005
Impact of Ladle Design on BathMixing. ISIJ Int. 45: 1940–1942[3] Castello-Branco Marco A S C and Schwerdtfeger K 1994
Large-scale measurements of the physical characteristics of
round vertical bubble plumes in liquids. Metallurgical andMaterials Trans. B 25: 359–371
[4] Sahai Y and Guthrie R I L 1982 Hydrodynamics of gas
stirred melts: Part II. Axisymmetric flows. Metallurgical andMaterials Trans. B 13: 203–211
[5] Dian-qiao Geng, Lei H and Ji-cheng He 2010 Optimization
of mixing time in a ladle with dual plugs. InternationalJournal of Minerals, Metallurgy and Materials 17: 709–714
[6] Schwarz M P 1996 Simulation of gas injection into liquid
melts. Applied Mathematical Modelling 20: 41–51
[7] Haiyan T, Xiaochen G, Guanghui Wu and YongW 2016 Effect
of Gas Blown Modes on Mixing Phenomena in a Bottom
Stirring Ladle with Dual Plugs. ISIJ Int. 56: 2161–2170[8] Xie J, Zhu X, Liao Q, Wang H and Yu-Dong Ding 2012
Dynamics of bubble formation and detachment from an
immersed micro-orifice on a plate. International Journal ofHeat and Mass Transfer 55: 3205–3213
[9] Cao Q and Nastac L 2018 Mathematical Investigation of
Fluid Flow, Mass Transfer, and Slag-steel Interfacial
Behavior in Gas-stirred Ladles. Metallurgical and MaterialsTrans. B 49: 1388–1404
[10] Patil S P, Satish D, Peranandhanathan M and Mazumdar D
2010 Mixing Models for Slag Covered, Argon Stirred
Ladles. ISIJ Int. 50: 1117–1124[11] Amaro-Villeda A M, Ramirez-Argaez M A and Conejo A N
2014 Effect of Slag Properties on Mixing Phenomena in Gas-
stirred Ladles by Physical Modeling. ISIJ Int. 54: 1–8[12] Gonzalez-Bernal R, Solorio-Diaz G, Banderas J A R, Torres-
Alonso E, Hernandez-Bocanegra C A and Zenit R 2018
Effect of the Fluid-Dynamic Structure on the Mixing Time
of a Ladle Furnace. Steel Research Int. 89: 1700281[13] Chen M, Wang N, Yao Y, Geng J and Xiong K 2008
Optimal Mixing Effect of LF Bottom-Blown Stirring by Two
Nozzles. Steel Research Int. 78: 468–472[14] Liu Z, Li L and Li B 2017 Modeling of Gas-Steel-Slag
Three-Phase Flow in Ladle Metallurgy: Part I Physical
Modeling. ISIJ Int. 57: 1971–1979[15] Ganguly S and Chakraborty S 2008 Numerical modelling
studies of flow and mixing phenomena in gas stirred steel
ladles. Ironmaking & Steelmaking 35: 524–530
[16] Fan C M and Hwang W S 2002 Study of optimal Ca-Si
injection position in gas stirred ladle based on water model
experiment and flow simulation. Ironmaking & Steelmaking29: 415–426
[17] Gomez A S, Conejo A and Zenit R 2018 Effect of separation
angle and nozzle radial position on mixing time in ladles
with two nozzles. Journal of Applied Fluid Mechanics 11:
11–20
[18] Chattopadhyay K, SenGupta A, Ajmani S K, Lenka S N and
Singh V 2009 Optimisation of dual purging location for
better mixing in ladle: a water model study. Ironmaking &Steelmaking 36: 537–542
[19] Yang F, Jin Y, Zhu C, Dong X, Lin P, Cheng C, Li Y, Sun L,
Pan J and Cai Q 2019 Physical Simulation of Molten Steel
Homogenization and Slag Entrapment in Argon Blown
Ladle. Processes 7: 479[20] Mandal J, Patil S, Madan M and Mazumdar D 2005 Mixing
time and correlation for ladles stirred with dual porous plugs.
Metallurgical and Materials Trans. B 36: 479–487
[21] Johansen S T and Boysan F 1988 Fluid dynamics in bubble
stirred ladles: part II. Mathematical modeling. Metallurgicaland Materials Trans. B 19: 755–764
[22] Krishnakumar K, Ballal N B, Sinha P K, Sardar M K and Jha
K N 1999 Water Model Experiments on Mixing Phenomena
in a VOD Ladle. ISIJ Int. 39: 419–425[23] Li L, Liu Z, Li B, Matsuura H and Tsukihashi F 2015 Water
Model and CFD-PBM Coupled Model of Gas-Liquid-Slag
Three-Phase Flow in Ladle Metallurgy. ISIJ Int. 55:
1337–1346
[24] Zhang L, Aoki J and Thomas B G 2006 Inclusion removal by
bubble flotation in a continuous casting mold. Metallurgicaland Materials Trans. B 37: 361–379
[25] Hoang Q N, Ramırez-Argaez M A, Conejo A N, Blanpain B
and Dutta A 2018 Numerical Modeling of Liquid-Liquid
Mass Transfer and the Influence of Mixing in Gas-Stirred
Ladles. The Journal of The Minerals, Metals & MaterialsSociety 70: 2109–2118
[26] Krishnapisharody K and Irons G A 2006 Modeling of slag
eye formation over a metal bath due to gas bubbling.
Metallurgical and Materials Trans. B 37: 763–772
[27] Pfister M and Hager W H 2014 History and Significance of
the Morton Number in Hydraulic Engineering. Journal ofHydraulic Engineering 140: 02514001
146 Page 14 of 14 Sådhanå (2021) 46:146