FIELD OF THE INVENTION
The present invention generally relates to determining clogging inside
submerged entry nozzle (SEN) used to deliver the molten metal from tundish
to mold via a stopper rod controlled flow mechanism. More particularly, the
present invention relates to a method for real-time estimation of the
percentage of deposition of nonmetallic inclusions.
BACKGROUND OF THE INVENTION
Generally, in a steel making process, a tundish is used as a buffer vessel
where the molten steel is continuously delivered from the ladle and injected
to the mold. A submerged entry nozzle (SEN) is connected between the
tundish bottom and the mold to discharge the molten metal from tundish to
mold without any contact with the air. Also, a stopper rod is installed inside
the tundish to regulate the flow of molten metal by controlling the opening
area of the tundish well available for flow of molten steel.
Deposition of nonmetallic inclusions in the nozzle, known as nozzle clogging,
is a long standing problem in a continuous casting of steelmaking. Alumina
inclusions in Al-killed steels, CaS inclusions in Ca treated steel and TiN
inclusions in Ti-killed steels are the examples of major inclusions that cause
clogging inside the SEN as well as in tundish outlet.
Due to continuous buildup of clogged materials, the SEN tube gets choked
and fails to deliver a desired flow rate to the mold. Thus, in every 3-4 heats,
the tube get choked due to clogging and replaced by a new one. Also, after a
few heats, the tundish gets clogged and needs replacement.

In addition to that, in course of the casting process, the inclusions gradually
gets deposited on the inner side wall as well as the ports of the SEN. The
blockage of the port due to clogging leads to asymmetric flow in the mould,
thus increasing meniscus fluctuation in the mould. Increase in mould level
fluctuation results in many casting defects and adversely affect the process
economics.
Several prior art methods are known to minimize clogging. One of the
known methods uses an inert gas supplied through the stopper rod tip, which
flushes away the clogged materials during casting. However, the amount and
location for supplying the inert gas is completely based on operator's
experience without conducting any pre-estimation of the clog amount and an
appropriate location of supplying inert gas during the course of casting. To
minimize casting defects due to nozzle clogging, it is important to determine
when to change a tube, a tundish and when to flush the tube. However, the
prior art do not teach any precise and accurate method to determine these
influencing factors, and a decision is generally based upon operators'
experience and hence, is susceptible to human error.
N. U. Girase ef al[1] have calculated nozzle clogging index by comparing the
theoretical flow rate inside the nozzle with the actual throughput value, which
is the ideal flow rate in the absence of clogging. This method uses
mathematical equation to estimate the theoretical flow rate throughout the
process. The major drawback of this method is the initial calibration of
stopper position which is practically difficult due to erosion and deposition of
clogged material during the process of casting.
Moreover, summation of discontinuity of stopper rod position [2], ratio
between number of increments to no. of drops have been used to define the
clogging index. F. Yuan et al.[3] used the method of regression to find the

clogging index based on stopper rod position. However, clogging index is
based on stopper rod position valid for constant tundish weight period and
won't be valid for tundish change over period. Also this method doesn't tell
about the method of capturing the data used for regression equation.
In light of the above, there is a need of a method than enable operator to
take a decision on SEN tube change, tundish change and flushing time. For
example if the clogging index shows the value beyond the threshold limit, the
operator can go for tube change or tundish change or inert gas flushing
accordingly. Similarly if the clogging index shows lower value, the operator
should continue casting without changing the tube or tundish change.
OBJECTS OF THE INVENTION
It is therefore an object of the invention to propose a method for real-time
estimation of the percentage of deposition of nonmetallic inclusions inside the
submerged entry nozzle.
Another object of the invention is to propose a method for real-time
estimation of the percentage of deposition of nonmetallic inclusions inside the
submerged entry nozzle, which minimizes casting defects due to nozzle
clogging.
Still another object of the invention is to propose a method for real-time
estimation of the percentage of deposition of nonmetallic inclusions inside the
submerged entry nozzle, which allows the operator to take an accurate and
precise decision on SEN tube change, tundish change and flushing time.

SUMMARY OF THE INVENTION
Accordingly, there is provided a method for real-time estimation of the
percentage of deposition of nonmetallic inclusions inside the submerged
entry nozzle.
In accordance with the inventive method, SEN-clogging is quantified during a
continuous casting of steel in real time. In this invention, a least square
method is used to develop an empirical equation by taking stopper position,
tundish weight and actual throughput as dynamic process variables to
estimate the theoretical flow rate of molten steel discharges to the mold at
the beginning of the each casting sequence (1stheat of the tundish
sequence). The empirical equation is tundish specific and the equation is
developed at the beginning of casting sequence. This equation is further used
to calculate the clogging index in rest of the heats in the tundish.
Further, the clogging index is calculated based on the ratio of difference in
actual flow rate and theoretical flow rate, (estimated by the empirical
equation developed at the beginning of the casting sequence) to the
theoretical flow rate. The decision of tube change, tundish change and
flushing time can be decided based on the clogging index value.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
Fig. 1 is a schematic view of submerged entry nozzle (SEN) which connects
tundish and mould.
Fig. 2 is a flowchart illustrating the method of calculating clogging index
during the process of casting operation.

Fig. 3 shows the method of capturing the data for developing the equation in
the 1st heat of the sequence.
Fig. 4 is a graph showing the outcome of the equation (without tundish
weight correction) developed by regression analysis during initial period of
casting sequence.
Fig. 5 is a graph showing the relationship between the tundish weight and
height of molten steel in the tundish.
Fig. 6 shows the relationship between the stopper position (lift) and the area
of opening available for flow of molten steel.
Fig. 7 shows the online output of the clogging index model in a caster.
Fig. 8 shows the clogged SEN collected after 1st tube replacement.
DETAILED DESCRIPTION OF THE INVENTION
The present invention focuses on a methodology to calculate clogging index
online in continuous casting of steelmaking. Clogging index is ratio of
difference in theoretical and actual flow rate to the theoretical flow rate of
molten steel.
Clogging index= l-(Qact/Qth) (1)

Where Qth is the theoretical molten steel flow rate inside SEN tube and Qact
is the actual molten steel flow.
In the present invention a statistical methodology is adopted to predict
clogging index online in the caster. In this methodology at every start of
tundish in operation a model equation is developed based on the actual flow
rate, stopper position, tundish weight, which is used to predict theoretical
flow rate in the rest of the casting sequence.
Once the model/ is developed the clogging index value can be estimated for
the rest of the heats in the sequence of casting.
The methodology consists of two parts. First part is to develop the
developing a linear equation based upon captured data of Qac and stopper
opening ratio using least square method. Second part is for predicting
clogging index in the rest of the sequence.
Linear equation in the first part is developed assuming that there is no
clogging at the start of casting sequence and actual flow rate is equal to
theoretical flow rate (Qth). The data for developing the linear equation is
retrieved for 15 minutes when tundish weight is stabilized as shown in figure
3.
Example of 1st heat regression based on only stopper position
Model Equation: Theoretical Flow rate=A*(stopper position) + B (2)
Values of A and B are calculated in the first heating cycle and are used one
sequence.
Values of A and B are tundish specific and determined every time tundish is
changed.

Figure 4 depicts the development of model equation for calculation of
theoretical flow rate with average tundish weight=30.69 tonne.
Modeling of Tundish weight:
In order to account the tundish weight effect on clogging index prediction, a
relationship between tundish weight and molten steel height is calculated.
The relationship is given in Fig. 5. The relationship is used to convert the
tundish weight (tonne) into height (m).
Qth is calculated using the equation below:
Qth=A*(actual tundish height/stabilized tundish height) 0.25* stopper
position + B
Values of A and B are determined already from equation 2 and stopper
position can be retrieved from caster wherein Qactis calculated from the
available information as below:
Qact = mould cross sectional area*casting speed*psteel(7800kg/m3)
Once Qth and Qact are known, the value of clogging index can be calculated as
given in equation 1.
Further, a data capturing algorithm is developed to formulate the regression
equation. This data capturing system optimizes the time period of data
collection, mode of data and filtering of data to give the correct prediction.
Example:

The developed methodology was used to calculate the nozzle clogging in real
time and data was captured as shown in figure 7.
Referring to the Fig. 7 the clogging index value has dropped from 0.4 to 0
after change of 1st tube. However, after changing of 2nd tube the clogging
index value has decreased to 0.3 which indicates that 30% of clog is in the
tundish well and stopper tip. Refer to the Fig 7., at 7th hour flushing, clogging
index value has been decreased from 0.5 to 0.3. After 4th heat the clogging
index value shows the value close to 0.4. Thus tube changing decision has
been made.
At the end of 13th heat the clogging index value shows the value close to 0.6,
which has crossed the threshold limit. Thus changing of tube won't decrease
the clogging value as more clogging in the tundish out-let. Accordingly
tundish change decision has taken at the end of 13th heat.
Fig. 8 depicts a clogged SEN tube. The measured value (when taken off)
shows about 30% wherein the inventive process of the current invention
estimates 36% deposited in SEN tube and tundish well, demonstrates the
acceptability of the developed method.
According to the present invention, it is possible to improve the casting yield
by taking suitable actions like tube change, tundish replacement and flushing
to minimize clogging as well as the quality of final slab. Calculated Qth is
tundish specific and gives better prediction. Incorporation of tundish weight
to calculate the Qth nullifies the error of prediction of clogging index during
the change in molten steel weight in the tundish.

WE CLAIM:
1. A method for on-line measuring of clogging index in a submerged entry
nozzle (SEN), the method being implemented in continuous casting
process, and comprising:
calculating actual flow rate of molten steel (Qac);
developing a linear equation based upon captured data of Qac and
stopper opening ratio using least square method, linear equation is
developed assuming that there is no clogging at the start of casting
sequence and actual flow rate is equal to theoretical flow rate (Qth);
calculating the continuous change in tundish weight by establishing
relation between tundish weight and tundish height, and converting
tundish weight to tundish height using a liner equation;
integrating tundish height factor in to the linear equation used to
calculate the theoretical flow rate;
measuring clogging index by calculating ratio of difference in
theoretical (Qth) and actual flow rate to the theoretical flow rate of
molten steel wherein, the theoretical flow rate of molten steel is
calculated using the equation below:
Qth =A*(actual tundish height/stabilized tundish height) 0.25 *stopper
position + B
Wherein values of A and B are calculated in the first heating cycle
using regression equations and are used for one sequence.
2. The method as claimed in claim 1, wherein the values of A and B are
tundish specific and determined every time tundish is changed.

3. The method as claimed in claim 1, wherein a decision on SEN tube
change, gas flushing, tundish change can be taken based upon a
predefined value of clogging index.
4. The method as claimed in claim 1, wherein the actual flow rate of molten
steel (Qac) is calculated based upon mould cross sectional area, casting
speed, and steel density.
5. The method as claimed in claim 1, wherein clogging index is calculated
continuously with a frequency of 5 seconds.
6. The method as claimed in claim 1, wherein linear equation based upon Qac
and stopper opening ratio using least square method is developed based
upon the data retrieved for 15 minutes when tundish weight is stabilized.

ABSTRACT

The present invention relates to a method of predicting the clogging index. The clogging index is an indicator of the degree of deposition of non-metallic inclusions inside submerged entry nozzle (SEN) tube, during continuous casting of steel. This invention includes online capturing of stopper position,
tundish weight, actual throughput, mould cross-sectional area data from the control system and uses the data to predict the clogging index. The predicted clogging index is then used as decision enabler for inert gas flushing to the
casting nozzle, decision of tube and tundish replacement in the casting process.