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CFD ANALYSIS OF BATCH-TYPE REHEATING FURNACE FOR IMPROVED HEATING PERFORMANCE
Bin Wu2, Tom Roesel1, Andrew M. Arnold1, Eugene Arnold3, George Downey lll3 and Chenn Q. Zhou1,2
1Department of Mechanical Engineering, 2Center for Innovation through Visualization and Simulation
Purdue University Calumet, 2200 169th Street, Hammond, IN 46323, USA 3ArcelorMittal-USA, Steelton, PA 17113
Abstract
Objective
Approach
Results and Discussion
Sponsors & Collaborators
Conclusions
Figure 6. Temperature Distribution Cross the Furnace
(Base Case)
Figure 6. Temperature Distribution Cross the Furnace
(Base Case)
Figure 2. Temperature distribution Figure 3. Streamline distribution
Table 1. Components for Two Types Fuels Table 1. Components for Two Types Fuels
To develop a 3D reacting CFD model of a reheating furnace.
To determine the hot flue gas flow patterns in the furnace by
analyzing the simulation results.
To simulate the whole heating process and examine the transient
three dimensional temperature fields in the number three reheat
furnace at ArcelorMittal.
To conduct parametric study to optimize the furnace operation.
In this CFD study, single phase steady state reacting flow had been
modeled. The realizable k-ε turbulence model had been used to describe
the turbulent features of the gas phase. For the natural gas combustion
modeling, the Probability Density Function (PDF) has been introduced
during the preheating process simulation. while the heat transfer through
radiation has been simulated using the Discrete-Ordinates model and P-1
model. The kinetics are shown below:
Table 1. Boundary Conditions of Regenerative Furnace
The major boundary conditions is shown in Table 1. These are directly
provided by the plant operators.
Charging Process
The next step in the analysis is to simulate the charging process during which
the furnace operation is in an unsteady state. For both furnaces, it takes 34
seconds to charge each billet. Of those 34 seconds, 17 pass with a door open,
and 17 with it closed before the next billet is charged. The doors operate
continuously while the billets are being charged into the furnace. For
comparison, the temperature profiles (K) are shown in Figure 4 for regenerative
furnace after 17 seconds have passed. By comparing with the previous old
furnace result, it is evident that the flame nearer to the door has moved
towards the door when it is opened, due to the change in the flow field.
However, the furnace that operates with regenerative burners has almost no
change in the temperature distribution with the opening door. The streamline
describes the similar trend of change in flow field in Figure 4 and 5. During the
operation, heat loss with the outflow through doors is inevitable. The same
phenomenon also influences the temperature along the length of the furnace
by shrinking the zone of high temperature when the door is held open,
especially in the traditional furnace.
Preheating Process
During the preheating of the furnace, all the doors are closed. The first step in
the simulation is the steady state case for the given initial combustion
conditions. The burners start firing from the left hand side of the furnace, and
every 40 seconds the firing side is converted from one side to the other. The
two seconds of down time has been taken into account by these simulations.
This process continues until the temperature at the center of the furnace
reaches steady state. The simulated temperature field with regenerative
burners is shown in Figure 2. The flame shape is shown on both the side view
and top view in planes associated with the burners. The streamline in Figure 3
shows the flow movement within the furnaces. By closely observing, it is
obvious that the regenerative burners provide more gas recirculation inside the
furnace and achieve higher temperatures.
Introduction
A reheating furnace is a critical component in value-added steel production.
These furnaces can have a significant impact on both product quality and
total cost. In order to obtain a better understanding of the furnace operation
which influences the temperature distribution, a Computational Fluid
Dynamics (CFD) analysis has been conducted to examine the transient and
three dimensional temperature fields in a prototype of the number three
reheating furnace located at ArcelorMittal. Also, a series of simulations
have been conducted to maximize the furnace performance. These
parametric studies include different burner designs, fuel flow rates, and
combustion air supplies to optimize the heating capacity of the furnace. The
comparison of the simulation results assists in understanding the effective
factors which are critical to the improvement of the furnace’s production
capacity, thus providing insight into furnace optimization.
Heating Process
After all the billets have been charged, all the doors are closed and the
heating process takes approximately 20 minutes. During the heating
period, the transient temperature of the billets has been monitored and this
provides precise information on the heating progress. The transient
average temperature of each billet has been recorded for quality control
and energy efficiency calculation. The transient average temperature of
twelve billets is shown in Figure 5. From the simulation, it has been
observed that it took around 20 minutes to heat the billet from 1900F to
2100F. This heating period has a good agreement with industrial data
provided by ArcelorMittal. From this recording, all the resident times can be
exactly controlled by the temperature monitoring.
Similarly, all the 32 billets in the new furnace have also been monitored
during the whole heating process. Figure 11 describes the heating progress
of all bars in new furnace. It takes around 1000 seconds to heat the first
billet up to 2100F. And unlike the old furnace, the charging process of the
new furnace alone needs 1088 seconds to finish, thus the first billet is
discharged while the fourth door zone is still undergoing charging process.
Compared with the traditional furnace, the regenerative burners heat the
billet up to 2100F within 1000 seconds, is much faster than the old furnace
performance.
The authors would like to thank ArcelorMittal for partially funding this work.
A reheating furnace is a critical component in value-added steel production.
These furnaces can have a significant impact on product quality and total
cost . The main function of the reheating furnace is to provide a uniform
heating environment for the billets or blooms that are obtained from the
continuous casting process. In the furnace, the billets are heated to the
rolling temperature at which the billets can be rolled into a variety of
shapes, such as the I-beams, channels, wire, rods etc. in the hot rolling mill.
The uniformity of the target temperature on the billets determines the
quality of the steel. During the heating process, the temperature distribution
inside the furnace has a significant influence on the temperature uniformity
of the billets. The residence time of the billets in the furnace is equally
essential to the quality control process. Thus it is important to monitor the
transient temperature to avoid over or under heating. However, it is
exceedingly difficult to directly measure and examine the transient
temperature distribution of the furnace as well as the billets. Therefore
attempts at optimization may be based on experience and trial and error.
This may not be the most efficient method, and may have drawbacks such
as large energy losses and ineffectiveness. Effective optimization of the
reheating furnace performance with increased efficiency and lower energy
losses requires a better understanding of the flow characteristics and
temperature distributions inside the furnace. The achievement of high
product quality requires close monitoring of temperatures on the billets
during the heating process and is essential in the current steel industry .
Computational Fluid Dynamics (CFD) has been identified as the most
suitable technology that can be used to analyze and optimize the heating
process; and to improve the efficiency and performance of reheating
furnaces as well as the product quality. In this paper, a three-dimensional
(3-D) computational fluid dynamics (CFD) model has been developed from
a prototype of the No.3 Reheating furnace at ArcelorMittal Steelton which is
shown in Figure 1.
Figure.1. Charging and discharging operation of reheating furnace
225.0 COOCO
225.0 COOCO
Firing sequence 40 s
Switching down time 2 s
Mass flow rate of air at each burner 0.558965 kg/s
Mass flow rate cooling air at each burner 0.02795 kg/s
Mass flow rate of natural gas at each burner 0.0282 kg/s
Dimension of billets 180 × 7.5 × 11 in
Number of billets at each zone 8
Total number of Billets 32
Figure 4. Temperature distribution
of new furnace, at 17 seconds when
1st door is opening
Figure 5. Streamline distribution of
new furnace, 1st door open
Figure 5. Transient average temp
for twelve billets, old furnace with
traditional burners
Figure 6. Transient average temp for
thirty two billets, new furnace with
regenerative burners
it is very important to simulate the furnace operating conditions with different
burner capacities, especially different fuel and air flow rates. In the interests
of better understanding of the effects of different fuel and air rates on furnace
performance, the series of fuel and air flow rates that listed in Table 2 have
been simulated.
Parametric Studies of the New Furnace
Case
No.
Burner
Capacity
Natural Gas
(kg/s)
Combustion Air
(kg/s)
Cooling Air
(kg/s)
1 100% 0.1692 3.3537 0.1677
2 75% 0.1269 2.5151 0.1258
3 60% 0.1015 2.0123 0.1006
4 50% 0.0846 1.6769 0.0839
5 30% 0.0508 1.0061 0.0503
6 25% 0.0423 0.8385 0.0425
Table 2. Boundary Conditions of Different Burner Capacity
From Figure 7 (a) to (f), the temperature distributions of the furnace with the
different burner capacities can be easily observed. With the decrease of the
fuel and air flow rates, the shrinkage of the flames is very obvious, as well as
that of the high temperature zones.
(a) Temperature distribution with
the capacity of 100%
(b) Temperature distribution with the
capacity of 75%
(c) Temperature distribution with
the capacity of 60%
(d) Temperature distribution with the
capacity of 50%
(e) Temperature distribution with the
capacity of 30%
(f) Temperature distribution with the
capacity of 25%
A 3-D transient turbulent reacting CFD model has been developed to
simulate the whole process of the reheating furnaces with traditional
burners and regenerative burners.
The transient 3-D temperature field and velocity distribution has been
obtained and the influence of doors operating was also considered.
The temperature of the walls has been compared with the data
provided from industry and a good agreement has been obtained.
It has been seen that the regenerative burners are quite efficient and
effective. The regenerative burners increase the furnace efficiency by
reducing heating time.
The door effect has been minimized by trimming the fluid flow within
the furnace. The temperature inside the entire furnace achieves a
more even distribution which in turn improves the product quality.
The minimum burner capacity has been achieved with series of
different energy inputs. This can reduce the energy consumption and
maintain effective heating performance simultaneously.
By monitoring the surface, core and average temperature of the billets,
the whole heating progress for the billets has been observed.
The temperatures in the core and on the surface experience
convergence twice with the non-uniform charging while the uniform
charging only has one convergence at the end of the heating process.
The comparison of these two initial charging conditions shows that the
non-uniform charging has higher heating speed than the uniform
charging.
Figure 7.
CONTACT
Director: Prof. Chenn Q. Zhou
Phone: (219)989-2665
Email: [email protected]
www.purduecal.edu/civs/