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: civs@purduecal.edu

www.purduecal.edu/civs/