# The optimisation of the secondary cooling water distribution with improved genetic algorithm in continuous casting of steels

Abstract: An improved genetic algorithm is presented for the water consumption of the secondary cooling zone based on the heat transfer model of the off-line bloom caster. This study is to control the existing cooling systems and the steel casting practises in order to produce steel with best possible quality. The fitness function of improved genetic algorithm is founded according to the metallurgical criteria. This algorithm coupled with heat transfer model and metallurgical criteria, added dynamic coding method and self-adapting mutation on the original genetic algorithm can increase water distribution adaptively and improve the process efficiency. The simulation results of T91 bloom show that the optimised distribution reduced by 2% of water consumption comparing to that of before optimisation. The maximum surface cooling rate and the rate of temperature rise reduced, and the equiaxed rate increases. The function is built for explaining the relationship between the casting speed and water distribution.

## Summary (2 min read)

### Introduction

- Continuous casting technology, a main method in steelmaking industry, has been rapidly developed in recent years.
- Given that the cooling process removes the superheat and the latent heat of fusion at the solidification front, the main cause of internal crack, surface crack and center segregation is the unreasonable secondary cooling structure.
- These defects should be avoided for the sake of competitiveness in manufacturing.
- A number of intelligent optimization methods used in the secondary cooling process have been developed rapidly.
- This study presents an optimization model for controlling the water intensities of the water in the SCZ of bloom caster.

### The Mathematical Optimization Model

- The state system used in the present study is a two-dimensional heat transfer model in which the heat conduction to the withdrawal direction is neglected.
- Suppose that the cross section of the bloom is a rectangular, Ω=[0, a]×[0, b], which is moving along the z direction with a constant speed.
- Then T satisfies the following nonlinear heat conduction equation with boundary conditions [10].
- The heat of liquid iron is transferred from the surface in the continuous casting process.
- The cooling water flow rate temperature is difference between the inlet and outlet of the mold.

### Metallurgical criteria

- The surface quality is related to the fluctuations of the surface temperature, the reheating temperature between zones and the cooling ratio.
- Limiting the surface temperature above the upper limit of the low ductility region, transversal cracking is also reduced.
- The maximum permissible reheating rate Cp and the maximum cooling ratio CN along the machine are chosen to be 100°C/m and 200°C/m in order to avoid midway surface cracking.
- (11) Since the differences between units of objective functions, it is to make the objective functions uniformization.
- This algorithm is likely to result in large mutation probability in the initial stage, which is used to produce new individual.

### Application and Discussion

- The improved GA coupled with the heat transfer model has been applied in a bloom caster.
- The parameters of the IGA optimized process are designed the initial population is 30, the maximize number of evolutionary computation is 100, the length of chromosome is 128, and the individual number is 4.
- Fig. 3(a) shows a comparison between the surface and central temperatures before and after optimization.
- The optimized water distribution is more reasonable, which reduces stress cracks.
- (a) Strand temperature (b) Shell thickness Fig. 3 Strand temperature and shell thickness before and after optimization with casting speed of 0.6 m min -1.

### Conclusions

- A heat transfer model is developed based on the bloom caster, in which the error is controlled less than 5% compared to the measured temperature.
- It is evident that the application of IGA with a heat transfer model to simulate optimal operating conditions for a steel continuous caster is a powerful tool for optimizing the water flow of the secondary cooling process.
- The simulation generated by the IGA shows the modifications, which corresponds with the model quality and reduction in water consumption.
- The IGA with adaptive method in the crossover and mutation process can improve the optimized efficiency of the algorithm.
- It is found that the water consumption after optimization reduced by 2%, compared to that of before optimization.

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### Cites background from "The optimisation of the secondary c..."

...Many other studies were also conducted to determine the relationship between pump operation and load demands, and a series of optimal control strategies were investigated to achieve potential energy saving (Dai et al. 2015; Yang et al. 2014; Zhai et al. 2015)....

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