Study On Mathematical Modeling Of Solidification And Heat Transfer In Continuous Casting Of Bloom And Optimization For Cooling Water

With the growing number of the bloom caster put into operation in recent years and continuous casting bloom production gradually increased, the quality of the bloom is more and more the attention of casting workers. Due to the characteristics of the bloom: a large section size, a large solidified shell linear shrinkage, a large heat capacity, a long liquid core, the bloom is more prone to quality problems of surface cracks, center porosity. Billet quality defects is closely related to its solidification process, and billet solidification process by the mold cooling and secondary cooling, so the research of process of solidification and heat transfer and determination of the suitable cooling water flow is significant to understand solidification behavior and guarantee the quality of billet.Focused on380mmx490mm bloom continuous casting machine in DSSG, combined with field practical, and based on the heat transfer mechanism this paper develops2D heat transfer model of bloom. In the modeling process, the thesis use enthalpy to deal with latent heat of solidification. Taking into account the heat transfer model is non-linear partial differential equation, it cannot be solved analytically, using the finite element method to numerically solve the model. Under different conditions, to simulate the temperature distribution of the bloom cross-section and the growth of solidified shell. Casting speed and superheat’s effects on steady temperature field are analyzed in this paper.Each section water flow of Continuous casting secondary cooling zone is the direct factor that affect the quality of billet, unreasonable secondary cooling system will cause the quality problem of billet. In order to improve the quality of billet and to improve the secondary cooling system, combined with the bloom solidification heat transfer model, this thesis studies optimization method based on metallurgy criterion function and develops a secondary cooling water optimization model based on adaptive ant colony algorithm. For the disadvantage of the basic ant colony algorithm, easily trapped in local minima, stagnation, etc., improved adaptive ant colony algorithm is used, in order to improve search efficiency in optimizing secondary cooling water. The result of simulation shows that optimized the secondary cooling system can make the billet surface temperature distribution to flatten, reduce the temperature rise rate and can better meets the requirements of the metallurgical criteria to improve the cooling process in the slab, and improve product quality.