METALLURGICAL LENGTH PREDICTION IN CONTINUOUS CASTING

 Around 98% of the crude steel produced in the United States goes through the CC process, in which a water-cooled mold is used to solidify molten steel using water sprays to create semifinished slabs or billets. The quality of both the exterior and inside of the slab is directly related to the rate at which it is cooled, making secondary cooling a difficult process. The heat must be removed efficiently without causing the slab to crack or deform in any way. Low grade steel is produced because of inadequate spray cooling and solidification, which leads to flaws like cracking and breakout. Real-time online dynamic casting control systems are becoming increasingly popular in continuous casting as a means to increase yield and energy efficiency. These systems are built to reliably produce high-quality steel products via real-time temperature measurements and dynamic adjustment of the spray cooling rate. For real-time heat transfer and solidification calculations in the field, the key challenge is determining an accurate Heat Transfer Coefficient (HTC) for the steel product's surface. The correlations for predicting the spray cooling rate empirically have been developed with great care. Nevertheless, these correlations are only valid under specific application circumstances. Building it takes a significant amount of time and effort, and there is no assurance that the correlation will continue to accurately predict HTC even if the development process is modified in any way. An in-depth investigation into the heat transfer mechanisms that take place during the secondary cooling step of continuous steel casting is required in order to achieve control and optimization goals for this step. The non-optimized solidification process also contributes to the formation of inhomogeneous steel properties. The project required the application of computational fluid dynamics modeling techniques so that the casting process could be regulated and improved upon. Simulation of droplet formation, droplet transport, and impingement heat transfer during secondary cooling with an air-mist nozzle in a 3D computational fluid dynamics (CFD) model is going to be done in this study with the intention of generating a multivariable correlation that can accurately predict the lumped HTC under any casting condition. This will be accomplished by using the model. It modeled the solidification of the whole continuous caster by taking into consideration the impacts of roll gap, roll diameter, casting speed, and superheat in order to estimate the metallurgical length and slab temperature. This was done in order to calculate the metallurgical length