As a result of the intense air-water interaction in the spray nozzle, air-mist spray is one of the most promising technologies for attaining high heat transfer. CFD simulations and multivariable linear regression were used in the first part of this study to analyze the air-mist spray produced by a flat-fan atomizer and to predict the heat transfer coefficient using the casting operating conditions such as air pressure, water flow rate, cast speed and standoff distance. For the air-mist spray cooling simulation, a four-step simulation method was utilized to capture the turbulent flow and mixing of the two fluids in the nozzle, as well as the generation, transport, and heat transfer of droplets. Analysis of the casting parameters showed that an increase in air pressure results in efficient atomization, increases the kinetic energy of the droplets and produces smaller droplet size thus, the cooling of the slab increases significantly. Also, a decrease in water flow rate, standoff distance and casting speed would result in more efficient cooling of the steel slab. The second part of the study investigated the solidification of steel in the secondary cooling region. Caster geometry and casting parameters were studied to evaluate their impact on the solidification of steel. The parameters studied include roll gap, roll diameter, casting speed and superheat. It was found that a smaller ratio of roll gap to roll diameter is more efficient for adequate solidification of steel without any defect. Casting speed was found to have a significant effect on the solidification of steel while superheat was found to be insignificant in the secondary zone solidification. The result from the air-mist spray cooling was integrated into the solidification model to investigate the solidification of steel in the entire caster and predict the surface temperature, shell growth and metallurgical length. To replicate real casting process, temperature dependent material properties of the steel were evaluated using a thermodynamic software, JMatPro. The air-mist spray model was majorly investigated using ANSYS Fluent 2020R1 CFD tool while the solidification of steel was studied using STARCCM+ CFD software. Using the findings from this study, continuous casting processes and optimization can be improved.

<p> 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 </p>