Continuous casting process based on an optimized submerged entry nozzle

Abstract

Continuous casting process is an important part in the steel manufacturing process. The slab production quality is commonly influenced by mould and flow pattern of submerged entry nozzles (SEN). Hence, the present work aimed to attain a more liquid flow rate to increase the slab production quantity within a certain period. Moreover, a novel African Buffalo Algorithm (ABA) is presented in this work to optimise the SEN parameters and the SEN was designed in the MATLAB environment. The developed ABA model optimises the design parameters of SEN such as the size of the nozzle, the shape of the port, length, submergence depth, etc. The fitness of buffalo effectively optimises the SEN parameters and by utilising the optimised design parameters, the SEN was resigned in the MATLAB to identify the proposed framework's effectiveness. The results demonstrated that the liquid flow rate is increased and surface tension gets minimised. When the flow rate of liquid grows, the wave amplitude also upturns. The effect of liquid and air flow rate, port shape and size, maximum wave amplitude, surface tension, etc., were calculated with 0° parallel port. In addition, the presented SEN's results were compared with other existing SEN to determine the optimised SEN's effectiveness. The comparison result demonstrated that the designed optimised SEN has a high liquid flow rate, casting speed, density and viscosity.