Optimisation of continuous casting process parameters based on coupled heat and stress model

Abstract

Based on a coupled heat and stress model, an artificial intelligence optimisation program was developed to optimise the process parameters in the continuous casting of steel. The program can be used to identify the key factors for the cracks of the strand and obtain the optimum process parameters of continuous casting. The optimisation program contains two models, one is the thermomechanical model developed using the finite difference method, and the other is the optimisation model developed using the subproblem approximation method. The whole program works by automatic iteration between the two models. This study has taken the stress constraint in the solidified shell into consideration when studying the metallurgical constraints. The application of the achieved optimum parameters would make it possible to run the caster at maximum productivity, with minimum cost and fewer defects. After manufacturing verification of this optimisation project, the incidence of cracks has reduced from 8% to 2%, and water consumption in the secondary cooling zone has been decreased by 25%.