Determining the heat transfer coefficient during the continuous casting process using stochastic particle swarm optimization

Abstract

In recent years, the continuous casting process has started to play a key role in the casting region. To obtain high quality steel, the temperature field within the steel needs to be identified. Thus, a method is needed for accurately determining the heat transfer coefficient h in the cooling regions during the casting process. In this study, we built an inverse heat transfer problem (IHTP) model. Based on this model, we then employed stochastic particle swarm optimization (SPSO) to solve the problem. The results of the numerical experiments showed that the relative errors obtained using our inverse method were all less than 2%, which indicates high accuracy. During the solving process, we found that this is a multimodal problem; thus, we examined the causes of the multimodal property. Finally, we developed a preliminary strategy for eliminating the infeasible solutions derived using our method. Our findings are significant for accurately estimating the heat transfer coefficient in the cooling region and reducing the effects of the multimodal property during the solving process.