Optimizing Elemental Transfer Predictions in Submerged Arc Welding via CALPHAD Technology under Varying Heat Inputs: A Case Study into SiO2-Bearing Flux

Abstract

With the advancement of the manufacturing industry, performing submerged arc welding subject to varying welding heat inputs has become essential. However, traditional thermodynamic models are insufficient for predicting the effect of welding heat input on elemental transfer behavior. This study aims to develop a model via CALPHAD technology to predict the influence of heat input on essential elements such as O, Si, and Mn when typical SiO2-bearing fluxes are employed. The predicted data demonstrate that the proposed model effectively forecasts changes in elemental transfer behavior induced by varying welding heat inputs. Furthermore, the study discusses the thermodynamic factors affecting elemental transfer behavior under different heat inputs, supported by both measured compositions and thermodynamic data. These insights may provide theoretical and technical support for flux design, welding material matching, and composition prediction under various heat input conditions subject to submerged arc welding processes when SiO2-bearing fluxes are employed.