Neural network modelling of the Nb effect on mechanical properties of the ferritic bainitic dual-phase steel

ABSTRACTThe production of low-alloy advanced high-strength steels such as the dual-phase (DP) steel with ferritic-bainitic microstructure using a hot strip mill is challenging in terms of consistent mechanical properties-based DP steel without violating the hot strip mill rolling capacity. In the present study, the Artificial Neural Network (ANN) technique was employed to develop tensile strength, yield strength and %Elongation models which can cater to complex relationships between the DP steel mechanical properties as a function of steel composition and rolling parameters. Furthermore, ANN models were used to predict the Nb effect on the mechanical properties of the DP steel. Model prediction and validation confirmed that niobium has a notable influence on mechanical properties. Finally. Nb's role during hot rolling was reviewed and justified.KEYWORDS: Dual-phase steelartificial neural networkhot strip milleffect of Nbhot rollingrolling parametersstrengthelongation AcknowledgementThe authors thank Tata Steel management for supporting this work.Disclosure statementAuthors have no conflict of interest to declare.Declaration of interestsThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Data availability statementThe data that support the findings of this study are available from the corresponding author upon reasonable request.