Modelling of austenite decomposition of hot-rolled plain carbon steels under complex cooling conditions

Abstract

The purpose of the present work is to develop a mathematical model allowing the simultaneous prediction of both transformation product portions and mean ferrite grain size from the same common principles as a result of austenite decomposition during continuous cooling of plain carbon steels. The transformation products considered specifically are polygonal ferrite and pearlite. The model is based on the classical equations of nucleation-growth theory and also contains some empirical parameters. The chemical driving forces for nucleation and composition of elements at the phase interfaces are derived from thermodynamic analysis. Three modes of ferrite nucleation are taken into account that correspond to the nucleation on the austenite grain corners, edges and faces. The model considers the reduction of the nucleation sites due to the occupation of austenite grain boundary surface by ferrite grains. Pearlite transformation starts at the γ/α interface and suppresses further ferrite grain growth. The parameters related to ferrite reaction were determined on the basis of a series of austenite transformation kinetic curves and grain size measurements for a steel with the composition 0.084%C-0.58%Mn-0.02%Si obtained by dilatometric technique for cooling rates from 0.032 to 2.5 K/s. The parameters related to pearlite reaction were determined on the basis of the data for a steel with 0.66%C. After determination of the model parameters the model was applied to complex cooling conditions of the run-out table of the hot strip mill at Voest-Alpine Stahl Linz GmbH. Predicted ferrite grain size appeared to be 1.2 - 1.3 times smaller than the observed one. With regard to experimental data on grain growth in iron, it was suggested that the underestimation of grain size is due to additional ferrite grain growth occurring after the coiling of the steel sheet. Taking that into account provided satisfactory agreement with observed values.