Statistical Modeling for Prediction of CCT Diagrams of Steels Involving Interaction of Alloying Elements

Steel is used in a wide variety of applications, which require specific mechanical properties. To achieve the desired properties, thermomechanical processing techniques are used, followed by continuous cooling, which results in specific microstructural evolution through phase transformation. This naturally influences the combined requisite property. During the processing, materials can be either deformed in austenitic state or as-cast from the melt and then cooled to room temperature. In the cooling stage, austenite can decompose to ferrite phase types roughly classified as (polygonal) ferrite, bainite and martensite. Since the different ferritic phases have a decisive influence on the mechanical properties, it is important to control the austenite decomposition process. The most important factor affecting the austenite decomposition is the chemical composition of the steel and the applied cooling path. The austenite decomposition is conventionally represented using time-temperature diagrams, either for holding at constant temperature (TTT, time temperature transformation diagrams) or for cooling at different rates (CCT, continuous cooling transformation diagrams). The TTT diagram can be used to calculate an estimate for the transformation start using Scheil’s additivity rule,[1,2] but since there is a considerable difference in the long-time isothermal holding and fast continuous cooling, the usage of the CCT diagram gives a better estimate of the transformation onset during rapid cooling. Since fast cooling rates are often used in steel production, predicting the decomposition of austenite using CCT diagrams was the subject of several earlier studies.[3,4,5] Earlier studies[6,7,8] focused on the usage of an additive regression model of chemical composition as well as the cooling path effect for the start of transformation of ferrite, bainite and martensite, respectively. In these earlier studies, the interaction of different alloying elements was not taken into account; instead, the applied model assumed linear dependence on the alloying elements. Unfortunately, the physical interpretation of the overall transformation kinetic of undercooled austenite in steel is determined by several factors, such as the mobility of the compositional atoms participating in the transformation. This results in solute microsegregation, formation of precipitates, etc., which signifies interaction among the alloying elements. Therefore, using an additive model does not practically represent the physical phenomenon. To address this challenge, in this article we present a model that considers the interaction and quadratic dependence of alloying elements on the transformation onset. This provides better description of the experimental data since only the most significant interaction and quadratic alloying element terms were considered. This enables all the individual alloying elements to be significant for the time-dependent growth and response temperature. The efficiency of the current model has been further examined by fitting it with the CCT behavior of several steels, represented in References 9 and 10, which focus on molybdenum-containing steels.

Source: KNUST