Ferrite/Pearlite Band Prevention in Dual Phase and TRIP Steels: Model Development

Abstract

A model for predicting the conditions for ferrite/pearlite band prevention in dual phase and TRIP steels has been developed. The competition between processing parameters such as the austenitisation time and temperature, the transformation temperature and microchemical segregation wavelength is explored. The effects of alloy composition in the tendency to form ferrite/pearlite bands are quantified. A simple formula combining processing parameters and compositions for describing band formation is presented. The calculations show that the most prominent factor for preventing banding is the control of the microchemical wavelength. In addition to C and Mn, Al and Si concentrations have shown to play a smaller but significant role in band formation behaviour.KEY WORDS: segregation; banding; ferrite; pearlite; microstructural homogeneity; kinetics; phase transformations; diffusion; nucleation; solidification. Model for Ferrite/Pearlite Band PreventionThe computer model combines the effects of solute segregation due to solidification, the diffusion of the segregated components during homogenisation and the nucleation of ferrite in regions possessing different concentration values during controlled cooling after hot rolling. The diffusion is assumed to occur in the austenitic field g, and the transformation either in the three phase region gϩaϩq or in the two phase region gϩq (where a stands for ferrite and for q stands for cementite), as shown schematically in Fig. 2. Solidification and Solute SegregationThe first phenomenon leading to ferrite/pearlite banding that takes place in alloy production is solidification. At this stage, the primary and secondary dendrite arms advance towards fresh liquid regions. This causes an inhomogeneous solute distribution in the dendrite, where its centre contains the low carbon content that characterises the liquid→d-ferrite reaction at the alloy concentration. The dendrite edges impinge with each other in the last stages of solidification, requiring that such interfaces be characterised by the high carbon concentration of the eutectic point. Therefore, the liquid →d-ferrite composition and eutectic reaction composition provide the extreme composition values to be homogenised in the high temperature austenitisation treatment. These were obtained for a variety of steels from a thermochemical database.9) The procedure employed for each studied alloy grade was to reduce the temperature from the liquid field to the eutectic temperature. The d-ferrite composition and the composition of the last liquid in equilibrium were assumed to be the initial segregation values present, which will approach the average alloy concentration as homogenisation proceeds.8) Reduced segregation values obtained from non-equilibrium solidification processes may be incorporated in the model through assuming an increased austenitisation time value. However, the equilibrium composition values that are assumed capture very well the expected compositional variations across the dendrites as a function of alloy composi...

Computational design of precipitation strengthened austenitic heat-resistant steels

“…Inspired by persistent demands from industries and academia, various computational-guided alloy design approaches have been developed, including but not limited to computational thermodynamics-aided [10][11][12][13][14][15], artificial neural networks [16,17] and even ab initio models [18][19][20]. Recently, a genetic algorithm (GA) optimization protocol has been successfully combined with thermodynamics to design new Ultra High Strength (UHS) stainless steel grades [21][22][23][24][25][26], in which alloy compositions and heat treatment parameters (austenitization and ageing temperatures) are optimized simultaneously so as to obtain desirable microstructural components and avoid undesirable phases throughout the entire heat treatment process. GAs are biologically inspired optimization techniques, which tend to mimic the basic Darwinian concepts of natural evolution [27].…”

Formation Mechanisms of Cracks Formed During Hot Rolling of Free-Machining Steel Billets

“…This implies that the directionality of bandshaped C-and Mn-rich regions during hot rolling readily expects the directionality of pearlite bands after hot rolling. [30,31] Thus, the selective oxidation high temperatures during hot rolling can be explained by band structures of C-and Mn-rich regions, instead of pearlite bands. The oxide intrusion or selective oxidation at high temperatures can work as stress concentration sites during hot rolling and, consequently, causes of the crack initiation in the surface region of the rolled billet.…”

Modelling and characterization of chi-phase grain boundary precipitation during aging of Fe–Cr–Ni–Mo stainless steel

“…The interfacial energy is assumed to be 0.1 J/m 2 in this calculation. The factor   is taken as 0.0015 [30,31].…”