Modelling of microstructure and mechanical properties of steel using the artificial neural network

The paper presents some results of the research connected with the development of new approach based on the artificial intelligence of predicting the volume fraction and mean size of the phase constituents occurring in a steel after thermomechanical processing and cooling. The independent variables in the model are austenite grain size and cooling rate over the temperature range of the occurrence of phase transformations. The dependent parameters are proeutectoid ferrite, Widmanstätten ferrite and pearlite fractions as well as ferrite grain size. Furthermore, a preliminary model for the prediction of mechanical properties was elaborated based upon the same idea.