The knowledge of the martensite start (Ms) temperature of steels is sometimes important during parts and structures fabrication, and it can not be always properly estimated using conventional empirical methods. The additions in newly developed steels of alloying elements not considered in the empirical relationships, or with compositions out of the bounds used to formulate the equations, are common problems to be solved by experimental trial and error. If the trial process was minimised, cost and time might be saved. This work outlines the use of an artificial neural network to model the calculation of Ms temperature in engineering steels from their chemical composition. Moreover, a physical interpretation of the results is presented.Peer Reviewe

The influence of bainite morphology on the impact toughness behaviour of continuously cooled cementite free low carbon bainitic steels has been examined. In these steels, bainitic microstructures formed mainly by lath-like upper bainite, consisting of thin and long parallel ferrite laths, were shown to exhibit higher impact toughness values than those with a granular bainite, consisting of equiaxed ferrite structure and discrete island of martensite/austenite constituent. Results suggest that the mechanism of brittle fracture of cementite free bainitic steels involves the nucleation of microcracks in martensite/austenite islands but is controlled by the bainite packet size.