The use of thermal analysis to predict the microstructure of cast iron

Abstract

During the last decade, with the development of computer technology, computer-aided casting design/solidification modelling techniques has advanced significantly. However, much remains to be done, especially to predict microstructure evolution. In this study, Computer-Aided Differential Thermal Analysis (CADTA) and solidification modelling techniques are incorporated together to predict the composition and microstructural features of cast iron from the data obtained from a test sample of the melt before the pouring the real casting. The composition prediction is accomplished by detecting the austenite liquidus and eutectic temperature by thermal analysis before any treatment. The microstructure prediction is carried-out by the incorporation of CADTA, which determines the amount of latent heat liberated and its release rate, and microstructure evolution modeling. It is shown both theoretically and experimentally that the formation of white iron is associated with less latent heat than is grey iron; this is reflected in the cooling curve by a reduced eutectic transformation temperature and a shorter transformation time. It is also observed that for grey iron the latent heat release rate during the eutectic reaction varies in a distinct way for various graphite morphologies.