Microstructure Modelling And Properties Prediction Of WC-Co Cemented Carbides

The current researches on WC-Co cemented carbides are mostly based on experiments, and this method costs a lot of materials and financial resources. To establish a parameterized model of the microstructure for tool material, and to achieve the computer aided design of material by using numerical simulation methods, and to predict the mechanical properties of materials combining the theoretical data with the measured data will shorten the development period of cemented carbides with time and cost saving.Digital image processing method was used on the scanning electron microscopy images of WC-Co cemented carbides to extract the microstructural parameters of materials. Parameterized models of WC-Co cemented carbides were established by using VC. By using the Python script language, the model was imported into ABAQUS software to establish the finite element analysis model.The method to determine the size of representative volume element of WC-Co cemented carbides was presented. At the same time, the equivalent elastic properties of WC-Co cemented carbides were predicted, and the result shows that the predicted values lie between the upper limit of Voigt model and the lower limit of Reuss model. The equivalent Young’s modulus decreases with the increase in Co content, whereas the equivalent Poisson’s ratio exhibits reverse trend.Three point bending models were established in order to predict the transverse rupture strength of WC-Co cemented carbides. The FEA results show that the simulated values have a good agreement with measured values.By using three point bending specimens and XFEM method, the fracture toughness of WC-Co cemented carbides was predicted. The crack propagation simulation results show that the stress in crack tip is larger than that elsewhere, and the stress concentration is obvious. The fracture toughness of WC-Co cemented carbides increases with the increase in Co content under the same WC grain size. The FEA results show that the simulated values have a good agreement with measured values.