Heat Deformation Behavior And Microstructural Evolution Of Fine Grained TC4 Alloy

Continuous Variable Cross-section Recycled Extrusion is a new method of sever plastic deformation, which has some advantages such as improving and eliminating inhomogeneous deformation including the drum-shaped and buckling as well as folding in the upsetting process. Moreover, the fine grain materials with large size can be obtained by this method. In this paper, the fine grain TC4 titanium alloy was prepared by Continuous Variable Cross-section Recycled Extrusion, the grain size of the fine grain TC4 titanium alloy is about 2~3μm, and the thermal simulation compression test of the fine grain material was carried out with the deformation temperature was 1023~1223K, the strain rate was 0.001~10s-1, Constitutive equation of the fine grain material was established, the paper studied the effects of different heat processing on Microstructure of the alloy in order to provide some guidance on theoretical and technical parameters of thermal processing of fine grained TC4 alloys. The main content of research and conclusions are as follows:(1) Some conclusions can be obtain from the the true stress-strain curve that in the beginning of hot deformation, the flow stress of alloy increasing rapidly with strain increased and reaches a peak, Strain continued to increase, the flow stress reduces gradually, the true stress-strain curve is relatively smooth, enter the steady flow stage. With the increase of deformation temperature and the reduction of strain rate, the flow stress decreases. The higher the hot deformation temperature and the lower the strain rate, the smaller strain will be needed to alloy enter the steady flow phase.(2)The constitutive equations of the fine grain TC4 alloy prepared by continuous variable cross-section recycled extrusion were established by Arrhenius equation and artificial neural network, and the constitutive equations were based on the stress-strain curves of the experiment. The results show that the modeling process of Arrhenius type model is more complex and involved more calculation of parameters,while the neural network model is more simple compared with the Arrhenius type model, BP neural network model does not need a specific model equations, just need to set the number of hidden layer and the number of hidden layer nodes, so it does not need complex calculation of parameter. Moreover, the correlation degree and the relative error between prediction data and experimental data of two kinds of constitutive equations are also calculated. The results show that the prediction data of artificial neural network is more precise, which is more suitable for the numerical simulation of flow stress of the fine grain TC4 alloy prepared by continuous variable cross-section recycled extrusion.(3) Some conclusions can be obtain through analysis the microstructure of specimenthes that in the beginning of hot deformation,with the increasing of deformation temperature, the grain size of α phase is gradually increasing, its volume fraction decreasesing, but the α phase is still equiaxed and the uniformity of structure was not changed much. When the deformation temperature up to 900℃ the volume fraction of α phase decreases obviously, the grain of α phase becomes bigger and the uniformity of structure become worse and the grain boundaries of α phase precipitated more β phase. When the temperature of thermal deformation up to 950℃, he grain boundaries of α phase is almost disappeared and the equiaxed structure become further coarsened. With decreasing strain rate, the α phase have the trend to obvious growth. The results show that,when the deformation temperature range from 750~800℃, strain rate range from 0.001-0.1s-1, the microstructure of sample is equiaxed, finer and more uniform.