Papers by Keyword: Flow Stress

Abstract: Isothermal tensile test of medium carbon steel material was conducted on a computer controlled servo-hydraulic testing machine at the deformation temperatures (923 to 1223 K) and the strain rates (0.05 to 1.0 s^-1). Using the experimental data, the artificial neural network (ANN) model with a back-propagation (BP) algorithm was proposed to predict the hot deformation behavior of medium carbon steel material. For the model training and testing purpose, deformation temperature, strain rate and strain data were considered as inputs and in addition, the flow stress data were used a targets. Before running the neural network, the test data were normalized to effectively run the problem and after solving the problem, the obtained results were again converted in order to achieve the actual data. According to the predicted results, the coefficient of determination (R²) and the average absolute relative error between the predicted flow stress and the experimental data were determined as 0.997 and 0.913%, respectively. In addition, by evaluating each test conditions, it was found that the average absolute relative error based on an ANN model varied from 0.55% to 1.36% and moreover, the results showed the better predictability compared with the measured data. Overall, the trained BP-ANN model is found to be much more efficient and accurate by means of flow stress prediction with respect to the experimental data for an entire tested conditions.

Abstract: A phenomenological model presented by the authors in the previous study, which is a kind of two-region exponential function model, is used to describe flow stress behaviors of bearing steel, STB2. In this model, flow stress is calculated using two separated equations for hardening and softening regions. Peak stress, peak strain, hardening coefficient, steady state stress and softening coefficient are the required parameters for the model. These parameters are then either interpolated using linear regression or used to find some fitted functions of strain rate and temperature to identify the flow stress. The former is called the piecewise bi-linear function model (PLF model) while the latter the closed-form function model (CFF model). It has been shown that the flow stress curves of STB2 steel obtained by these two models are in good agreement with experimental results.

Abstract: Predictive power and final shape are very important in the forging process. This study used a finite element method to analyze the forging force, final shape and stress distribution of the cellphone shell forging at different temperatures. To predict the results of FEM simulation accurately, the stress flow and friction factor play an important role. The AL-6061 stress-strain curve at different temperatures was obtained from the compression test of the universal material testing machine. The friction factor between Al-6061 alloy and die is determined by ring compression test.The stress-strain curve and friction factor are applied to the finite element analysis of cellphone forging. Finite element analysis is used to determine the maximum forging load, effective stress distribution and shape of cellphone shell forging. Then the cellphone shell is forged with the parameters of finite element analysis results. Finally, the forging force and product shape are compared between the experimental data and the simulation results. The dimension of the cellphone shell agree with the initial design and the forming force does not exceed the maximum allowable forging load of the machine.

Abstract: The deformation behavior in isothermal compression of Ti-5Al-4Mo-2Cr-4Zr-2Sn-1Fe alloy was investigated at the deformation temperature of 800°C, 850°C, 900°C, 950°C and 1000°C, the strain rate of 0.01s^-1, 0.1s^-1, 1.0s^-1 and 10.0s^-1, and the height reduction of 70%. The flow stress increases rapidly with the increasing of strain at the beginning of deformation. When the strain exceeds a certain value, the flow stress begins to decline and becomes steady. With the increasing of deformation temperature and decreasing of strain rate, the steady stress and peak stress decrease significantly. The effect of strain on the processing maps of Ti-5Al-4Mo-2Cr-4Zr-2Sn-1Fe alloy is obvious. As the strain increases, the instable region moves towards high temperature and high strain rate area. Meanwhile, the contour of efficiency of power dissipation becomes more and more intensive, and the region with high efficiency of power dissipation reduces. Strain rate of 0.01s^-1 and deformation temperature of 900°C are the optimum processing parameters for Ti-5Al-4Mo-2Cr-4Zr-2Sn-1Fe alloy forging under strain of 0.3.

Abstract: A new modified low-cost titanium alloy, Ti-Al-X, was designed for petroleum drilling applications. The alloy ingots were prepared by combination of vacuum consumable electrode arc melting, forging/hot rolling, homogenization, and solid-solution/aging treatments. The hot deformation behavior of Ti-Al-X alloy was investigated by a thermal simulation machine Gleeble 1500 at temperature range of 850~1000°C with the strain rate range of 0.001 s^-1~1s^-1. The deformation resistance significantly decreases with the increase of deformation temperature and the strain rate. The alloy exhibits flow instability under the deformation conditions of strain rates about 0.001 s^-1 and temperature above 1000°C, which should be avoided during hot working. In addition, the instability area enlarged in processing map with the increasing of true strain.

Abstract: In order to provide an accurate prediction of the flow stress during the thermal deformation process, a physical model is established. In the model, it is assumed that the flow stress is mainly composed of short-range stress and long-range stress. The short-range stress is a friction stress needed to be overcome when dislocations pass short-range obstacles and through the lattice, and the long-range stress is athermal stress caused by the interaction of dislocation substructure. The model is established mainly based on the evolution of dislocation density which is described as a competitive process of work hardening and recovery. Meanwhile, the interaction between vacancies and dislocations is also taken into account. The effect of solutes and precipitation on stress is quantified. In addition, some experiments have been performed using two steels containing different amounts of Nb under various deformation conditions. The experimental results indicate the prediction accuracy of the model is satisfactory.

Abstract: Densification behaviour of sintered Fe-0.8%C-1%Si-0.8%Cu powder metallurgy steel under the influence of two different aspect ratios subject to cold forging is studied in the present investigation. The critical evaluation of cold deformation exercise revealed that induced strains are linearly contributing to enhance densification till the specimen fracture; however overall resistance to deformation of material is exhibiting in three different responses with respect to improvement in densification. That is at initially, high resistance to deformation followed by high kinetics of deformation and finally exhibiting little resistance against overall deformation. Although, the aforementioned criteria is common for both the aspect ratios, the applied deformation is little homogeneous when aspect ratio is less that directly contributes to enhance the rate of attainment of densification as little faster in the later stage of densification on the other hand the higher aspect ratio preform is bit non-linear in nature and retards stress in the later stage.

Abstract: The selection of the flow stress model of materials has a great influence on the plastic forming simulation of metal. For closed extrusion fine blanking, selecting the accurate and appropriate material flow stress model can make the finite element simulation closer to the real situation, and the simulation data is more reliable. In order to solve the accuracy problem of finite element simulation closed-extruding fine blanking, 5 types of flow stress fitting curve equations were obtained based on the data of sheet metal tensile test. With the secondary development of finite element software Deform-2D, the circular piece of closed-extruding fine blanking forming process was simulated, whose diameter is 14 mm and thickness is 30 mm. The simulation results of different rheological models were compared after physical experiment being carried out.The results show that Ludwik extrapolation rheological model is suitable for finite element simulation of closed-extruding fine blanking technology, which effectively improves closed-extruding fine blanking simulation accuracy. Lay the foundation for the application of closed-extrusion fine blanking in industry.

Abstract: A new modeling method called multivariate adaptive regression spline (MARS) was firstly employed to predict the hot rolling flow stress and explain the relationship among flow stress and various parameters such as major chemical compositions, rolling temperature, rolling speed, compression ratio, thickness, roll radius, furthermore, analyze the importance of the predictor variables. The results showed that the error of training and testing was less than 2%, and rolling temperature, rolling speed, and strip thickness had much contribution to flow stress. Moreover, the impact of various factors on the flow stress can be validated by real production data, which proved the reliability of MARS model to predict the flow stress and guide the practical production.

Abstract: Isothermal compression tests were conducted to investigate the effect of hot deformation parameters on flow behavior and microstructure of Ti-6Al-4V-0.2O alloy. The experimental results show that the strain rate and height reduction have little effect on the volume fraction of primary α at a deformation temperature of 860 ̊C. At a deformation temperature of 940 ̊C, the volume fraction of primary α at a high strain rate (10s^-1) is about 10% less than that at low strain rates (0.01s^-1~1s^-1). It may be one of the reasons for the significantly discontinuous yielding phenomenon. Another reason is that the dislocation density decreased suddenly due to the dynamic recovery. With the increasing strain rate and the decreasing deformation temperature, the volume fraction of irregular secondary α increases and lamellar secondary α decreases. And with height reduction increasing, the irregular secondary α increases firstly and then tends to be steady because of dynamic recovery and recrystallization.