The stress strain curve of 7075 aluminum alloy in the temperature range of 310 °C to 410 °C was obtained by Gleeble-3800. By Nakazima test, the isothermal thermoforming limit diagrams of 7075 aluminum alloy at different deformation temperatures and stamping speeds were acquired. Moreover, the parameters of automotive S-rail hot stamping process were optimized by GA-BP neural network. The results show that the forming limit curve of 7075 aluminum alloy increases as the deformation temperature and stamping speed increase. The predicted optimal parameters for hot stamping of automotive S-rails by GA-BP neural network are: stamping speed is 50 mm/s, friction coefficient between die and blank is 0.1, and blank holder force is 5 kN. The maximum thinning rate at this process parameter is 9.37%, which provided a reference for 7075 aluminum alloy automotive S-rail hot stamping.

Valve microstructure is important during hot forging. Austenitic 21-4N steel is often used in exhaust valves. In this study, the microstructure evolution of the forging valve process was predicted using the internal state variables (i.e., average grain size, recrystallized fraction, and dislocation density) modus for 21-4N. First, 21-4N was subjected to hot compression tests on a Gleeble-1500D and static grain growth tests in a heating furnace. A set of uniform viscoplastic constitutive equations was established based on experimental data. Next, the determined unified constitutive equations were conducted in DEFORM-3D, and the microstructure evolution of 21-4N during forging was calculated. Finally, the simulation results of grain size evolution were validated via experiments. Results showed good consistency between the simulations and experiments. Thus, the models adequately predicted the microstructure evolution.

Titanium alloy possesses high strength, good corrosion resistance, and high heat resistance; thus, it is widely used in the aerospace and other fields. Blades of titanium alloy are important components of aero-engines and are essential to the engines operation. In this work, a Ti-6Al-4V blade was formed by cross wedge rolling (CWR) to realize the near net-shape of an aero-engine blade. First, thermal simulation experiments of Ti-6Al-4V were carried out to obtain the thermal deformation constitutive equation of the alloy. The finite element software Deform-3D was then used to simulate the thermodynamic coupling of the forming process, and the metal flow, temperature, and stress–strain distribution laws during the forming process were analyzed. Finally, experimental verification of the Ti-6Al-4V blade was carried out by using an H500 CWR mill. The results revealed the feasibility of applying CWR to preform Ti-6Al-4V blades.

As a critical component of a train, the railway wagon bogie adapter has higher quality requirements. During the forging process, external loads can induce voids, cracks, and other defects in the forging, thereby reducing its service life. Hence, studying the damage behavior of the forging material, specifically AISI 1035 steel, becomes crucial. This study involved obtaining stress–strain curves for AISI 1035 steel through uniaxial tensile tests at temperatures of 900 °C, 1000 °C, and 1100 °C, with strain rates of 0.1 s⁻¹, 1 s⁻¹, and 10 s⁻¹. Subsequently, SEM was used to observe samples at various deformation stages. The damage parameters, $q_1$, $q_2$ and $q_3$ in the GTN model “a computational model used to analyze and simulate material damage which can effectively capture the damage behavior of materials under different loading conditions” were then calibrated using the Ramberg–Osgood model and stress–strain curve fitting. Image Pro Plus software v11.1 quantified the sample porosity as $f_0$, $f_n$, $f_c$ and $f_F$. A finite element model was established to simulate the tensile behavior of the AISI 1035 steel samples. By comparing the damage parameters of $f_0$, $f_n$, $f_c$ and $f_F$ obtained by the finite element method and experimental method, the validity of the damage parameters obtained by the finite element inverse method could be verified.