To realize the purpose of energy saving, materials with high weight are replaced by low-weight materials with eligible mechanical properties in all kinds of fields. Therefore, conducting research works on lightweight materials under specified work conditions is extremely important and profound. To understand the relationship of aluminum alloy AA5005 among flow stress, true strain, strain rate, and deformation temperature, hot isothermal tensile tests were conducted within the strain rate range 0.0003–0.03 s⁻¹ and temperature range 633–773 K. Based on the true stress-true strain curves obtained from the experiment, a traditional constitutive regression Arrhenius-type equation was utilized to regress flow behaviors. Meanwhile, the Arrhenius-type equation was optimized by a sixth-order polynomial function for compensating strain. Thereafter, a back propagation artificial neural network (BP-ANN) model based on supervised machine learning was also employed to regress and predict flow stress in diverse deform conditions. Ultimately, by introducing statistical analyses correlation coefficient (R²), average absolute relative error (AARE), and relative error ($\delta$) to the comparative study, it was found that the Arrhenius-type equation will lose accuracy in cases of high stress. Additionally, owning higher R², lower AARE, and more concentrative $\delta$ value distribution, the BP-ANN model is superior in regressing and predicting than the Arrhenius-type constitutive equation.

Microstructure is an important factor that affects the mechanical properties and service life of forgings. Through the full study of the formability of the material, the internal microstructure of the material can be effectively controlled. In order to accurately describe the formability of materials during thermal processing, 3D hot processing maps containing strains were established in this paper, and the 3D hot processing maps were coupled with the finite element method for simulation calculation. The Cr5 alloy steel was subjected to unidirectional thermal compression at a strain rate of 0.005–5 s⁻¹ and temperature range of 900–1200 °C on a Gleeble-1500D thermal simulation machine, in order to obtain the date of true stress and strain. Based on the dynamic material model (DMM), the 3D processing maps of Cr5 alloy steel was established, and the 3D processing maps were associated with the analysis of microstructure evolution during hot deformation. The results show that the optimum thermal deformation conditions are as follows: temperature of 1000–1125 °C, strain rate of 0.01–0.2 s⁻¹, and peak power dissipation of 0.41. The 3D processing maps were coupled with the finite element software FORGE^® to simulate the hot working process, and the distribution and change of power dissipation and flow instability domain on the metal deformation under different thermal deformation conditions were obtained. The comparison between the simulation results and metallographic images of typical regions of metal deformation shows that they are in good agreement. This method can effectively predict and analyze the formability of materials during hot processing and provide guidance for practical industrial production.

Warm deformation is a plastic-forming process that differs from traditional cold and hot forming techniques. At the macro level, it can effectively reduce the problem of high deformation resistance in cold deformation and improve the surface decarburization issues during the hot deformation process. Microscopically, it has significant advantages in controlling product structure, refining grain size, and enhancing product mechanical properties. The Gleeble-1500D thermal–mechanical physical simulation system was used to conduct isothermal compression tests on GCr15 bearing steel. The tests were conducted at temperatures of 600–1050 °C and strain rates of 0.01–5 s⁻¹. Based on the experimental data, the critical strain model and dynamic recrystallization model for the warm–hot forming of GCr15 bearing steel were established in this paper. The model accuracy is evaluated using statistical indicators such as the correlation coefficient (R). The dynamic recrystallization model exhibits high predictive accuracy, as indicated by an R-value of 0.986. The established dynamic recrystallization model for GCr15 bearing steel was integrated into the Forge^® 3.2 numerical simulation software through secondary program development to simulate the compression process of GCr15 warm–hot forming. The dynamic recrystallization fraction was analyzed in various deformation regions. The grain size of the severe deformation zone, small deformation zone, and difficult deformation zone was compared based on simulated compression specimens under the conditions of 1050 °C and 0.1 s⁻¹ with the corresponding grain size obtained with measurement based on metallographic photos; the relative error between the two is 5.75%. This verifies the accuracy of the established dynamic recrystallization and critical strain models for warm–hot deformation of GCr15 bearing steel. These models provide a theoretical basis for the finite element method analysis and microstructure control of the warm–hot forming process in bearing races.

Titanium alloy is widely applied in aerospace, medical, shipping and other fields due to its high specific strength and low density. The purpose of this study was to analyze the formability of Ti6Al4V alloys at elevated temperatures. An accurate constitutive model is the basic condition for accurately simulating the plastic forming of materials, and it is an important basis for optimizing the parameters of the hot forging forming process. In this study, the optimization algorithm was used to accurately identify the high-temperature constitutive model parameters of Ti6Al4V titanium alloy, and the hot working diagram was established to optimize the hot forming process parameters. The optimal forming conditions of Ti6Al4V titanium alloy are given. Ti6Al4V alloy was subjected to high-temperature compression tests at 800–1000 °C and at strain rates of 0.01–5 s⁻¹ on a Gleeble-1500D thermal/mechanical simulation machine. Each parameter of the Hansel–Spittel constitutive model was taken as an independent variable, and the accumulated error between the stress calculated by the constitutive model and the stress obtained by experimentation was used as an objective function. Based on response surface methodology, an inverse optimization method for identifying the parameters of the high-temperature constitutive model of Ti6Al4V alloy is proposed in this paper. An orthogonal test design was adopted to obtain sample point data, and a third-order response surface approximate model was established. The genetic algorithm (GA) was applied to reversely optimize the parameters of the constitutive model. To verify the accuracy of the optimized constitutive model, the average absolute relative error (AARE) and correlation coefficient (R) were used to evaluate the reliability of optimized constitutive model. The R value of the model was 0.999, and the AARE value was 0.048, respectively, indicating that the established high-temperature constitutive model for Ti6Al4V alloy has good calculation accuracy. The flow stress behavior of the material could be accurately delineated. Meanwhile, in order to study the formability of Ti6Al4V alloy, the hot processing map of the alloy, based on a dynamic material model, was established in this paper. The optimum hot working domains of the Ti6Al4V alloy were determined within 840–920 °C/0.01–0.049 s⁻¹ and 940–980 °C/0.11–1.65 s⁻¹; the hot processing map was verified in combination with the microstructure, and the fine and equiaxed grains and a large amount of β phase could be found at 850 °C/0.01 s⁻¹.

X12 (X12CrMoWVNbN10-1-1) ferritic heat resistant steel is an important material for the production of new-generation ultra-supercritical generator rotors. Hot compression tests of X12 ferritic heat-resistant steel were performed via a Gleeble-1500D testing machine under temperatures of 1050–1250 °C and strain rates of 0.05–5 s⁻¹. In order to provide material model data for finite element simulations and accurately predict the hot deformation behavior, a reverse optimization method was proposed to construct elevated temperature constitutive models of X12 ferritic heat-resistant steel in this paper, according to the Hansel–Spittel constitutive model. To verify the accuracy of the model, the predicted and experimental values of the constitutive model were compared. The results indicated that the model had a high prediction accuracy. Meanwhile, the correlation coefficient between the experimental value and the predicted value of constitutive model was 0.97833. For further verification of the accuracy of the model, it was implemented in finite element FORGE^@ software to simulate the compression tests of different samples under different conditions. Comparing actual displacement–load curves with displacement–load curves acquired through finite element simulations, the results indicated that displacement–load curves predicted by the model were very consistent with actual displacement–load curves, which verified the accuracy of the model. Moreover, to research the optimal processing parameters of the material, hot processing maps were drawn according to the dynamic material model. In terms of microstructure evolution, a characteristic area distribution map of the hot processing map was established. Therefore, the optimal hot forming parameters regions were in the range of 1150–1200 °C/0.05–0.62 s⁻¹ for X12 ferritic heat-resistant steel.

In order to avoid the stress shielding phenomenon in orthopedic bionic bone implantation, it is necessary to consider the design of mechanical compatible implants imitating the host bone. In this study, we developed a novel cancellous bone structure design method aimed at ensuring the mechanical compatibility between the bionic bone and human bone by means of computer-aided design (CAD) and finite element analysis technology (specifically, finite element modeling (FEM)). An orthogonal lattice model with volume porosity between 59% and 96% was developed by means of CAD. The effective equivalent elastic modulus of a honeycomb structure with square holes was studied by FEM simulation. With the purpose of verifying the validity of the cancellous bone structure design method, the honeycomb structure was fabricated by selective laser sintering (SLS) and the actual equivalent elastic modulus of the honeycomb structure was measured with a uniaxial compression test. The experimental results were compared with the FEM values and the predicted values. The results showed that the stiffness values of the designed structures were within the acceptable range of human cancellous bone of 50–500 MPa, which was similar to the stiffness values of human vertebrae L1 and L5. From the point of view of mechanical strength, the established cellular model can effectively match the elastic modulus of human vertebrae cancellous bone. The functional relationship between the volume porosity of the nylon square-pore honeycomb structure ranging from 59% to 96% and the effective elastic modulus was established. The effect of structural changes related to the manufacture of honeycomb structures on the equivalent elastic modulus of honeycomb structures was studied quantitatively by finite element modeling.