The effects of heat treatment processing on the microstructures of Ti-6Al-4V alloy are systematically studied. Static globularization behavior of lamellar α phase is found when the alloy is cooled in air or furnace from 950–960 °C (below the β-transus temperature, about 975 °C). Three kinds of microstructures (basket-weave, globular-lamellar, and equiaxed microstructures) are obtained by different heat treatments. The uniaxial tensile tests of the studied alloy with different initial microstructures are conducted at the elevated temperature and different strain rates. It is found that the initial microstructures have obvious effects on the tensile properties and fracture mechanisms. The alloy with basket-weave microstructures exhibits the most obvious work hardening behavior and the highest strength. The alloy with globular-lamellar microstructures has the better ductility than that with basket-weave microstructures. Furthermore, the alloy with equiaxed microstructures has the best ductility, because the equiaxed α phases can delay the formation and coalescence of microvoids. Meanwhile, α phases are elongated, bent and spherized, which contributes to the flow softening during tensile deformation. Especially, the alloy with initial equiaxed microstructures finally transforms to bimodal microstructures after tensile fracture. Additionally, the alloys with three different initial microstructures all show a primary ductile fracture.

Effects of initial microstructures on hot tensile deformation behaviors and fracture characteristics of Ti-6Al-4V alloy

The time variance and nonlinearity of forging processes pose great challenges to high-quality production. In this study, a one-step-ahead model predictive control (MPC) strategy based on backpropagation (BP) neural network is proposed for the precise forging processes. Two online updated BP neural networks, predictive neural network (PNN) and control neural network (CNN), are developed to accurately control the die forging hydraulic press machine. The PNN and CNN are utilized to predict the output (the velocity of upper die) and determine the input (the oil pressure of driven cylinders), respectively. The weights of neural networks are initially trained offline and then updated online according to an error backpropagation algorithm. In the proposed control strategy, only the input and output are required, which makes the forging process easy to be controlled. In addition, because of the generalized ability and adaptability of neural networks, the proposed predictive controller can well deal with the time variance and nonlinearity of forging process. Two forging experiments demonstrate the feasibility and effectiveness of the proposed strategy. Moreover, comparing the proposed MPC strategy with the traditional MPC approach and PID controller, it can be found that the proposed MPC strategy is the most effective control approach for the practical forging process.

A precise BP neural network-based online model predictive control strategy for die forging hydraulic press machine

In order to study the flow behaviors of an Al-Zn-Mg-Cu alloy at elevated temperatures, uniaxial tensile tests were carried out in wide deformation temperature and strain rate ranges. The flow stress rapidly increases to a peak value and then slightly decreases with the increased strain, and the dynamic recovery (DRV) is the primary softening mechanism. A unified constitutive model based on dislocation density was developed. An iterative procedure was implemented into the developed model to describe the flow behaviors at time-variant deformation conditions (e.g. the strain rate is changed during hot deformation). The predicted flow stresses were in accord with the experimental results, suggesting that the flow behaviors of the studied Al alloy at elevated temperatures can be well reproduced by the developed model. Meanwhile, the variations of the product of the instantaneous work hardening (WH) rate and stress caused by dislocation evolution, the dislocation density changing rate, as well as the dislocation mean free path, were given to analyze the WH and DRV mechanisms of Al-Zn-Mg-Cu alloy.

A unified constitutive model based on dislocation density for an Al-Zn-Mg-Cu alloy at time-variant hot deformation conditions

A review on modelling techniques for formability prediction of sheet metal forming

Hot compression features of Ti-55511 alloy are investigated by high-temperature compression tests in α+β region. It is found that the flow stress and softening mechanisms are obviously influenced by deformation conditions. The true stress decreases with the reduced strain rate or the raised temperature. The spheroidization of α phase and dynamic recrystallization (DRX) of β phase easily occur at low temperatures such as 973, 1003 and 1033 K, while the dynamic recovery (DRV) of β phase mainly occurs at high temperatures such as 1063 K because of the transformation from α phase to β phase at relatively high temperatures A dislocation density-based constitutive model, which is associated with DRV, work hardening mechanisms and the spheroidization of α phases, is established and validated to describe flow behavior. The correlation coefficient (R) and average absolute relative error (AARE) of the established model are 0.9924 and 6.8%, respectively. 3D power dissipation efficiency maps and processing maps are established to determine the appropriate processing window, i.e., too low temperatures (lower than 973 K) or too high strain rates (higher than 1 s−1) easily induce flow instability. Therefore, the medium temperature (1003–1063 K) and the low strain rate (0.001–0.1 s−1) are applicable for thermal compression of the studied titanium alloy.

A dislocation density-based model and processing maps of Ti-55511 alloy with bimodal microstructures during hot compression in α+β region

Development of experimental and theoretical forming limit diagrams for warm forming of austenitic stainless steel 316

Forming limit diagram (FLD) is an important performance index to describe the maximum limit of principal strains that can be sustained by sheet metals till to the onset of localized necking. It is useful tool to access the forming severity of a drawing or stamping processes. In the present work, FLD has been determined experimentally for Ti-6Al-4 V alloy at 400 °C by conducting a hemispherical dome test with specimens of different widths. Additionally, theoretical FLDs have been determined using Marciniak Kuczynski (M-K) model. Various yield criteria namely: Von Mises, Hill 1948, Hill 1993 and Cazacu Barlat in combination with different hardening models viz., Hollomon power law (HPL), Johnson-Cook (JC), modified Johnson-Cook (m-JC), modified Arrhenius (m-Arr.), modified Zerilli–Armstrong (m-ZA) have been used in M-K analysis for theoretical FLD prediction. The material properties required for determination of yield criteria and hardening models constants have been calculated using uniaxial tensile tests. The predicted theoretical FLDs results are compared with experimental FLD. It can be observed that influence of yield criterion in M-K analysis for theoretical FLD prediction is predominant than the hardening model. Based on the results; it is observed that the theoretical FLD using Cazacu Barlat and Hill 1993 yield criteria with m-Arr. hardening model has a very good agreement with experimental FLD.

Geetha Krishna

Papers

Development of experimental and theoretical forming limit diagrams for warm forming of austenitic stainless steel 316

Experimental and theoretical investigation of forming limit diagram for Ti-6Al-4 V alloy at warm condition

Influence of material models on theoretical forming limit diagram prediction for Ti–6Al–4V alloy under warm condition