3D Processing Maps Research Articles

An Investigation on unstable flow during hot deformation of Inconel X750 superalloy using 3D processing map and shear band formation criterion

In this study, deformation efficiency and instability criteria were employed to delineate the unstable flow regions for Inconel X750 superalloy through high temperature deformation. High temperature stress–strain data attained from isothermal hot compression experiments in the temperature range of 950–1150 °C and strain rates between 0.0001 and 1 s⁻¹ to identify safe and un-safe deformation domains in terms of an integrated 3D processing maps. These domains were validated through detailed microstructure observation and material tendency to shear band formation in terms of the competition between work hardening and strain rate sensitivity i.e. flow localization parameter. The superimposed effect of microstructure features like dynamic precipitation, dynamic recovery (DRV), and dynamic recrystallization (DRX) with destructive shear banding were responsible for controlling the material behaviour. Based on the TEM images, it was observed that material revealed stable flow at lower strain rates while adiabatic shear band and flow localization occurred at higher strain rates due to activation of slip systems and cell formation.

Revealing the Dynamic Recrystallization Mechanism and Hot Workability of Fe–0.15C–10Mn Medium‐Mn Steel through Grain Size Distribution and 3D Processing Maps

Revealing the Dynamic Recrystallization Mechanism and Hot Workability of Fe–0.15C–10Mn Medium‐Mn Steel through Grain Size Distribution and 3D Processing Maps

Strain rate affects the deformation mechanism of a Ti-55511 titanium alloy: Modeling of constitutive model and 3D processing map using machine learning

The constitutive model and processing map are effective tools for analyzing the hot deformation behavior of titanium alloys. The stress-strain curves of the Ti-5Al-5Mo-5V-1Cr-1Fe alloy were obtained through the Gleeble thermal simulation experiment. The deformation microstructures at different strain rates were characterized by EBSD and TEM. According to the stress-strain curve, the constitutive models were established by using the Arrhenius equation and the BP artificial neural network (BP-ANN). The constitutive model constructed by BP-ANN has higher fitting accuracy, with the Pearson’s R of 0.99902 and the MAPE of 5.499 %. The 3D processing map of the Ti-55511 alloy was constructed by the BP-ANN constitutive model, which takes temperature, strain, and strain rate as variables. In the processing map, the deformation mechanism is dynamic recovery when the power dissipation efficiency is 0.2–0.33, and the deformation mechanism is dynamic recrystallization when the efficiency is 0.33–0.5. At temperatures of 1123 K and 1153 K and the strain of 0.4, the deformation mechanism is dynamic recovery at the strain rate of 1 s−1. At the strain rate of 0.1 s−1, the deformation mechanism is dynamic recrystallization. This is due to the fact that the higher strain rate prevents dislocations from rearranging, thereby inhibiting dynamic recrystallization behavior.

Flow characteristics, ANN-based prediction, 3D processing map, and interface microstructure of titanium/stainless steel bimetallic composite

To investigate the hot deformation characteristics, workability, and interfacial microstructure of the titanium/steel bimetallic composite, hot compression simulations were carried out on the TA1/SUS430 composite within the temperatures of 750 °C–1050 °C, accompanied by strain rates spanning from 0.01 s⁻1–10 s⁻1. The hyperbolic sine Arrhenius constitutive equation and back-propagation artificial neural network (BP-ANN) model for flow stresses of this bimetallic composite were developed. 2D and 3D hot processing maps were established to study processability. The results revealed the calculated average activation energy (Q) was 277.9671 kJ/mol. The BP-ANN model demonstrated higher prediction accuracy than the Arrhenius model, with a correlation coefficient (R2) of 0.99947. As the strain increases, the area of the unstable region in the processing map expands, and the failure mode is characterized by the formation of microcracks at the bonded interface. Interfacial exfoliation manifested under elevated temperature and high strain rate deformation conditions. High power dissipation (η) values were observed within the processing parameters of 875°C–950 °C/0.01 s−1-0.03 s−1. The bimetal exhibited superior deformation coordination at low strain rates. TiC predominantly constituted the interface products at lower temperatures, while at higher temperatures, phases containing both Fe and Ti dominated. Furthermore, the deformed steel stratum manifested a pronounced cubic orientation <001>//CD and a less dominant recrystallized γ orientation. This γ texture attenuated progressively with increased deformation temperatures, while the strain rate has less impact.

Revealing the hot deformation behavior of AZ42 Mg alloy by using 3D hot processing map based on a novel NGO-ANN model

The hot deformation behavior of AZ42 alloy was observed using thermal compression tests at a temperature scope of 250–400 °C and strain rate scope of 0.001–1 s−1. True stress-strain curves exhibited a combination of work hardening and dynamic softening features. A Northern Goshawk algorithm (NGO)-optimized artificial neural network (ANN) model was proposed. The established NGO-ANN model demonstrated impressive prediction accuracy, achieving a high determination coefficient of 0.991, a mean absolute percentage error of 3.51 %, and a root mean square error of 2.73. Subsequently, three-dimensional (3D) hot processing map based on the dynamic material model (DMM) theory was created. There were three different regions within the processing maps: the flow instability region (region A: 250–260 °C, 0.02–1 s−1, and region B: 300–400 °C, 0.01–0.1 s−1), high-power dissipation coefficient region (region C: 350–400 °C, 0.001–0.02 s−1, and region D: 300–350 °C, 0.5–1 s−1), and low power dissipation efficiency safety region (region E: the rest ones). Microstructural analysis revealed significant local plastic flow features in the flow instability region and a combination of coarse initial deformation grains and fine dynamic recrystallization (DRX) grains in the low power dissipation efficiency safety region. Fine and uniform grains were observed in the high-power dissipation efficiency region with DRX degree VDRX as high as 85.6 %, resulting in the best mechanical properties. Based on the established 3D hot processing map, the optimal process domains were determined.

Machine learning-assisted constitutive modeling of a novel powder metallurgy superalloy

The flow behavior and microstructure evolution during thermomechanical processing (TMP) of powder metallurgy superalloys are very important for their service behavior. In this contribution, a machine learning-assisted physical model was proposed to predict the flow stress, dynamic recrystallization (DRX) kinetic, and grain size evolution of a novel FGH4113A superalloy during the TMP. The work hardening and dynamic softening stages were modeled separately to predict the flow stress. The novel aspect of the proposed model is that the strong coupled effects of deformation temperature, strain rate, true stain, and primary γ' precipitates on the DRX kinetic were quantitatively described by the genetic algorithm-based artificial neural network (GA-ANN). Besides, the grain size modeling considered the pinning effect by primary γ' precipitates and the deformation-induced DRXed grain growth. Comparing the experimental and predicted flow curves, DRX fraction, and average grain size reveals that the proposed model has a preferable prediction accuracy than the conventional model. Then the specific DRX kinetic and grain size evolution characteristics were revealed. The promoting effect of strain rate on the DRX degree was gradually increased with the deformation temperature. Finally, the 3D processing map based on the developed model was established to guide TMP's optimized design and microstructure control. Three domains were divided and discussed: grain refinement, constant, and growth. The optimal processing window is defined as 1000–1050 °C/0.001–0.006 s−1 and 1075–1100 °C/0.008–0.01 s−1.

Microstructural and mechanical characteristics of hot worked homogenized AA7068 using 3D processing map and DEFORM-3D

AA7068 is classified as high strength aluminum alloy and is primarily utilized in wrought conditions which can be achieved with hot deformation. The process of hot deformation is a competent way of optimizing material properties; thus, understanding its deformation behavior in the wide range (250–450 °C, 10−3–100 s−1) is vital in processing a high-performance product. The true stress-true strain trend indicated its dependence on thermomechanical variables and precipitate size. The constitutive calculations accurately predicted the flow stress behavior. The kinetic rate calculations demonstrated that glide dislocation motion (with a value of n = 6.3) was observed during hot deformation. 3-dimensional processing map (PM) has revealed a progressive rise in efficiency (η) with increase in true strain. The PM analysis has successfully identified both stable and unstable working regions. Within the stable working region, a peak efficiency (η) of 54% was observed in the range of 347–359 °C and 10−3 s−1, 0.69 true strain. In, the stable working region, the microstructural characteristics demonstrated a notable increase in the dynamic softening depending on the process time and deformation temperature. At lower temperatures, the dynamic softening in the deformed specimens predominantly occurred through dynamic recovery (DRV), whereas at high temperatures, it facilitated by dynamic recrystallization (DRX). The DRX during deformation was observed to occur through continuous dynamic recrystallization (CDRX) and particle stimulated nucleation (PSN) mechanism. Hot forging finite element modeling (FEM) exhibited an uneven material flow with the peak effective strain occurring in the core of the specimen. Open forging in the optimum working conditions resulted in the highest tensile strength of 340 MPa, observed at a temperature of 450 °C and strain rate of 10−3 s−1.

Numerical Simulation of Crack Condition in Forging Products of M50 Bearing Steel Based on Processing Map Theory

The microstructure of forged products significantly impacts their properties, and defects or carbide distribution are not visible to the naked eye. Isothermal compression tests on M50 steel with a Gleeble 3500 tester were conducted to study microstructure behavior during forging. Tests examined the hot deformation behavior within a temperature range of 900–1200 °C and a strain rate range of 0.01–10 s−1. Power dissipation efficiency (η) and flow instability (ξ), which are crucial processing map parameters, were employed to analyze the high-temperature deformation behavior of M50 steel. The 3D processing map determined the optimum forging conditions, indicating that hot working should start at an initial temperature of 1050 °C or higher and a strain rate of 1 s−1, decreasing the strain rate and temperature as the strain increases. The 3D power dissipation efficiency map displayed an average value of 0.43 or higher at a strain rate of 0.1 s−1 and a temperature of 1150 °C before reaching a strain rate of 0.8. The Finite Element Method (FEM) simulated results, revealing ξ and η distributions, and confirmed that microstructure observation during deformation matched the hot forging parameters. This approach can effectively predict microstructure changes during hot forging.

Deformation and Fracture Characterization of an Mg-Sn-Ca Alloy Using 3D Processing Maps

The deformation and fracture characterization of an Mg−2Sn−1Ca alloy were studied through uniaxial isothermal compression tests. The flow stress curves, the efficiency of power dissipation, the instability parameter and the fracture behavior of an Mg−2Sn−1Ca alloy under the condition of various hot working parameters were investigated according to the experimental data. Processing maps were established by superimposing the instability map over the power dissipation map. It was found that flow stress reduces with increases in the deformation temperature and decreases in the strain rate. The processing of Mg−2Sn−1Ca alloys should avoid the instability region in which the conditions are high strain under high temperature and low strain under low temperature. At 473 K or a high strain rate, unidirectional cracks and fish scale cracks can be produced, and cracks can be avoided under the optimum processing area of 623–723 K/0.001–0.1 s−1.

Optimization of hot deformation processing parameters for as-extruded 7005 alloys through the integration of 3D processing maps and FEM numerical simulation

The hot deformation behavior and microstructure were investigated for as-extruded 7005 alloys, which is the same as the billet state in real applications in the commercial forging process. It provides a more accurate understanding of the hot deformation flow behavior and microstructure evolution of 7005 alloys for commercial forging processing engineers and mold designers. The compression tests were conducted in temperatures 300–550 °C and strain rates 0.001–1 s−1 using an isothermal hot compression test. The power dissipation efficiency (η) and instability parameter (ξ) were calculated according to the true stress-true strain data obtained from the thermal compression tests. 3D thermal processing maps including the true strains were generated for as-extruded 7005 alloys, and the optimal processing conditions were selected according to η, ξ, and microstructure. The results showed that η increased with increasing temperature but decreased with increasing strain rate. The size of the instability region expanded with decreasing temperature and with increasing strain rate. An η < 0.20 is generally designated an instability region. Microscopic defects such as micro cracks and flow localizations could be observed, and the microstructures of the stability regions showed fine recrystallized grains with η above 0.30. The optimal processing conditions were determined to be a processing temperature between 425 and 500 °C and a strain rate between 0.1 and 0.01 s−1. This study is the first to optimize the closed die forging processing parameters through integration of 3D processing maps and a numerical simulation for a hub based on its real workpiece appearance. A function for prediction of the microstructure evolution is provided using commercial simulation software to help mold designers and forging processing engineers reduce the trial time.

Workability and dynamic restoration mechanisms of Al-6.2Zn-2.1Mg-0.15Zr alloy during medium temperature compression

Medium temperature compressions were implemented in the range of 433–593 K and 0.001–5 s−1 to reveal the workability and dynamic restoration mechanisms of quenched Al-6.2Zn-2.1Mg-0.15Zr alloy. The activation energy evolution with processing parameters was inspected through the modified kinetic equation that derived by integrally considering the strain and deformation parameters, and the results suggested activation energies decreased with the increasing strain rate and deformation temperature while less affected by the increase of strain at a specific strain rate condition. The 3D processing map was constructed to optimize the processing regions, in which two unstable domains yielded by distinct microscopic instabilities were marked whilst the safe working regions could be identified at 533–593 K, 0.001–0.1 s−1 with dissipation efficiency >20%. The microstructural evolution of the compressed specimens was examined, and the results confirmed different types of dynamic recovery (DRV) involving dislocation migration and rearrangement were dominate restoration process during the compression. Also, the microstructures of the specimens deformed at unstable domains were characterized, the results revealed fluctuating flow localization, micro cracking and particles debonding as well as dynamic strain aging were responsible for compression failure.

Dynamic Response and Microstructural Characterization of Al3Zr/Al Composite Using 3D Processing Map

Dynamic Response and Microstructural Characterization of Al3Zr/Al Composite Using 3D Processing Map

An investigation on the hot workability and microstructural evolution of a novel dual-phase Mg–Li alloy by using 3D processing maps

Hot compression tests of a novel dual-phase Mg–Li alloy were performed in temperature range of 200–400 °C and strain rate range of 0.01–10s−1. 2D and 3D processing maps were established using Prasad's and Murty's instability criteria (methods) based on the dynamic materials model. It was found that one instability region obtained based on Prasad's instability criterion exist in the domain of power dissipation efficiency at a strain of 0.7. Prasad's and Murty's instability criteria are difficult to accurately characterize the instability characteristics of the alloy. The accuracy processing map rectified was obtained by means of Murty's and Prasad's instability criteria and microstructural analysis. On the basis of the processing map rectified, the optimum hot working parameters were obtained to be the temperature range of 320–400 °C and strain rate range of 0.01–0.4s−1 with the peak power dissipation efficiency. In this domain, the α phase undergone dynamic recrystallization (DRX) and dynamic recovery (DRV). The β-phase occurred DRX during the hot deformation. The instability regions lie in the temperature range of 200–250 °C with strain rate range of 0.01–1s−1 and the temperature range of 200–312 °C with strain rate range of 1–10s−1. Microstructural observations indicate that characteristics of the flow instabilities were flow localization, deformation twinning, the adiabatic shear bands and macro/micro cracking. The rectified processing map was successfully verified by the hot rolling test. The rectified processing map could accurately characterize workability characteristics of a novel dual-phase Mg–Li alloy and could be used for the optimization of hot working process parameters.

Experimental and Numerical Studies on Hot Compressive Deformation Behavior of a Cu-Ni-Sn-Mn-Zn Alloy.

Cu-9Ni-6Sn alloys have received widespread attention due to their good mechanical properties and resistance to stress relaxation in the electronic and electrical industries. The hot compression deformation behaviors of the Cu-9Ni-6Sn-0.3Mn-0.2Zn alloy were investigated using the Gleeble-3500 thermal simulator at a temperature range of 700-900 °C and a strain rate range of 0.001-1 s-1. The microstructural evolution of the Cu-9Ni-6Sn alloy during hot compression was studied by means of an optical microscope and a scanning electron microscope. The constitutive equation of hot compression of the alloy was constructed by peak flow stress, and the corresponding 3D hot processing maps were plotted. The results showed that the peak flow stress decreased with the increase in the compression temperature and the decrease in the strain rate. The hot deformation activation energy was calculated as 243.67 kJ/mol by the Arrhenius equation, and the optimum deformation parameters for the alloy were 740-760 °C and 840-900 °C with a strain rate of 0.001~0.01 s-1. According to Deform-3D finite element simulation results, the distribution of the equivalent strain field in the hot deformation samples was inhomogeneous. The alloy was more sensitive to the deformation rate than to the temperature. The simulation results can provide a guideline for the optimization of the microstructure and hot deformation parameters of the Cu-9Ni-6Sn-0.3Mn-0.2Zn alloy.

Three-dimensional processing map based on BP-ANN and interface microstructure of Fe/Al laminated sheet

To improve the coordinated deformability and working stability of pure iron/aluminum (Fe/Al) laminates, pack isothermal compression experiments were conducted at deformation temperatures and strain rates ranging from 623 to 823 K and 0.01 to 10 s−1, respectively. The back-propagation neural network (BP-ANN) model was developed to predict the flow behavior of these laminates. Three-dimensional (3D) processing maps were established to optimize processing parameters by considering the deformation temperature, strain, and strain rate variables. The results indicated that the BP-ANN model is quite accurate, with a correlation coefficient (R) of 0.9979 and a mean absolute error (MAE) of 1.4681%. A peak energy dissipation efficiency of 73% was obtained in the optimized parameter range of 723–823 K and 1-10 s−1. The excellent deformation coordination between iron and aluminum layers occurred at 723 K/10 s−1. A Fe/Al interdiffusion layer of about 1 μm was formed at the interface, and the iron and aluminum layers present fine recrystallized (DRX) grains along the interface. In the rolling experiment guided by the most suitable process conditions in the hot processing map, the Fe/Al bonding was good at 723 K, and the reduction rate was 55%.

Decreasing the mechanical anisotropy of the forged Mg-8.5Gd-2.5Y-1.5Zn-0.5Zr alloy by modulating blocky LPSO particles using multi-directional forging

The blocky LPSO particles were modulated by single-directional and multi-directional forging, and the effect of blocky LPSO particles on the anisotropy of mechanical properties of Mg-8.5Gd-2.5Y-1.5Zn-0.5Zr alloy forged parts was investigated. In the present work, 3D processing maps are established, and the forming domain that is both stable and power efficient is in the temperature range from 430 to 500 °C and strain rate range from 0.001 to 0.06 s − 1, which is used to guide the single-directional forging (SDF) and multi-directional forging (MDF) experiments. The tensile mechanical properties reveal that the blocky LPSO particles have an influence on the mechanical anisotropy, especially in terms of the elongation anisotropy. The blocky LPSO particles after the MDF process have a more regular shape and smaller size and are homogeneously distributed, which is responsible for the low anisotropy of the elongation. In addition, the age-hardening capability of the MDF part is higher than that of the SDF part.

Characterization of Hot Workability in AISI 4340 Based on a 3D Processing Map

This study performed high-temperature compression tests at the temperature 900 to 1200 °C and strain rate 0.01 to 10 s−1 to characterize the high-temperature deformation behavior of AISI 4340. The constitutive equation of AISI 4340 was expressed using the Arrhenius model and the Zener–Hollomon (Z) parameter. Dynamic Recrystallization (DRX) behavior was evaluated by observing the compressed specimen with Electron Backscatter Diffraction (EBSD). The processing map is based on the dissipation efficiency of the dynamic material model (DMM) and the plastic instability criterion of Ziegler. At strain 0.4, the power dissipation efficiency value is 0.5 or more, and the instable zones are immediately identified through the processing map. The strain, strain rate and temperature data obtained from the FEM simulation of the hot forging process are displayed on the proposed 3D processing map to avoid the flow instability zones and ensure high power dissipation efficiency zones, allowing the operator to control the process’s temperature and speed.

3D 변형 공정 지도 기반 AISI 4340 소재의 열간 단조 온도 및 변형률 속도 제어

This paper investigated the hot deformation behavior of an AISI 4340 material through high-temperature compression experiments. The compression tests were performed to obtain stress-strain curves at processing temperatures of 900, 1,000, 1,100, and 1,200℃, and the strain rates of 0.01, 0.1, 1, and 10 sSUP-1/SUP up to a true strain of 1.0 in the high-temperature compression mode of GleebleSUP®/SUP 3,500. A novel 3D processing map, constructed through power dissipation efficiency and Ziegler

Hot Deformation Behavior and 3D Processing Maps of Mn18Cr18N Steel

The isothermal hot deformation behavior in the ranges of 1023–1473 K (750–1200 °C) and 0.001–10 s−1 for 0.53 wt% N‐bearing Mn18Cr18N steel is studied with a Gleeble‐3500 thermomechanical simulator. The results indicate that the peak stress decreases with decreasing strain rate and increasing temperature. The calculated deformation activation energy of the experimental steel is 449.118 kJ mol−1 by regression analysis. At the same time, 3D processing maps are established based on experimental data and the principles of the dynamic materials model. The domain of stable deformation gradually expands with the increase in strain, while the instability region shrinks accordingly. From the microstructure of specimens and the processing maps established, it is clear that dynamic recrystallization emerges in the peak power dissipation efficiency domain, 1000–1150 °C/0.002–0.1 s−1, which is the optimum region of hot working of the steel.

Hot Formability Study of Cr5 Alloy Steel by Integration of FEM and 3D Processing Maps.

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.