Constitutive Equations for Describing the Hot Compressed Behavior of TC4–DT Titanium Alloy

Wang, Haoran; Wang, Chunge; Li, Muyu; Ma, Rui

doi:10.3390/ma13153424

Cited by 9 publications

(8 citation statements)

References 38 publications

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“…Lin et al [22] and Mandal et al [27] corrected the model by adding a strain rate index to the Zener-Hollomon parameter; however, this method requires that the predicted and experimental results agree well at a strain rate of 1 s −1 . Wang et al [28] modified the model by replacing the true strain rate with the effective strain rate. This method calculated the effective strain rate from the material constants calibrated at the true strain rate and then substituted the effective strain rate into the model.…”

Section: Introductionmentioning

confidence: 99%

Hot Deformation Behavior of the 25CrMo4 Steel Using a Modified Arrhenius Model

Tian

Zhang

et al. 2022

Materials

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25CrMo4 steel is widely used in the manufacturing of high-speed train axles due to its excellent mechanical properties. The purpose of this study is to develop an accurate modified constitutive model to describe the hot deformation behavior of the steel. Isothermal compression experiments were performed at different strain rates (0.01, 0.1, 0.5, and 1 s−1) and different temperatures (950, 1000, 1050, and 1100 °C) using a Gleeble-3800 thermal simulator. The microstructure after hot deformation was observed by the electron backscatter diffraction (EBSD), and the effects of temperature and strain rate were analyzed. The results showed that the coupling effect of temperature and strain rate on the dislocation density led to the change in the shape of the true stress–strain curve and that dynamic recovery (DRV) and dynamic recrystallization (DRX) caused the macroscopic softening phenomenon, with DRX being the main mechanism. Based on the true stress–strain curves, the strain-compensated Arrhenius constitutive model was calibrated. To improve prediction ability, a modified Arrhenius constitutive model was proposed, in which the temperature and strain rate coupling correction functions were incorporated. The original, modified Arrhenius models were evaluated according to the absolute relative error (ARE), the average absolute relative error (AARE), and the correlation coefficient (R2). Compared with the original model, the modified Arrhenius model has a higher prediction accuracy, with the ARE value mostly below 4%, the AARE value of 1.91%, and the R2 value of 0.9958.

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Section: Introductionmentioning

confidence: 99%

Hot Deformation Behavior of the 25CrMo4 Steel Using a Modified Arrhenius Model

Tian

Zhang

et al. 2022

Materials

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“…[23] The constitutive models mainly include phenomenological constitutive models, [24][25][26][27] physical-based constitutive models, [28][29][30][31][32] and data-based intelligent algorithm models. [33][34][35] Because of the high prediction precision, the phenomenological constitutive models are generally applied to forecast the flow behaviors of steels, [17,36] aluminum alloys, [37] titanium alloys, [38][39][40][41] etc. The physical-based constitutive models link the microstructure evolution and macroflow behaviors, and can deeply reflect the deformation mechanisms of alloys.…”

Section: Introductionmentioning

confidence: 99%

Dislocation Density–Based Model and Stacked Auto‐Encoder Model for Ti‐55511 Alloy with Basket‐Weave Microstructures Deformed in α + β Region

et al. 2021

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The flow behaviors of Ti-55511 alloy with basket-weave microstructures are investigated during the hot compression in α þ β region. It is observed that the flow behaviors are visibly influenced by the deformation temperature and strain rates. The primary softening mechanisms are the dynamic recovery of β grains and the spheroidization of lamellar α phases. Meanwhile, a dislocation densitybased model and a stacked auto-encoder (SAE) model are built to reveal the flow behaviors of the studied alloy. The relationship between the evolution of dislocation density and the hardening/softening mechanisms are considered in the dislocation density-based model, with the correlation coefficient being 0.9957. The structures of the established SAE model based on the intelligence algorithm are confirmed layer by layer. The SAE model has a high prediction accuracy when the number of hidden layers is 3, and the nodes of three hidden layers are 15, 40, and 35, respectively. It can demonstrate the nonlinear relationship between the flow stress and deformation parameters.

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“…The 7075 aluminum alloy is the earliest ultra-high strength aluminum alloy and is mainly used for the loadbearing parts of aircraft [1]. Similar to most alloys [4][5][6], the 7000 series aluminum alloys are generally produced by various thermoplastic processes, including extrusion, forging and rolling. However, their thermoplastic forming is complicated, because the deformation behavior is controlled by deformation conditions including strain, strain rate and temperature [7,8].…”

Section: Introductionmentioning

confidence: 99%

“…As an important means to characterize the relationship between the flow stress of materials and deformation parameters, the constitutive model is widely used, and also can provide great convenience for the study of hot deformation characteristics in finite element simulation [4]. Reliable simulation results require an accurate constitutive model, which is always pursued by scholars [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Some typical models are proposed, including phenomenological model, physical model and artificial neural network (ANN) model [12,13]. Recently, in the prediction of high temperature flow stress in aluminum alloys, a phenomenological constitutive model called the strain-compensated Arrhenius model (SCAM) has been extensively employed [4,[14][15][16][17][18][19][20]. Meanwhile, some statistical methods such as correlation coefficient (R) and average absolute relative error (AARE) are often employed to characterize the predictive power of the constitutive model.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Flow Stress of Annealed 7075 Al Alloy in Hot Deformation Using Strain-Compensated Arrhenius and Neural Network Models

Yang

et al. 2021

Materials

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Hot compression experiments of annealed 7075 Al alloy were performed on TA DIL805D at different temperatures (733, 693, 653, 613 and 573 K) with different strain rates (1.0, 0.1, 0.01 and 0.001 s−1.) Based on experimental data, the strain-compensated Arrhenius model (SCAM) and the back-propagation artificial neural network model (BP-ANN) were constructed for the prediction of the flow stress. The predictive power of the two models was estimated by residual analysis, correlation coefficient (R) and average absolute relative error (AARE). The results reveal that the deformation parameters including strain, strain rate, and temperature have a significant effect on the flow stress of the alloy. Compared with the SCAM model, the flow stress predicted by the BP-ANN model is in better agreement with experimental values. For the BP-ANN model, the maximum residual is only 1 MPa, while it is as high as 8 MPa for the SCAM model. The R and AARE for the SCAM model are 0.9967 and 3.26%, while their values for the BP-ANN model are 0.99998 and 0.18%, respectively. All these reflect that the BP-ANN model has more accurate prediction ability than the SCAM model, which can be applied to predict the flow stress of the alloy under high temperature deformation.

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Constitutive Equations for Describing the Hot Compressed Behavior of TC4–DT Titanium Alloy

Cited by 9 publications

References 38 publications

Hot Deformation Behavior of the 25CrMo4 Steel Using a Modified Arrhenius Model

Hot Deformation Behavior of the 25CrMo4 Steel Using a Modified Arrhenius Model

Dislocation Density–Based Model and Stacked Auto‐Encoder Model for Ti‐55511 Alloy with Basket‐Weave Microstructures Deformed in α + β Region

Prediction of Flow Stress of Annealed 7075 Al Alloy in Hot Deformation Using Strain-Compensated Arrhenius and Neural Network Models

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