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

Yang, Huibin; Bu, Hengyong; Li, Mengnie; Lu, Xin

doi:10.3390/ma14205986

Cited by 22 publications

(12 citation statements)

References 35 publications

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“…For example, Deb et al [21] utilized a modified J-C model and deep learning algorithm to develop a constitutive model for TC4 alloy, which effectively predicted the flow stress behavior under various hot working conditions. Yang et al [22] used the Arrhenius model and the BP neural network algorithm to accurately describe the constitutive relationship between strain rate, hot working temperature, and flow stress of the 7075 alloy, and they analyzed the prediction accuracy of these two models. Yu et al [23] utilized empirical models and deep learning algorithm models to develop multiple sets of constitutive models for the TG6 alloy, and they compared the applicability of different models.…”

Section: Introductionmentioning

confidence: 99%

Study on the Constitutive Modeling of (2.5 vol%TiB + 2.5 vol%TiC)/TC4 Composites under Hot Compression Conditions

Qiang,

Wang,

Wang

et al. 2024

Materials

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The hot deformation behavior of titanium matrix composites plays a crucial role in determining the performance of the formed components. Therefore, it is significant to establish an accurate constitutive relationship between material deformation parameters and flow stress. In this study, hot compression experiments were conducted on a (2.5 vol%TiB + 2.5 vol%TiC)/TC4. The experiments were performed under temperatures ranging from 1013.15 to 1133.15 K and strain rates ranging from 0.001 to 0.1 s−1. Based on the stress–strain data obtained from the experiment, the constitutive models were established by using the Arrhenius model and the BP neural network algorithm, respectively. Considering the relationship between strain rate, hot working temperature, and flow stress, a comparative analysis was conducted to evaluate the prediction accuracy of two different constitutive models. The research results indicate that the flow stress of (2.5 vol%TiB + 2.5 vol%TiC)/TC4 increases with decreasing temperature and increasing strain rate, and the stress–strain curve shows obvious work hardening and softening behaviors. Both the Arrhenius model and the BP neural network algorithm are effective in predicting the hot compression flow stress of (2.5 vol%TiB + 2.5 vol%TiC)/TC4, but the average relative error and root mean square error of the BP neural network algorithm are smaller and the correlation coefficient is higher, thus possessing higher accuracy and reliability.

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Section: Introductionmentioning

confidence: 99%

Study on the Constitutive Modeling of (2.5 vol%TiB + 2.5 vol%TiC)/TC4 Composites under Hot Compression Conditions

Qiang,

Wang,

Wang

et al. 2024

Materials

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“…Later, a few constitutive models for reconstituting high-temperature deformation features of alloys were built [ 19 , 20 , 21 , 22 ]. Typically, multi-type phenomenological equations [ 23 , 24 , 25 , 26 , 27 ] as well as machine learning models [ 28 , 29 ] are constructed to visualize thermal-flow-forming features in Al–Zn–Mg–Cu alloys and other alloys [ 30 , 31 , 32 , 33 , 34 ]. Additionally, multi-type microstructural changing mechanisms affecting the flow behaviors have been considered, and physical mechanism constitutive (PMC) models have been built [ 25 , 35 , 36 , 37 ].…”

Section: Introductionmentioning

confidence: 99%

High-Temperature Tensile Characteristics of an Al–Zn–Mg–Cu Alloy: Fracture Characteristics and a Physical Mechanism Constitutive Model

He,

Chen,

Chen

et al. 2024

Materials

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High-temperature tensile tests were developed to explore the flow features of an Al-Zn-Mg-Cu alloy. The fracture characteristics and microstructural evolution mechanisms were thoroughly revealed. The results demonstrated that both intergranular fractures and ductile fractures occurred, which affected the hot tensile fracture mechanism. During high-temperature tensile, the second phase (Al2CuMg) at the grain boundaries (GBs) promoted the formation and accumulation of dimples. With the continual progression of high-temperature tensile, the aggregation/coarsening of dimples along GBs appear, aggravating the intergranular fracture. The coalescence and coarsen of dimples are reinforced at higher tensile temperatures or lower strain rates. Considering the impact of microstructural evolution and dimple formation/coarsening on tensile stresses, a physical mechanism constitutive (PMC) equation is herein proposed. According to the validation and analysis, the predictive results were in preferable accordance with the testing data, showing the outstanding reconfiguration capability of the PMC model for high-temperature tensile features in Al–Zn–Mg–Cu alloys.

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“…Aluminum alloys have been the preferred candidates for lightweighting in aerospace, transportation, and other sectors due to their high specific strength [1][2][3][4]. However, traditional commercial aluminum alloys gradually fail to satisfy the increasingly stringent requirements of mechanical properties and corrosion resistance, etc.…”

Section: Introductionmentioning

confidence: 99%

Hot Deformation Behavior and Processing Maps of an As-Cast Al-5Mg-3Zn-1Cu (wt%) Alloy

et al. 2023

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One of the key issues limiting the application of Al-Mg-Zn-Cu alloys in the automotive industry is forming at a low cost. Isothermal uniaxial compression was accomplished in the range of 300–450 °C, 0.001–10 s−1 to study the hot deformation behavior of an as-cast Al-5.07Mg-3.01Zn-1.11Cu-0.01Ti alloy. Its rheological behavior presented characteristics of work-hardening followed by dynamic softening and its flow stress was accurately described by the proposed strain-compensated Arrhenius-type constitutive model. Three-dimensional processing maps were established. The instability was mainly concentrated in regions with high strain rates or low temperatures, with cracking being the main instability. A workable domain was determined as 385–450 °C, 0.001–0.26 s−1, in which dynamic recovery (DRV) and dynamic recrystallization (DRX) occurred. As the temperature rose, the dominant dynamic softening mechanism shifted from DRV to DRX. The DRX mechanisms transformed from continuous dynamic recrystallization (CDRX), discontinuous dynamic recrystallization (DDRX), and particle-stimulated nucleation (PSN) at 350 °C, 0.1 s−1 to CDRX and DDRX at 450 °C, 0.01 s−1, and eventually to DDRX at 450 °C, 0.001 s−1. The eutectic T-Mg32(AlZnCu)49 phase facilitated DRX nucleation and did not trigger instability in the workable domain. This work demonstrates that the workability of as-cast Al-Mg-Zn-Cu alloys with low Zn/Mg ratios is sufficient for hot forming.

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

Cited by 22 publications

References 35 publications

Study on the Constitutive Modeling of (2.5 vol%TiB + 2.5 vol%TiC)/TC4 Composites under Hot Compression Conditions

Study on the Constitutive Modeling of (2.5 vol%TiB + 2.5 vol%TiC)/TC4 Composites under Hot Compression Conditions

High-Temperature Tensile Characteristics of an Al–Zn–Mg–Cu Alloy: Fracture Characteristics and a Physical Mechanism Constitutive Model

Hot Deformation Behavior and Processing Maps of an As-Cast Al-5Mg-3Zn-1Cu (wt%) Alloy

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