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

Zhi, Chenchen; Wu, Zhenyu; Lei, Junyi; Huang, Zhiquan; Xv, Haijie; Zhu, Yanjun; Wang, Jia; Liu, Pengtao; Ma, Lifeng

doi:10.3390/met13040645

Cited by 4 publications

(2 citation statements)

References 23 publications

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“…The hot processing map encompasses both a power dissipation efficiency map and an instability map. It effectively portrays the correlation between thermal deformation parameters and the mechanism of microstructure evolution (Zhi et al, 2023). The model treats the thermal processing of materials as an energyconsuming system, in which the total power P tot of the system includes two parts.…”

Section: Hot Processing Mapsmentioning

confidence: 99%

Prediction of flow stress and microstructure evolution mechanism during thermal tensile process of ZK60 alloy

Liu,

Yang,

Liao

et al. 2024

Front. Mater.

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In this work, the hot deformation behavior and microstructure evolution of ZK60 alloy are investigated. Meanwhile, constructive models and hot processing maps of ZK60 alloy during thermal tension are also established. Toward these ends, thermal tensile tests were performed at elevated deformation temperatures (523 K–673 K) and wide-ranging strain rates (0.0005 s−1 to 0.1 s−1). The findings indicated that as the tensile temperature increases and the strain rate decreases, the flow stress exhibited a decrease. To better evaluate the flow behavior of the alloy, Arrhenius model coupled strain effects and particle swarm optimization support vector machine (PSO-SVM) regression model are developed. Both the developed Arrhenius model and PSO-SVM regression model could depict the flow stress of the hot deformation ZK60 alloy. However, the results comparison revealed that the PSO-SVM regression model provides a more accurate prediction of the stress in the studied alloy with the AARE and R of 1.12% and 0.9984, respectively. The microstructure observation revealed that the primary softening mechanism in the alloy is predominantly dynamic recrystallization (DRX). Using the created hot processing map, the stability processing areas for this alloy were concentrated in the range of 573 K–653 K with a strain rate of 0.001 s-1 to 0.08 s-1. The described model is implemented in the finite element software. Then, the wire-drawing process of ZK60 alloy is also simulated.

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Section: Hot Processing Mapsmentioning

confidence: 99%

Prediction of flow stress and microstructure evolution mechanism during thermal tensile process of ZK60 alloy

Liu,

Yang,

Liao

et al. 2024

Front. Mater.

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“…Existing processing maps have limitations in not showing the effect of strain on workability. Some researchers developed a 3D processing map according to the strain of the material to solve this problem [29][30][31]. Recently, Park et al developed FEM simulation data that can plot on the 3D processing map to control process parameters, avoid flow instability and include high power dissipation efficiency [32].…”

Section: Introductionmentioning

confidence: 99%

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

Park

Han

Kwon

et al. 2023

Metals

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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.

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Optimization of Hot Backward Extrusion Process Parameters for Thin-Walled Tubes of Mg-9Gd-3Y Alloy Based on 3D Processing Maps

Zeng,

Dong,

Wang

et al. 2024

J. of Materi Eng and Perform

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

Cited by 4 publications

References 23 publications

Prediction of flow stress and microstructure evolution mechanism during thermal tensile process of ZK60 alloy

Prediction of flow stress and microstructure evolution mechanism during thermal tensile process of ZK60 alloy

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

Optimization of Hot Backward Extrusion Process Parameters for Thin-Walled Tubes of Mg-9Gd-3Y Alloy Based on 3D Processing Maps

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