A review of hot deformation behavior and constitutive models to predict flow stress of high-entropy alloys

被引:202
作者
Savaedi, Zeinab [1 ]
Motallebi, Reza [1 ]
Mirzadeh, Hamed [1 ]
机构
[1] Univ Tehran, Sch Met & Mat Engn, Coll Engn, POB 11155-4563, Tehran, Iran
关键词
Multi-principal element alloys; Hot deformation; Mechanical properties; Constitutive analysis; Flow stress; ARTIFICIAL NEURAL-NETWORK; ZN MAGNESIUM ALLOYS; DYNAMIC RECRYSTALLIZATION BEHAVIOR; SEVERE PLASTIC-DEFORMATION; CARBON MICROALLOYED STEEL; MECHANICAL-PROPERTIES; RATE SUPERPLASTICITY; THRESHOLD STRESS; PROCESSING MAPS; JOHNSON-COOK;
D O I
10.1016/j.jallcom.2022.163964
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
This review article summarizes the hot deformation behavior of high entropy alloys (HEAs) and the corresponding constitutive description of flow stress. The potential of hot working for grain refinement via dynamic recrystallization (DRX), reduction of casting defects, and enhancement of mechanical properties of HEAs is explained. The necklace formation, work hardening analysis for identification of the occurrence and initiation of DRX, and the effects of processing parameters on dynamically recrystallized grain size are discussed. The effects of deformation conditions (represented by the Zener-Hollomon parameter), alloying elements, dynamic precipitation, and the presence of phases on the hot deformation behavior and restoration processes of DRX and dynamic recovery (DRV) are overviewed. The application of processing maps for the characterization of the onset of flow instability, cracking, flow softening, and DRX during hot forming of HEAs is presented. Regarding the constitutive modeling of flow stress for characterization of material flow (at different deformation temperatures, strain rates, and strain), the utilization of the threshold stress (due to the presence of phases or their precipitation during high-temperature deformation), and temperature-dependent Young's modulus, as well as correlating the obtained values of deformation activation energy and stress exponent with the expected ones from the creep theories are taken into account. Afterward, the available methods and equations for modeling and prediction of flow curves during thermomechanical processing are assessed, where the strain-compensated Arrhenius model, artificial neural network (ANN) model, Zerilli-Armstrong model, Johnson-Cook model, Hensel-Spittel model, and dislocation density-based multiscale constitutive model are presented. Finally, some suggestions for future research works are proposed. (c) 2022 Elsevier B.V. All rights reserved.
引用
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页数:21
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