Constitutive modeling of hot deformation behavior of AlCrFeNi multi-component alloy

• Published in: Vacuum 2022-07, Vol.201, p.111059, Article 111059
• Main Authors: Qiao, Ling, Zhu, Jingchuan
• Format: Article
• Language: English
• Subjects: AlCrFeNi MEAs; Arrhenius-type constitutive equation; Artificial neural network; Hot deformation behavior; Processing map; Support vector machine
• ISSN: 0042-207X; 1879-2715
• DOI: 10.1016/j.vacuum.2022.111059

In present paper, the hot deformation behavior of an equiatomic AlCrFeNi medium entropy alloy (MEAs) was investigated. Hot compression tests were carried out at various temperatures ranging from 800 °C to 1100 °C at different strain rates from 0.001 s−1 to 1 s−1. The flow stress analysis was performed on AlCrFeNi MEAs by using Arrhenius type relationship, and a linear dependence of flow stress on Zener–Hollomon parameter (Z) can be determined. Moreover, a comparative study was carried out to further evaluate the predictability of the Arrhenius-type constitutive equation and artificial neural network (ANN), support vector machine (SVM) model. The results show that the constitutive model developed by SVM performs better to describe the interdependency between deformation temperature, strain rate and flow stress. The activation energy (Q) for high-temperature deformation was calculated as 376.6 kJ/mol, and the related strain rate sensitivity (m), the power dissipation (η), and instability parameter (ξ) were also derived. The processing maps suggest that the flow instability tends to occur at high strain rate and the optimum processing parameters can be determined to direct the hot working process. •The mixture of Fe-Cr-rich A2 structure and B2 phase was identified in as-cast AlCrFeNi MCAs.•Constitutive equation correlating flow stress, strain rate, and temperature is formulated.•The predictive performance of Arrhenius-type constitutive equation, ANN and SVM were evaluated.•Power dissipation efficiency and instability maps were generated.•The hot processing parameters can be determined by hot working maps.