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Zhenhua Liu

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Open access Aug 2026

Hot Deformation Behavior of AA3102 Aluminum Alloy: Constitutive Modeling, Microstructural Evolution and Numerical Simulation

This study systematically investigates the hot deformation behavior and microstructural evolution of AA3102 aluminum alloy through isothermal uniaxial compression tests conducted at 400–550 °C and strain rates of 0.01–10 s−1. Previous studies on 3xxx-series Al–Mn alloys have mainly considered temperature and strain-rate effects while neglecting strain-dependent material parameter variations, limiting prediction accuracy under large deformation and obscuring dynamic softening mechanisms. Here, the experimental flow stress data were corrected for interfacial friction and adiabatic temperature rise. A sixth-order strain-compensated Arrhenius constitutive model was then developed to describe the coupled effects of temperature, strain rate, and strain. Full-strain-range power dissipation and flow instability maps were constructed using the dynamic material model, while optical microscopy and DEFORM-3D simulations were employed to clarify microstructural evolution and deformation inhomogeneity. The model achieved a correlation coefficient of 0.9841 and an average absolute relative error of 3.67%, demonstrating high predictive accuracy. No flow instability was detected within the investigated range, indicating excellent hot formability. The favorable compression-processing window was identified as 500–550 °C and 0.1–1 s−1, while the peak power-dissipation efficiency increased from 30.55% at ε = 0.2 to 32.90% at ε = 0.8. Optical-microstructural observations suggest that increasing temperature and decreasing strain rate are associated with an increasing contribution of dynamic recrystallization relative to dynamic recovery. Finite-element results further reveal pronounced spatial variations in strain, temperature, strain rate, and stress during compression. These findings provide baseline constitutive and thermomechanical information for subsequent AA3102 hot-extrusion optimization.

Xian-Zheng Liu, N. Jamadon, Xiao-Ming Liu et al. · 0 citations

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