Hot Deformation Behavior of AA6061-T6 Aluminum Alloy: Flow Stress, Constitutive Modeling, and Microstructural Evolution

AA6061-T6 undergoes work hardening, dynamic recovery, and progressive flow softening during hot torsion, yet a systematic single-campaign dataset with quantified experimental uncertainty is absent from the literature. Gleeble hot torsion tests were conducted at eleven conditions from 250 to 450 °C and 0.91 to 9.07 s−1. With the stress multiplier fixed a priori at α = 0.045 MPa−1 from compression literature on this alloy, a two-stage calibration determined the remaining Garofalo–Arrhenius constants: the temperature-slope stage anchors Q = 151.1 kJ mol−1 (consistent with Al lattice self-diffusion), and a global Zener–Hollomon regression conditional on Q yields n = 1.371 and A = 3.51 × 1010 s−1; a fully simultaneous three-parameter fit is shown to be practically unidentifiable on the three-level matrix. Training AARE = 15.5% (R = 0.908); leave-one-out cross-validation gives AARE = 23.0%, bounding the predictive uncertainty. The Prasad instability map identifies 400–450 °C at 0.91–2.72 s−1 as the optimal hot-forming window; flow instability is predicted at 350 °C (outright at 2.72 and 9.07 s−1, with the 0.91 s−1 condition at the map boundary), and macroscopic fracture was observed in all three specimens tested there. Optical microscopy in specimen T1 (εeq = 3.69) shows elongated subgrains at the gauge center and fine-grained zones near the fracture surface consistent with localized geometric dynamic recrystallization. The activation energy, smooth post-peak softening, and subgrain wall morphology identify dynamic recovery as the likely dominant restoration mechanism. Adiabatic heating and a 24% peak-stress repeatability scatter at the single repeated condition (450 °C, 9.07 s−1) are quantified and propagated into the constitutive model uncertainty bounds. Because the training-to-cross-validation error gap (15.5% versus 23.0% AARE) reflects the limited three-level strain-rate matrix, the calibrated equation is recommended for interpolation within the tested window of 300 to 450 °C and 0.91 to 9.07 s−1 (noting that 300 °C was tested only at 0.91 s−1, so higher-rate predictions at that temperature are extrapolations) and for forming-window identification, not for extrapolation beyond this domain without additional validation data.