Deformation behavior of an Al–Cu–Mn–Fe–Zr alloy is investigated by plane strain compression tests at a warm deformation region. The flow stress first increases and then keeps steady, and the flow stress increases with reducing temperature or raising strain rate. However, the influence of strain rate on flow stress is weak at 100 and 150 °C. The dynamic recovery (DRV) mechanism is the dominant mechanism to balance the work hardening, and a larger number of dislocations are consumed at low strain rates. So, the deformed grains are difficult to reach the critical strain for dynamic recrystallization (DRX). When the strain rate is relatively high, the critical strain can be reached in a short time, which promotes the process of DRX. In addition, an improved unified constitutive model is built based on the evolution of dislocation density. The predicted flow stresses are in a close agreement with the measured results, proving that the built model can nicely reproduce the flow behavior.

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The flow behaviors of Ti-55511 alloy with basket-weave microstructures are investigated during the hot compression in α þ β region. It is observed that the flow behaviors are visibly influenced by the deformation temperature and strain rates. The primary softening mechanisms are the dynamic recovery of β grains and the spheroidization of lamellar α phases. Meanwhile, a dislocation densitybased model and a stacked auto-encoder (SAE) model are built to reveal the flow behaviors of the studied alloy. The relationship between the evolution of dislocation density and the hardening/softening mechanisms are considered in the dislocation density-based model, with the correlation coefficient being 0.9957. The structures of the established SAE model based on the intelligence algorithm are confirmed layer by layer. The SAE model has a high prediction accuracy when the number of hidden layers is 3, and the nodes of three hidden layers are 15, 40, and 35, respectively. It can demonstrate the nonlinear relationship between the flow stress and deformation parameters.

The rheological behavior and deformation mechanisms of a new powder metallurgy (P/M) superalloy at various deformation conditions are researched. The deformation conditions have significant influence on the rheological stress. Increasing the deformation temperature or decreasing the strain rate can decrease the rheological stress. The discontinuous hardening and softening phenomena are observed at the strain rate of 1 s−1, resulting from the complex phase transformation and dynamic recrystallization. Besides, the deformation activity energy (Q) declines with increasing the strain. The phenomenon is attributed to the spheroidization of γ′ phase and the decreased content/aspect ratio of γ′ phase. The deformation mechanisms of the researched superalloy are the accumulation of dislocation, stacking faults shearing, dislocations pinned by γ′ phase, and the formation of microtwins during hot deformation. The strain‐compensated Arrhenius and particle swarm optimization‐based backpropagation artificial neural network (PSO‐BP ANN) models are established to predict the rheological behavior. Compared to the strain‐compensated Arrhenius equation, the developed PSO‐BP ANN model presents the higher accuracy in predicting the rheological behavior of the researched alloy. Furthermore, for the developed PSO‐BP ANN model, the correlation coefficient is 0.9995, and the root mean square error is 1.224 MPa. So, the forecasted rheological stresses are consistent with the measured ones.

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