Hot Deformation Behavior of a Beta Metastable TMZF Alloy: Microstructural and Constitutive Phenomenological Analysis

Abstract

A metastable beta TMZF alloy was tested by isothermal compression under different conditions of deformation temperature (923 to 1173 K), strain rate (0.172, 1.72, and 17.2 s−1), and a constant strain of 0.8. Stress–strain curves, constitutive constants calculations, and microstructural analysis were performed to understand the alloy’s hot working behavior in regards to the softening and hardening mechanisms operating during deformation. The primary softening mechanism was dynamic recovery, promoting dynamic recrystallization delay during deformation at higher temperatures and low strain rates. Mechanical twinning was an essential deformation mechanism of this alloy, being observed on a nanometric scale. Spinodal decomposition evidence was found to occur during hot deformation. Different models of phenomenological constitutive equations were tested to verify the effectiveness of flow stress prediction. The stress exponent n, derived from the strain-compensated Arrhenius-type constitutive model, presented values that point to the occurrence of internal stress at the beginning of the deformation, related to complex interactions of dislocations and dispersed phases.

Artificial neural network applicability in studying hot deformation behaviour of high-entropy alloys

“…The characterisation of hot deformation behaviour during hot working is vital for developing metalforming processes [8][9][10][11], for which the appropriate constitutive equations are utilised to predict the hot deformation behaviour of the materials under the prevailing loading conditions [12,13]. For this purpose, the empirical, semi-empirical, phenomenological, and physically-based models [14,15], as well as machinelearning approaches such as artificial neural networks (ANN) models [16][17][18][19][20][21][22][23] have been proposed so far.…”