A modified constitutive model based on Arrhenius-type equation to predict the flow behavior of Fe–36%Ni Invar alloy

Abstract

Abstract

Recrystallisation-assisted creep of an austenitic Fe-Ni alloy under low stresses after hot deformation

“…The flow curves obtained during pre-deformation were close to those reported by [34], yet with a slightly lower flow stress, possibly due to a difference in lubrication conditions and strain measurement method. The effects of pre-deformation strain rate and temperature on stress relaxation are shown in Figs 2a and 2b, respectively.…”

“…During the pre-deformation stage, the specimens were first heated up to a given temperature (between 850 and 1050°C) at 30°C/s under a very low compressive stress,  hold , (approximately 4.5 MPa, in order to hold the specimen) and then held for 10 s for temperature homogenisation. They were then compression loaded under displacement control with a constant strain rate up to a 30% axial strain, which is known to be the critical deformation level to trigger dynamic recrystallisation in a similar Fe-32%Ni alloy at 1000°C and 2×10 -3 s -1 [43], and in a Fe-36%Ni alloy [34] in conditions close to those investigated in the present work. After pre-deformation, either the displacement of the anvils was kept constant (see stress relaxation tests in Fig.…”

“…(A.1), ̇ is constant and its value is taken as the strain rate at the beginning of the creep test, before the onset of recrystallisation. Also, ̇ is assigned to be the flow behaviour of the fully recrystallised material, determined from delayed creep tests, and described as in [34],…”

“…It ranged between 1000 and 1020°C (for 10-20% deformation per hot torsion pass at 0.3 s -1 ), yet with no associated microstructural observation. The high-temperature flow behaviour of a Fe-36Ni-type alloy was first reported [34] on a coarse-grained Fe-37%Ni-0.02%Mn-0.03%Si subjected to homogenization at 1200°C, then to isothermal compression at 850-1100°C, for strain rates between 10 -2 and 10 s -1 . From the reported electron backscatter diffraction (EBSD) maps, only the high temperature, low strain rate conditions were found to lead to continuous dynamic recrystallisation; post-dynamic and static recrystallisation phenomena were not addressed in their paper.…”

The Parameters Identification of High-Temperature Constitutive Model Based on Inverse Optimization Method and 3D Processing Map of Cr8 Alloy Steel

“…Olga Yakovtseva [ 5 ] used the mathematical Arrhenius constitutive model and artificial neural network model to predict the flow behavior of Al-Zn-Mg alloy, and the results showed that both of them had good predictability, and the prediction accuracy of the artificial neural network model was slightly higher. Shuai He [ 6 ] took the effect of strain on the Arrhenius model′s constants and thermal deformation activation energy (Q) as an independent function, and used the sixth-degree polynomial to perform the fitting. The correlation coefficient (R) and average absolute relative error (AARE) of the measured and predicted data were estimated to be 0.99026% and 3.94%, respectively, which verified the precision of the modified Arrhenius constitutive model.…”