Hot Deformation Behavior of a Novel Ni-Cr-Fe Based Superalloy

DU Fangxin; ZHAO Cong; LIU Jinping; LIU Jinsong

doi:10.3969/j.issn.1674-6457.2025.09.017

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Journal of Netshape Forming Engineering ›› 2025, Vol. 17 ›› Issue (9) : 176-184. DOI: 10.3969/j.issn.1674-6457.2025.09.017

Superalloy Forming

Hot Deformation Behavior of a Novel Ni-Cr-Fe Based Superalloy

DU Fangxin^1,*, ZHAO Cong¹, LIU Jinping², LIU Jinsong¹

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Abstract

The work aims to study the hot deformation behavior of a novel Ni-Cr-Fe based superalloy in the temperature range of 1 075-1 150 ℃ and strain rate range of 0.001-1 s^-1 by carrying out hot compression tests on a Gleeble-3500 thermo- mechanical simulator. Metallographic microscope and transmission electron microscope were used to observe hot deformation microstructure of the studied alloy. At the same time, the Arrhenius constitutive model based on strain compensation and BP (back-propagation) neural network model were also established. The flow stress of a novel Ni-Cr-Fe based superalloy was significantly affected by hot deformation parameters, which was negatively correlated with deformation temperature and positively correlated with strain rate. The microstructure analysis showed that the original grains inside the studied alloy were basically replaced by fine dynamic recrystallization (DRX) grains under the deformation condition of 1 150 ℃/0.01 s^-1. Under the deformation condition of 0.1 s^-1/1 075 ℃, a large number of dislocation tangles were clearly observed. At the same time, the dislocation wall formed by dislocation accumulation and migration was also observed. As the strain rate decreased to 0.01 s^-1, it was found that the dislocation density inside the grains decreased significantly and the DRX nuclei was observed. Two kinds of models were used to predict the variation of flow stress with strain. The correlation coefficient of BP neural network model was 0.998 5 and the average relative error was 1.752 1%. The prediction accuracy of BP neural network model was higher than that of Arrhenius constitutive model based on strain compensation. The established BP neural network model is more suitable for accurately predicting the flow stress of a novel Ni-Cr-Fe based superalloy.

Key words

nickel-based superalloy / hot deformation / microstructure / constitutive model / neural network

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DU Fangxin, ZHAO Cong, LIU Jinping, LIU Jinsong. Hot Deformation Behavior of a Novel Ni-Cr-Fe Based Superalloy[J]. Journal of Netshape Forming Engineering. 2025, 17(9): 176-184 https://doi.org/10.3969/j.issn.1674-6457.2025.09.017

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Funding

Guizhou Science and Technology Foundation(ZK[2024]Key 062); Science and Technology Projects of Hubei Provincial Education Department (B2018503); The Research and Innovation Team Building Plan of Wuhan City Polytechnic (2023whcvcTD02)