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<p>The hot flow behavior of FeCoCrNiAl<sub>0.1</sub> high-entropy alloys (HEAs) was investigated using a Gleeble−3500 thermal simulation test machine under hot deformation conditions at 950-1100°C/0.001-1&#xa0;s<sup>-1</sup>. A modified Zerilli-Armstrong (Z-A) model, a modified Johnson-Cook (J-C) model, and a GA-BP neural network were devised to predict the hot flow behavior. Model accuracy was evaluated using correlation coefficients (R<sup>2</sup>) and mean absolute relative error (AARE). Additionally, electron backscatter diffraction (EBSD) analysis was employed to examine microstructural evolution of the studied alloy after hot compression experiments. The results indicate that the modified Z-A model yielded R<sup>2</sup> of 0.9354 and AARE of 7.52%, while the modified J-C model attained R<sup>2</sup> of 0.9435 and AARE of 6.38%. Notably, GA-BP neural network exhibits the highest accuracy, with R<sup>2</sup> reaching 0.9969 and AARE of 2.66%. Microstructural analysis revealed that many fine recrystallized grains were formed at grain boundaries and within grain interiors. Continuous dynamic recrystallization (CDRX) and discontinuous dynamic recrystallization (DDRX) occurred simultaneously during hot deformation.</p>

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Evaluation of Hot Flow Behavior Models in FeCoCrNiAl0.1 High-Entropy Alloys by Modified Johnson-Cook Model, Modified Zerilli-Armstrong Model and GA-BP Neural Network

  • 期刊论文

  • 发表日期：

    2025年9月9日

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  • Bo Li,
  • Yuan Song,
  • Zhicheng Huang,
  • Han Yang,
  • Zhaojie Chu,
  • Xicong Ye,
  • Dong Fang

摘要

The hot flow behavior of FeCoCrNiAl0.1 high-entropy alloys (HEAs) was investigated using a Gleeble−3500 thermal simulation test machine under hot deformation conditions at 950-1100°C/0.001-1 s-1. A modified Zerilli-Armstrong (Z-A) model, a modified Johnson-Cook (J-C) model, and a GA-BP neural network were devised to predict the hot flow behavior. Model accuracy was evaluated using correlation coefficients (R2) and mean absolute relative error (AARE). Additionally, electron backscatter diffraction (EBSD) analysis was employed to examine microstructural evolution of the studied alloy after hot compression experiments. The results indicate that the modified Z-A model yielded R2 of 0.9354 and AARE of 7.52%, while the modified J-C model attained R2 of 0.9435 and AARE of 6.38%. Notably, GA-BP neural network exhibits the highest accuracy, with R2 reaching 0.9969 and AARE of 2.66%. Microstructural analysis revealed that many fine recrystallized grains were formed at grain boundaries and within grain interiors. Continuous dynamic recrystallization (CDRX) and discontinuous dynamic recrystallization (DDRX) occurred simultaneously during hot deformation.