Prediction of Hot Deformation Behavior in AlCoCrFeNi2.1 Eutectic High Entropy Alloy by Conventional and Artificial Neural Network Modeling
Springer Science and Business Media LLC - Trang 1-16 - 2023
Tóm tắt
In the present study, we report here the flow curve prediction of AlCoCrFeNi2.1 eutectic high entropy alloy (EHEA) at different temperatures and strain rates using different modeling techniques such as physics-based [modified Zerilli–Armstrong (ZA) model], phenomenological [modified Johnson–Cook (JC) model, Arrhenius model], and artificial neural network (ANN) modeling. Finally, the performance of all conventional (i.e., physics-based and phenomenological) and ANN modeling was evaluated by coefficient correlation (R) and average absolute relative error (AARE) parameters. It is found that the flow curve prediction by phenomenological modeling [i.e., modified JC model (R = 0.9646, AARE = 19.41%) and Arrhenius model (R = 0.9696, AARE = 14.62%)] is better as compared to physics-based modified ZA model (R = 0.9321, AARE = 21.42%). A comparative evaluation of obtained simulated results indicates that the prediction of hot deformation behavior of studied EHEA using ANN modeling (where R = 0.9985, and AARE = 4.57%) is matching excellently with experimental flow curve results as compared to conventional modeling approaches.
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