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Microstructural Evolution and Mechanical Properties of Graphene-Reinforced Ti-6Al-4V Composites Synthesized via Spark Plasma Sintering
Open AccessFeature PaperArticle

Flow Stress of Ti-6Al-4V during Hot Deformation: Decision Tree Modeling

1
Metal Forming R&D Group, Korea Institute of Industrial Technology, 156 Gaetbeol-ro, Yeonsu-gu, Incheon 21999, Korea
2
Department of Smart Automobile, Soonchunhyang University, 22 Soonchunhyang-ro, Sinchang-myeon, Asan-si, Chungcheongnam-do 31538, Korea
*
Author to whom correspondence should be addressed.
Metals 2020, 10(6), 739; https://doi.org/10.3390/met10060739
Received: 10 April 2020 / Revised: 26 May 2020 / Accepted: 27 May 2020 / Published: 2 June 2020
In this study, the flow stress of Ti-6Al-4V during hot deformation was modeled using a decision tree algorithm. Hot compression experiments for Ti-6Al-4V in a Gleeble-3500 thermomechanical simulator were performed under a strain rate of 0.002–20 s–1 and temperatures of 575–725 °C. After the experiments, flow stress behavior was modeled, first by a traditional Arrhenius type equation, second by utilizing the artificial neural network, and lastly, with the aid of the decision tree algorithm. While the characteristics of measured flow stress were noticeably dependent on the resulting strain rate and temperature, the modeling accuracy regarding the flow stress results of the Arrhenius type equation, neural network approach and decision tree algorithm were compared. The decision tree algorithm predicted the flow stress most effectively. View Full-Text
Keywords: Ti-6Al-4V; hot deformation; decision tree Ti-6Al-4V; hot deformation; decision tree
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Lim, S.-S.; Lee, H.-J.; Song, S.-H. Flow Stress of Ti-6Al-4V during Hot Deformation: Decision Tree Modeling. Metals 2020, 10, 739.

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