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Predicting the Parabolic Rate Constants of High-Temperature Oxidation of Ti Alloys Using Machine Learning

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Abstract

In this study, we attempt to build a statistical (machine) learning model to predict the parabolic rate constant \((k_{\text{P}} )\) for the high-temperature oxidation of Ti alloys. Exploring the experimental studies on high-temperature oxidation of Ti alloys, we built our dataset for machine learning. Apart from the alloy composition, we included the constituent phase of the alloy, temperature of oxidation, time for oxidation, oxygen and moisture content, remaining atmosphere (gas except O2 gas in dry atmosphere), and mode of oxidation testing as the independent features while the parabolic rate constant \((k_{\text{P}} )\) is set as the target feature. We employed three different ML models to predict the ‘\(k_{\text{P}}\)’ for Ti alloys. Among the regression models, the gradient boosting regressor yields the coefficient of determination (R2) of 0.92 for \(k_{\text{P}}\). The knowledge gained from this study can be used to design novel Ti alloys with excellent resistance towards high-temperature oxidation.

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Acknowledgements

SKB is thankful to Dr. Sayan Sarcar, Assistant Professor, Faculty of Library Information and Media Science, University of Tsukuba, Tsukuba, Japan for fruitful discussions. This work was supported by the Council for Science, Technology and Innovation under the Cross-ministerial Strategic Innovation Promotion Program. This study was also partially supported by the Japan Society for the Promotion of Science KAKENHI Grant (Number 18H01718), ISIJ Research Promotion Grant and NIMS-Tohoku cross appointment system.

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Authors and Affiliations

  1. Research Center for Structural Materials, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki, 305-0047, Japan

    Somesh Kr. Bhattacharya, Ryoji Sahara & Takayuki Narushima

  2. Department of Materials Processing, Tohoku University, 6-6-2 Aza Aoba, Aramaki, Aoba-ku, Sendai, 980-8579, Japan

    Ryoji Sahara & Takayuki Narushima

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  1. Somesh Kr. Bhattacharya
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  2. Ryoji Sahara
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  3. Takayuki Narushima
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Correspondence to Somesh Kr. Bhattacharya.

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Bhattacharya, S.K., Sahara, R. & Narushima, T. Predicting the Parabolic Rate Constants of High-Temperature Oxidation of Ti Alloys Using Machine Learning. Oxid Met 94, 205–218 (2020). https://doi.org/10.1007/s11085-020-09986-3

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  • DOI: https://doi.org/10.1007/s11085-020-09986-3

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