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Prediction of Creep Life Using an Explainable Artificial Intelligence Technique and Alloy Design Based on the Genetic Algorithm in Creep-Strength-Enhanced Ferritic 9% Cr Steel

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Abstract

Creep-strength-enhanced ferritic steels have been introduced for high-temperature components. The high accuracy of creep life prediction and new high creep-strength alloys are needed for safe long-term operation. In this paper, a data-driven method was used to overcome the limitations of the simple-parameter life prediction method that does not consider the complex interactions that occur between many input variables. The explainable artificial intelligence technology, such as the Shaply additive explanation value(SHAP), enables intuitive understanding of the effect of individual variables on creep life and helps to quantitatively evaluate the effect. The artificial intelligence model was optimized using a genetic algorithm, and a method for proposing an optimal alloy composition with a desired creep life could be presented. In this paper, the maximum expected creep life of 58,640 h in the standard component range of ASME SA213 T92 under the conditions of 650 °C and 100 MPa was predicted, and a new alloy composition having a creep life of over 100,000 h under the same conditions is proposed.

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Acknowledgements

The study was supported by the MOTIE Project No.20016472 and 20016054 of Research Center for Technological Innovation on Future Energy in Changwon National University.

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Authors and Affiliations

  1. Research Center for Technological Innovation on Future Energy, Changwon National University, Changwon, 51140, Republic of Korea

    Byeong Ook Kong, Min Soo Kim, Byung Hoon Kim & Je Hyun Lee

  2. Department of Materials Science and Engineering, Changwon National University, 51140, Changwon, Republic of Korea

    Je Hyun Lee

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  1. Byeong Ook Kong
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  2. Min Soo Kim
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Correspondence to Je Hyun Lee.

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Kong, B.O., Kim, M.S., Kim, B.H. et al. Prediction of Creep Life Using an Explainable Artificial Intelligence Technique and Alloy Design Based on the Genetic Algorithm in Creep-Strength-Enhanced Ferritic 9% Cr Steel. Met. Mater. Int. 29, 1334–1345 (2023). https://doi.org/10.1007/s12540-022-01312-7

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