Metal Temperature Estimation from Microstructural Features in Stainless Steel Image with Sparse Modeling
Author:
Affiliation:
1. Graduate School of Informatics and Engineering, The University of Electro-Communications
2. National Institute for Materials Science (NIMS)
Publisher
Japanese Neural Network Society
Link
https://www.jstage.jst.go.jp/article/jnns/29/1/29_15/_pdf
Reference11 articles.
1. 1) Endo, A., Sawada, K., Nagata, K., Yoshikawa, H., Shouno, H. (2021): Prediction of metal temperature by microstructural features in creep exposed austenitic stainless steel with sparse modeling, Science and Technology of Advanced Materials: Methods, Vol.1, No.1, pp.225-233.
2. 2) NIMS Creep Data Sheet, No.M-11, 2016.
3. 3) Sawada, K., Sekido, K., Murata, M., Kamihira, K., Kimura, K. (2018): Precipitation behavior during aging and creep in 18Cr-9Ni-3Cu-Nb-N steel, Materials Characterization, Vol.141, pp.279-285.
4. 4) Kimura, K., Sawada, K. (2020): Creep deformation property and creep life evaluation of Super304H, ser. Pressure Vessels and Piping Conference, V006T06A079, Vol.6: Materials and Fabrication.
5. 5) Nguyen, T. D., Sawada, K., Kushima, H., Tabuchi, M., Kimura, K. (2014): Change of precipitate free zone during long-term creep in 2.25cr-1mo steel, Materials Science and Engineering: A, Vol.591, pp.130-135.
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