High-Resolution Characterization of Deformation Induced Martensite in Large Areas of Fatigued Austenitic Stainless Steel Using Deep Learning
Abstract
1. Introduction
2. Materials and Methods
3. Results and Discussion
3.1. Visualization of Martensite Phase in SEM Micrographs
3.2. Large-Area Mapping: Automated Image Acquisition in the SEM
3.3. Deep Learning
4. Summary and Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Model | Best Validation Dice Loss | Best Validation IoU Score |
---|---|---|
U-net with ResNet encoder | 0.3639 | 0.5436 |
FPN | 0.8619 | 0.1379 |
Link Net | 0.3958 | 0.5258 |
PSP Net | 0.5853 | 0.3471 |
Section | Analyzed Area (mm2) | α′-Martensite Fraction |
---|---|---|
Longitudinal | 7.97 | 0.931% |
Transversal | 7.97 | 1.298% |
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Mikmeková, Š.; Man, J.; Ambrož, O.; Jozefovič, P.; Čermák, J.; Järvenpää, A.; Jaskari, M.; Materna, J.; Kruml, T. High-Resolution Characterization of Deformation Induced Martensite in Large Areas of Fatigued Austenitic Stainless Steel Using Deep Learning. Metals 2023, 13, 1039. https://doi.org/10.3390/met13061039
Mikmeková Š, Man J, Ambrož O, Jozefovič P, Čermák J, Järvenpää A, Jaskari M, Materna J, Kruml T. High-Resolution Characterization of Deformation Induced Martensite in Large Areas of Fatigued Austenitic Stainless Steel Using Deep Learning. Metals. 2023; 13(6):1039. https://doi.org/10.3390/met13061039
Chicago/Turabian StyleMikmeková, Šárka, Jiří Man, Ondřej Ambrož, Patrik Jozefovič, Jan Čermák, Antti Järvenpää, Matias Jaskari, Jiří Materna, and Tomáš Kruml. 2023. "High-Resolution Characterization of Deformation Induced Martensite in Large Areas of Fatigued Austenitic Stainless Steel Using Deep Learning" Metals 13, no. 6: 1039. https://doi.org/10.3390/met13061039
APA StyleMikmeková, Š., Man, J., Ambrož, O., Jozefovič, P., Čermák, J., Järvenpää, A., Jaskari, M., Materna, J., & Kruml, T. (2023). High-Resolution Characterization of Deformation Induced Martensite in Large Areas of Fatigued Austenitic Stainless Steel Using Deep Learning. Metals, 13(6), 1039. https://doi.org/10.3390/met13061039