A Future with Machine Learning: Review of Condition Assessment of Structures and Mechanical Systems in Nuclear Facilities
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- Konstantinos Prantikos & Lefteri H. Tsoukalas & Alexander Heifetz, 2022. "Physics-Informed Neural Network Solution of Point Kinetics Equations for a Nuclear Reactor Digital Twin," Energies, MDPI, vol. 15(20), pages 1-22, October.
- Piotr F. Borowski, 2021. "Digitization, Digital Twins, Blockchain, and Industry 4.0 as Elements of Management Process in Enterprises in the Energy Sector," Energies, MDPI, vol. 14(7), pages 1-20, March.
- Antonello, Federico & Buongiorno, Jacopo & Zio, Enrico, 2022. "A methodology to perform dynamic risk assessment using system theory and modeling and simulation: Application to nuclear batteries," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
- Bodda, Saran Srikanth & Gupta, Abhinav & Dinh, Nam, 2020. "Enhancement of risk informed validation framework for external hazard scenario," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
- Stetco, Adrian & Dinmohammadi, Fateme & Zhao, Xingyu & Robu, Valentin & Flynn, David & Barnes, Mike & Keane, John & Nenadic, Goran, 2019. "Machine learning methods for wind turbine condition monitoring: A review," Renewable Energy, Elsevier, vol. 133(C), pages 620-635.
- Jianhui Wu & Jingen Chen & Chunyan Zou & Xiaoxiao Li, 2022. "Accident Modeling and Analysis of Nuclear Reactors," Energies, MDPI, vol. 15(16), pages 1-3, August.
- Brendan Kochunas & Xun Huan, 2021. "Digital Twin Concepts with Uncertainty for Nuclear Power Applications," Energies, MDPI, vol. 14(14), pages 1-32, July.
- Lorenzo Malerba & Abderrahim Al Mazouzi & Marjorie Bertolus & Marco Cologna & Pål Efsing & Adrian Jianu & Petri Kinnunen & Karl-Fredrik Nilsson & Madalina Rabung & Mariano Tarantino, 2022. "Materials for Sustainable Nuclear Energy: A European Strategic Research and Innovation Agenda for All Reactor Generations," Energies, MDPI, vol. 15(5), pages 1-48, March.
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Cited by:
- Zhiqiang Peng & Jichong Lei & Zining Ni & Tao Yu & Jinsen Xie & Jun Hong & Hong Hu, 2024. "Research on Data-Driven Methods for Solving High-Dimensional Neutron Transport Equations," Energies, MDPI, vol. 17(16), pages 1-11, August.
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Keywords
condition assessment; artificial intelligence; deep learning; damage detection; signal processing; data management; nuclear piping; concrete; advanced reactors; digital twin;All these keywords.
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