Digital twin-centered hybrid data-driven multi-stage deep learning framework for enhanced nuclear reactor power prediction

Digital twin-centered hybrid data-driven multi-stage deep learning framework for enhanced nuclear reactor power prediction

The accurate and efficient modeling of nuclear reactor transients is crucial for ensuring safe and optimal reactor operation. Traditional physics-based models, while valuable, can be computationally intensive and may not fully capture the complexities of real-world reactor behavior. This paper intro...

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Bibliographic Details
Main Authors: James Daniell, Kazuma Kobayashi, Ayodeji Alajo, Syed Bahauddin Alam
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Energy and AI
Subjects:
Digital twin
Machine learning
Neural network
Prediction
Nuclear systems
Online Access:http://www.sciencedirect.com/science/article/pii/S2666546824001162
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