Using machine learning to forecast and assess the uncertainty in the response of a typical PWR undergoing a steam generator tube rupture accident

Using machine learning to forecast and assess the uncertainty in the response of a typical PWR undergoing a steam generator tube rupture accident

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM)...

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Bibliographic Details
Main Authors: Tran Canh Hai Nguyen, Aya Diab
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:Nuclear Engineering and Technology
Subjects:
(RNN)
Recurrent neural network
(LSTM)
Long short-term memory
(GRU)
Gated recurrent unit
Online Access:http://www.sciencedirect.com/science/article/pii/S1738573323002516

Internet

http://www.sciencedirect.com/science/article/pii/S1738573323002516

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