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Chapter and Conference Paper
Pressurizer Control Optimization with Deep Learning-Based Predictions
With a consideration of alleviating the unstable control responses in traditional pressurizer control, this work adopts the cutting-edge deep learning method to optimize the PID control performance. A Long Sho...
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Chapter and Conference Paper
Research on Intelligent Accident Warning and Simulation for Loss of Coolant Accident in Nuclear Power Plants
Both Convolutional Neural Network (CNN) and Convolutional Long-Short Term Memory (ConvLSTM) are utilized for the accident warning and simulation for Loss of Coolant Accidents (LOCA) in this work. The advantage...
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Chapter and Conference Paper
The Design and Implementation of an LSTM-Based Steam Generator Level Prediction Model
The Long-Short Term Memory (LSTM) model is applied to the Steam Generator (SG) water level prediction in this work. The model is designed and implemented within the SIMULINK environment, where a real-time vali...
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Chapter and Conference Paper
The Application of LSTM Model to the Prediction of Abnormal Condition in Nuclear Power Plants
The Long Short-Term Memory (LSTM) model is investigated in this work, as a proposed prediction method for the abnormal condition in Nuclear Power Plants (NPPs). Its advantage of processing long timeline data i...
