Algorithm for autonomous power-increase operation using deep reinforcement learning and a rule-based system
The power start-up operation of a nuclear power plant (NPP) increases the reactor power to
the full-power condition for electricity generation. Compared to full-power operation, the …
the full-power condition for electricity generation. Compared to full-power operation, the …
[HTML][HTML] A reliable intelligent diagnostic assistant for nuclear power plants using explainable artificial intelligence of GRU-AE, LightGBM and SHAP
JH Park, HS Jo, SH Lee, SW Oh, MG Na - Nuclear Engineering and …, 2022 - Elsevier
When abnormal operating conditions occur in nuclear power plants, operators must identify
the occurrence cause and implement the necessary mitigation measures. Accordingly, the …
the occurrence cause and implement the necessary mitigation measures. Accordingly, the …
Development of a diagnostic algorithm for abnormal situations using long short-term memory and variational autoencoder
It is recognized that an abnormal situation diagnosis is a challenging task for nuclear power
plant (NPP) operators because of the excessive information and high workload in such …
plant (NPP) operators because of the excessive information and high workload in such …
Condition assessment of nuclear power plant equipment based on machine learning methods: A review
Y Xu, Y Cai, L Song - Nuclear Technology, 2023 - Taylor & Francis
The condition assessment of equipment in nuclear power plants (NPPs) could provide
essential information for operation and maintenance decisions, which would have a …
essential information for operation and maintenance decisions, which would have a …
[HTML][HTML] Comparison of deep reinforcement learning and PID controllers for automatic cold shutdown operation
Many industries apply traditional controllers to automate manual control. In recent years,
artificial intelligence controllers applied with deep-learning techniques have been …
artificial intelligence controllers applied with deep-learning techniques have been …
A multiple-architecture deep learning approach for nuclear power plants accidents classification including anomaly detection and “don't know” response
Nuclear power plants (NPPs) are complex systems that are monitored by a team of highly
trained operators, that in case of an anomalous event on the NPP, such as an accident, must …
trained operators, that in case of an anomalous event on the NPP, such as an accident, must …
ACGAN and BN based method for downhole incident diagnosis during the drilling process with small sample data size
C Wang, J Ma, H Jin, G Wang, C Chen, Y Xia, J Gou - Ocean Engineering, 2022 - Elsevier
During the drilling process, the complicated geological environment makes drilling
operations more difficult as the drilling depth increases, leading to a greater susceptibility to …
operations more difficult as the drilling depth increases, leading to a greater susceptibility to …
[HTML][HTML] Event diagnosis method for a nuclear power plant using meta-learning
Artificial intelligence (AI) techniques are now being considered in the nuclear field, but
application faces with the lack of actual plant data. For this reason, most previous studies on …
application faces with the lack of actual plant data. For this reason, most previous studies on …
Open set compound fault recognition method for nuclear power plant based on label mask weighted prototype learning
S Zhou, M Lin, S Huang, K Xiao - Applied Energy, 2024 - Elsevier
Most of the existing data-driven methods for diagnosing faults in nuclear power plants (NPP)
concentrate on addressing single fault problems under the closed set hypothesis. However …
concentrate on addressing single fault problems under the closed set hypothesis. However …
[PDF][PDF] Construction safety hazard recommendation using graph representation learning
Construction safety possesses a considerable challenge to the construction industry. Factual
risk assessment (RA) is vital for the effective identification of construction hazards and …
risk assessment (RA) is vital for the effective identification of construction hazards and …