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Peng, Hao;Wang, Yuanbing;Zhang, Xu;Hu, Qingren;Xu, Biao
- Nuclear Engineering and Technology
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- v.54 no.10
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- pp.3595-3603
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- 2022
Nuclear safety-class DCS is used for nuclear reactor protection function, which is one of the key facilities to ensure nuclear power plant safety, the maintenance for DCS to keep system in a high reliability is significant. In this paper, Nuclear safety-class DCS system developed by the Nuclear Power Institute of China is investigated, the model of reliability estimation considering nuclear power plant emergency trip control process is carried out using Markov transfer process. According to the System-Subgroup-Module hierarchical iteration calculation, the evolution curve of failure probability is established, and the preventive maintenance optimization strategy is constructed combining reliability numerical calculation and periodic overhaul interval of nuclear power plant, which could provide a quantitative basis for the maintenance decision of DCS system.
https://doi.org/10.1016/j.net.2022.05.011 인용 PDF KSCI

Wang, Chunbing;Duan, Qizhi;Zhang, Chao;Fan, Yipeng
- Nuclear Engineering and Technology
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- v.53 no.3
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- pp.842-850
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- 2021
Real Time Simulation (RTS) has long been used in the nuclear power industry for operator training and engineering purposes. And, Online Simulation (OLS) is based on RTS and with connection to the plant information system to acquire the measurement data in real time for calibrating the simulation models and following plant operation, for the purposes of analyzing plant events and providing indicative signs of malfunctioning. An OLS system has been developed to support PWR operations for CPR1000 plants. The OLS system provides graphical user interface (GUI) for operators to monitor critical plant operations for preventing faulty operation or analyzing plant events. Functionalities of the OLS system are depicted through the maneuvering of the GUI for various OLS functional modules in the system.
https://doi.org/10.1016/j.net.2020.07.036 인용 PDF KSCI

Xu, Chaoliang;Liu, Xiangbing;Wang, Hongke;Li, Yuanfei;Jia, Wenqing;Qian, Wangjie;Quan, Qiwei;Zhang, Huajian;Xue, Fei
- Nuclear Engineering and Technology
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- v.53 no.8
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- pp.2610-2615
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- 2021
The prediction of irradiation-induced transition temperature shift for RPV steels is an important method for long term operation of nuclear power plant. Based on the irradiation embrittlement data, an irradiation-induced transition temperature shift prediction model is developed with machine learning method XGBoost. Then the residual, standard deviation and predicted value vs. measured value analysis are conducted to analyze the accuracy of this model. At last, Cu content threshold and saturation values analysis, temperature dependence, Ni/Cu dependence and flux effect are given to verify the reliability. Those results show that the prediction model developed with XGBoost has high accuracy for predicting the irradiation embrittlement trend of RPV steel. The prediction results are consistent with the current understanding of RPV embrittlement mechanism.
https://doi.org/10.1016/j.net.2021.02.015 인용 PDF KSCI