An Overview of Data Fusion Methods for the Digital Twin of Nuclear Reactor

被引:0
作者
Song, Meiqi [1 ,2 ]
Chen, Fukun [1 ,2 ]
Liu, Xiaojing [2 ,3 ]
机构
[1] College of Smart Energy, Shanghai Jiao Tong University, Shanghai
[2] Shanghai Digital Nuclear Reactor Technology Integration Innovation Center, Shanghai
[3] School of Nuclear Science and Engineering, Shanghai Jiao Tong University, Shanghai
来源
Hedongli Gongcheng/Nuclear Power Engineering | 2025年 / 46卷 / 02期
关键词
Artificial intelligence; Data assimilation; Data fusion; Digital twin; Nuclear reactor;
D O I
10.13832/j.jnpe.2024.11.0148
中图分类号
学科分类号
摘要
The development of digital twin of nuclear reactor has the potential to enhance the safety and economic efficiency of nuclear power plants by achieving a cyber-physical fusion, while the key challenge of cyber-physical fusion is data fusion. Therefore, this paper focuses on the field of digital twin of nuclear reactor, starting from the definition of data fusion, fusion objects, fusion levels, fusion methods, and the relationship between digital twins and data fusion. Subsequently, the application and research status of data fusion methods in the entire life cycle of digital twin in nuclear reactor are discussed from eight perspectives: the construction of digital twin model of nuclear reactor, the optimization issues in the design and construction of nuclear reactor, the inversion and reconstruction of nuclear reactor operating parameters, the prediction of nuclear reactor operating parameters and remaining service life, the calibration of nuclear reactor operating parameters, the feedback and control of nuclear reactor operation, the fault detection, identification and diagnosis of nuclear reactor, and the data fusion of other aspects of digital twin of nuclear reactor. In conclusion, the challenges existing in current research has been identified from the aspects of data and fusion methods, providing references for addressing key data fusion issues in the future development of digital twin for nuclear reactor. © 2025 Atomic Energy Press. All rights reserved.
引用
收藏
页码:14 / 37
页数:23
相关论文
共 233 条
[1]  
TAO F, QI Q L., New IT driven service-oriented smart manufacturing: framework and characteristics, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49, 1, pp. 81-91, (2019)
[2]  
24, 1, pp. 1-18, (2018)
[3]  
TAO F, ZHANG H, LIU A, Et al., Digital twin in industry: state-of-the-art, IEEE Transactions on Industrial Informatics, 15, 4, pp. 2405-2415, (2019)
[4]  
25, 1, pp. 1-18, (2019)
[5]  
26, 1, pp. 1-17, (2020)
[6]  
HU M Y, ZHANG X Y, PENG C T, Et al., Current status of digital twin architecture and application in nuclear energy field, Annals of Nuclear Energy, 202, (2024)
[7]  
45, 7, pp. 2514-2522, (2021)
[8]  
13, 5, pp. 587-591, (2020)
[9]  
58, 7, pp. 1393-1405, (2024)
[10]  
LIU X, JIANG D, TAO B, Et al., A systematic review of digital twin about physical entities, virtual models, twin data, and applications, Advanced Engineering Informatics, 55, (2023)