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Lee, Seung Jun
Nuclear Safety Assessment and Plant HMI Evolution Lab.
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Current Progress in the Application of Artificial Intelligence for Nuclear Power Plant Operation

Author(s)
Bae, JunyongLee, Seung Jun
Issued Date
2024-08
DOI
10.1007/s11814-024-00246-7
URI
https://scholarworks.unist.ac.kr/handle/201301/83477
Citation
KOREAN JOURNAL OF CHEMICAL ENGINEERING
Abstract
Large-scale infrastructures, such as chemical plants and nuclear power plants (NPPs), are pivotal for modern civilization as they provide vital resources and energy. However, their operation introduces significant risks, as demonstrated by the tragic accidents at Bhopal and Fukushima. While extensive research has been conducted to improve the safety of these safety–critical systems, the human factor remains as a significant concern. In recent years, as artificial intelligence (AI) is being widely adopted in various fields, AI may be a solution for supporting operators and, ultimately, for reducing the overall risk of safety–critical systems such nuclear and chemical plants. This review discusses the application of AI in NPP operations, with a focus on event diagnosis, signal validation, prediction, and autonomous control. Various application examples are presented, highlighting the limitations of classical approaches and the potential for AI overcome such limitations to enhance the safety and efficiency of NPP operations. This work is expected to stimulate further investigation into the application of AI to support operators in not only NPPs but also other safety–critical systems, such as chemical plants.
Publisher
KOREAN INSTITUTE CHEMICAL ENGINEERS
ISSN
0256-1115
Keyword (Author)
Human factorNuclear power plantPlant operationArtificial intelligenceDeep learningSafety–critical system
Keyword
FUZZY NEURAL-NETWORKSTRANSIENT IDENTIFICATIONFAULT-DETECTION

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