Current Progress in the Application of Artificial Intelligence for Nuclear Power Plant Operation

IF 2.9 4区 工程技术 Q2 CHEMISTRY, MULTIDISCIPLINARY Korean Journal of Chemical Engineering Pub Date : 2024-08-05 DOI:10.1007/s11814-024-00246-7
Junyong Bae, Seung Jun Lee
{"title":"Current Progress in the Application of Artificial Intelligence for Nuclear Power Plant Operation","authors":"Junyong Bae,&nbsp;Seung Jun Lee","doi":"10.1007/s11814-024-00246-7","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":684,"journal":{"name":"Korean Journal of Chemical Engineering","volume":"41 10","pages":"2851 - 2870"},"PeriodicalIF":2.9000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Korean Journal of Chemical Engineering","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s11814-024-00246-7","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

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.

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
核电站运行中人工智能应用的最新进展
大型基础设施,如化工厂和核电厂(NPPs),是现代文明的关键,因为它们提供了重要的资源和能源。然而,正如博帕尔和福岛悲剧事故所证明的那样,它们的运行带来了巨大的风险。虽然已经开展了大量研究来提高这些安全关键系统的安全性,但人的因素仍然是一个重大问题。近年来,随着人工智能(AI)在各个领域的广泛应用,人工智能可能成为支持操作人员的一种解决方案,并最终降低核电站和化工厂等安全关键型系统的整体风险。本综述讨论了人工智能在核电站运行中的应用,重点是事件诊断、信号验证、预测和自主控制。文中介绍了各种应用实例,强调了传统方法的局限性以及人工智能克服这些局限性以提高核电站运行安全和效率的潜力。预计这项工作将激励人们进一步研究如何应用人工智能为核电厂以及化工厂等其他安全关键系统的操作人员提供支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Korean Journal of Chemical Engineering
Korean Journal of Chemical Engineering 工程技术-工程:化工
CiteScore
4.60
自引率
11.10%
发文量
310
审稿时长
4.7 months
期刊介绍: The Korean Journal of Chemical Engineering provides a global forum for the dissemination of research in chemical engineering. The Journal publishes significant research results obtained in the Asia-Pacific region, and simultaneously introduces recent technical progress made in other areas of the world to this region. Submitted research papers must be of potential industrial significance and specifically concerned with chemical engineering. The editors will give preference to papers having a clearly stated practical scope and applicability in the areas of chemical engineering, and to those where new theoretical concepts are supported by new experimental details. The Journal also regularly publishes featured reviews on emerging and industrially important subjects of chemical engineering as well as selected papers presented at international conferences on the subjects.
期刊最新文献
Colloidal Semiconductor Cadmium Chalcogenide Nanorods and Nanoplatelets: Growth, Optical Anisotropy and Directed Assembly Special Issue Editorial: Colloidal Quantum Dots Photocatalyst Design Principles for Photocatalytic Hydrogen Production and Benzyl Alcohol Oxidation with CdS Nanosheets Enhanced Energy Storage Capacity of TiO2 Atomic Layered Molybdenum Oxide–Sulfide Negatrode for an Aqueous Ammonium Ion Supercapacitor Evaluation of the Properties and Compositions of Blended Bio-jet Fuels Derived from Fast Pyrolysis Bio-oil made from Wood According to Aging Test
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1