关于人工智能在核能领域应用的若干思考

谭思超; 李桐; 刘永超; 梁彪; 王博; 沈继红

doi:10.13832/j.jnpe.2023.02.0001

关于人工智能在核能领域应用的若干思考

doi: 10.13832/j.jnpe.2023.02.0001

谭思超^{1, 2,},
李桐^{1, 2},
刘永超^{1, 2},
梁彪^{1, 2},
王博^{1, 2},
沈继红³

1.
哈尔滨工程大学黑龙江省核动力装置性能与设备重点实验室，哈尔滨，150001
2.
哈尔滨工程大学核安全与先进核能技术工信部重点实验室，哈尔滨，150001
3.
哈尔滨工程大学数学科学学院，哈尔滨，150001

基金项目: 中央高校基本科研业务费项目(3072022CFJ1506，3072022JC2401）

详细信息

作者简介:
谭思超（1979—），男，教授，博士研究生导师，主要研究方向为反应堆热工水力、核领域人工智能应用，E-mail: tansichao@hrbeu.edu.cn

中图分类号: TL48
计量
- 文章访问数: 2388
- HTML全文浏览量: 73
- PDF下载量: 406
- 被引次数: 0
出版历程
- 收稿日期: 2022-11-25
- 修回日期: 2022-12-21
- 刊出日期: 2023-04-15

Thoughts on the Application of Artificial Intelligence in Nuclear Energy Field

Tan Sichao^{1, 2
,},
Li Tong^{1, 2},
Liu Yongchao^{1, 2},
Liang Biao^{1, 2},
Wang Bo^{1, 2},
Shen Jihong³

1.
Heilongjiang Provincial Key Laboratory of Nuclear Power System & Equipment, Harbin Engineering University, Harbin, 150001, China
2.
Key Laboratory of Nuclear Safety and Advanced Nuclear Energy Technology, Ministry of Industry and Information Technology, Harbin Engineering University, Harbin, 150001, China
3.
School of Mathematical Sciences, Harbin Engineering University, Harbin, 150001, China

摘要

摘要: 在新一轮全球人工智能浪潮下，核能行业逐步开启与人工智能发展融合的进程。本文针对人工智能与核能领域结合应用过程中产生的一些问题进行了探讨与思考。首先，明确人工智能在核能领域的应用优势，人工智能技术通过降低运行成本、提高发电效率、优化控制策略等方法使得核能的经济性与功能性得到了提高和增强。其次，掌握人工智能与核能融合的关键所在，利用大数据、云计算、物联网等关键支撑技术，根据核能领域应用场景和边界实现人工智能技术与核工程问题的最佳适配。然后，确定核能智能化过程中的人员主导问题，由核行业人员来主导实现人工智能与核工程问题的有效适配融合，进而推动核能智能化发展。最后，实现人们对核能智能化的认可和接受，分别从数据、算法、标准化、安全化和社会公众接受度等角度讨论如何构建核能智能化可信安全体系，让核行业人员与社会公众接受核能智能化。通过对核能智能化进程中若干问题的阐述，以期引起核行业人员以及社会公众的共同思考，促进人工智能与核能科学技术的跨领域深度交叉融合，进而实现人工智能对核能行业的深入赋能。
- 核能 /
- 人工智能 /
- 经济性 /
- 功能性 /
- 最佳适配 /
- 人员主导 /
- 可信安全
Abstract: Under the new wave of global artificial intelligence, the nuclear energy industry has gradually started the process of integrating with the development of artificial intelligence. This paper discusses some problems arising from the combined application of artificial intelligence and nuclear energy. First of all, it clarifies the application advantages of artificial intelligence in the field of nuclear energy. Artificial intelligence technology can enhance the economical efficiency and functionality of nuclear energy by reducing the operating costs, improving the power generation efficiency and optimizing the control strategies. Secondly, it holds the key to the integration of artificial intelligence and nuclear energy, that is, applying key supporting techniques such as big data, cloud computing, and the Internet of Things, and realizing the best fitting of artificial intelligence technology to nuclear engineering problems according to the application scenarios and boundaries in the nuclear energy field. Then, it determines the personnel-led issues in the process of nuclear energy intelligentialization, where the nuclear industry personnel will lead the realization of the effective fitting and integration of artificial intelligence and nuclear engineering problems, thereby promoting the development of nuclear energy intelligence. Finally, it realizes people's recognition and acceptance of nuclear energy intelligence and discusses how to build an intelligent and trusted security system for nuclear energy from the perspectives of data, algorithms, standardization, security, and public acceptance so that nuclear industry personnel and the public accept nuclear energy intelligence. Through the elaboration of several issues in the process of nuclear energy intelligentialization, it is expected to arouse the common thinking of nuclear industry personnel and the public, promote the cross-disciplinary deep integration of artificial intelligence and nuclear energy science and technology and then realize the in-depth empowerment of artificial intelligence to the nuclear energy industry.
- Nuclear energy /
- Artificial intelligence /
- Economical efficiency /
- Functionality /
- Best fitting /
- Personnel-led /
- Trusted security

HTML全文

图 1 “核”“智”融合的关键技术

Figure 1. Key Techniques for Integratoin of "Nuclear" and "Intelligence"

下载: 全尺寸图片幻灯片

图 2 “核”“智”融合体系

Figure 2. "Nuclear" and "Intelligence" Integration System

下载: 全尺寸图片幻灯片

图 3 核能行业人工智能标准体系结构

Figure 3. Standard Architecture of Nuclear Industry Artificial Intelligence

下载: 全尺寸图片幻灯片

参考文献(13)

[1]	中国信息通信研究院. 人工智能白皮书: No. 202205[R]. 北京: 中国信息通信研究院, 2022.
[2]	中国电子技术标准化研究院. 人工智能标准化白皮书（2021版）[Z]. 北京: 中国电子技术标准化研究院, 2021
[3]	BERNARD J A. Applications of artificial intelligence to reactor and plant control[J]. Nuclear Engineering and Design, 1989, 113(2): 219-227. doi: 10.1016/0029-5493(89)90073-3
[4]	SUMAN S. Artificial intelligence in nuclear industry: chimera or solution?[J]. Journal of Cleaner Production, 2021, 278: 124022. doi: 10.1016/j.jclepro.2020.124022
[5]	刘林海. 能源数字化融合发展的经济性分析[J]. 商讯,2022(12): 151-154.
[6]	刘小年. 我国在运核能企业提高经济性探讨[J]. 中国能源,2019, 41(3): 40-44. doi: 10.3969/j.issn.1003-2355.2019.03.008
[7]	高景斌,彭子桥,王刚,等. 核电数字化仪控远程智能运维系统的应用分析[J]. 仪器仪表用户,2019, 26(8): 51-53,58. doi: 10.3969/j.issn.1671-1041.2019.08.015
[8]	吴国东,李幸群,张力. 海洋核动力平台智能化能效管理研究[J]. 船电技术,2019, 39(4): 18-20. doi: 10.13632/j.meee.2019.04.005
[9]	白轶,秦利华,王思诗. 基于大数据和关系型数据相融合的反应堆远程运维数据管理系统开发[J]. 核动力工程,2020, 41(2): 203-206. doi: 10.13832/j.jnpe.2020.02.0203
[10]	浙江大学中国科教战略研究院课题组. 中国人工智能人才培养报告[R]. 杭州: 浙江大学中国科教战略研究院, 2022.
[11]	LI X Y, CHENG K, HUANG T, et al. Equivalence analysis of simulation data and operation data of nuclear power plant based on machine learning[J]. Annals of Nuclear Energy, 2021, 163: 108507. doi: 10.1016/j.anucene.2021.108507
[12]	韩佳琳,曹诗南,章蕾,等. 数字化转型背景下工业数据安全风险与应对分析[J]. 通信世界,2022(14): 30-31. doi: 10.13571/j.cnki.cww.2022.14.008
[13]	汪庆华. 算法透明的多重维度和算法问责[J]. 比较法研究,2020(6): 163-173.