Research and Prospects of Artificial Intelligence Scientific Computing for Nuclear Industry

Liu Dong; Tian Wenxi; Liu Xiaojing; Hao Chen; Peng Hang; Yu Yang; Xiao Cong

doi:10.13832/j.jnpe.2024.09.0027

Volume 46 Issue 2

Apr. 2025

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Liu Dong, Tian Wenxi, Liu Xiaojing, Hao Chen, Peng Hang, Yu Yang, Xiao Cong. Research and Prospects of Artificial Intelligence Scientific Computing for Nuclear Industry[J]. Nuclear Power Engineering, 2025, 46(2): 1-13. doi: 10.13832/j.jnpe.2024.09.0027

Citation:

Liu Dong, Tian Wenxi, Liu Xiaojing, Hao Chen, Peng Hang, Yu Yang, Xiao Cong. Research and Prospects of Artificial Intelligence Scientific Computing for Nuclear Industry[J]. Nuclear Power Engineering, 2025, 46(2): 1-13. doi: 10.13832/j.jnpe.2024.09.0027

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Research and Prospects of Artificial Intelligence Scientific Computing for Nuclear Industry

doi: 10.13832/j.jnpe.2024.09.0027

Liu Dong^{1, 2, 3
,},
Tian Wenxi⁴,
Liu Xiaojing⁵,
Hao Chen⁶,
Peng Hang^{1, 2, 3},
Yu Yang^{1, 2
,},
Xiao Cong^{1, 2}

1.
State Key Laboratory of Advanced Nuclear Energy Technology, Nuclear Power Institute of China, Chengdu,610213, China
2.
Nuclear Energy Software and Digital Reactor Engineering Research Center of CNNC, Nuclear Power Institute of China, Chengdu, 610213, China
3.
Committee on Science and Technology of China National Nuclear Corporation, Beijing, 100045, China
4.
School of Nuclear Science and Technology, Xi'an Jiaotong University, Xi’an, 710049, China
5.
School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
6.
Nuclear Power Simulation Research Center, Harbin Engineering University, Harbin, 150001, China

Received Date: 2024-09-30
Accepted Date: 2024-12-09
Rev Recd Date: 2024-12-09

Available Online: 2025-01-17

Publish Date: 2025-04-02

Abstract

Abstract

Scientific computation is pivotal throughout the nuclear industry's technical framework, encompassing everything from the creation of nuclear databases to the design, analysis, validation, and operation of nuclear power engineering, as well as the reprocessing of nuclear fuel and the decommissioning of reactors. Historically, the scientific computing paradigm in the industrial field is mainly based on statistical methods for modeling experimental measurement data, as well as numerical computing methods represented by solving differential/integral equations. As artificial intelligence (AI) technology advances, leveraging AI for scientific computation is emerging as a novel paradigm. This paper introduces the basic principles and main features of this emerging technology field, focusing on the characteristics of the nuclear industry. It summarizes the current research work and analyzes the advantages and disadvantages of artificial intelligence scientific computing methods compared to traditional methods. The paper concludes with a prospective look at the future development trends of intelligent computation in the nuclear field, along with potential application scenarios, offering insights to foster the evolution of AI in scientific computation within the nuclear industry.
- Nuclear industry,
- Artificial intelligence,
- Scientific computing,
- Data-driven,
- Intelligent computation

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References(40)

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