Research Progress in the Application of Artificial Intelligence in Reactor Neutron Analysis
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摘要: 在全球科学智能研究与应用的浪潮下，人工智能技术已在反应堆中子学分析的各个环节得到应用，以增强中子学分析的智能化、精细化和高效化。本文对近年来人工智能技术在反应堆中子学分析中的应用研究进展进行综述，以期为推进反应堆数智化发展提供一定的借鉴和参考。为便于读者阅读，首先介绍了人工智能方法的基本分类及其特点；然后分别介绍了中子学分析的核数据评价处理、问题建模、方程数值求解以及输运结果应用四个主要环节的应用研究情况，并分析了其关键技术；最后从模型、数据和应用安全三个方面总结了人工智能技术在中子学分析计算中存在的问题，并给出了相应的研究建议与思考。Abstract: Amid the global surge in scientific intelligence research and applications, artificial intelligence (AI) technology has been applied in various aspects of reactor neutron analysis to enhance its intelligence, precision and efficiency. This paper provides a comprehensive review of the research progress in the application of AI technologies within reactor neutron analysis, aiming to provide insights for advancing the digitalization of reactors and supporting future developments in this field. We first introduce AI methods' basic classifications and characteristics, and then investigate the four key aspects of neutron analysis: nuclear data evaluation, problem modeling, numerical solution of equations, and transport result application. Also critical technologies are reviewed and summarized for each aspect. Finally, the paper discusses challenges in AI-based neutron analysis, particularly in model, data, and application security. In response to these challenges, the paper proposes research recommendations.
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图 1 人工智能方法分类
KAN—Kolmogorov-Arnold 网络；FCN—全连接神经网络；CNN—卷积神经网络；RNN—循环神经网络；GNN—图神经网络；SVM—支持向量机；KNN—K最近邻方法
Figure 1. Classification of Artificial Intelligence Methods
图 4 基于人工智能的输运方程数值求解
Figure 4. Numerical Solution of Transport Equation Based on AI Methods
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