放射性核素大气扩散模型研究综述

为提高放射性核素大气扩散的预测准确性，探讨传统模拟模型和人工智能技术在核安全与环境保护方面 的应用。研究考察高斯、欧拉、拉格朗日等传统模型在不同情境下的有效性，以及人工智能(特别是神经网络)在快 速准确反演核事故源项信息中的角色。结果表明：该研究为核事故应急管理和环境监测提供关键支持，并对提升核 安全和环境保护策略具有较为重要的意义。

Review of Atmospheric Dispersion Models for Radioactive Nuclides

In order to improve the prediction accuracy of atmospheric diffusion of radionuclides, the application of traditional simulation model and artificial intelligence technology in nuclear safety and environmental protection is discussed. This paper examines the effectiveness of traditional models such as Gaussian, Eulerian and Lagrangian models in different scenarios, and the role of artificial intelligence (especially neural networks) in the rapid and accurate retrieval of nuclear accident source term information. The results show that the study provides key support for nuclear accident emergency management and environmental monitoring, and is of great significance for improving nuclear safety and environmental protection strategies.