放射性泄漏源参数反演方法综述  

A review of radioactive leakage source parameter inversion methods

作　　者：徐宇涵 方晟[1] 董信文 庄舒涵 XU Yuhan;FANG Sheng;DONG Xinwen;ZHUANG Shuhan(Institute of Nuclear and New Energy Technology,Tsinghua University,Beijing 100084)

机构地区：[1]清华大学核能与新能源技术研究院,北京100084

出　　处：《辐射防护》2024年第S01期1-7,12,共8页Radiation Protection

摘　　要：近些年来,未知来源的放射性泄漏事件引起了广泛关注。针对此类事件,由于核应急响应通常缺少源项输入,难以依赖大气扩散模型进行辐射后果评估,因此基于有限环境监测数据的放射性泄漏源参数反演方法成为研究热点。本文系统介绍了完整的泄漏源参数反演的完整框架,包括监测数据、先验信息、大气扩散模型和反演方法四大要素,并将反演方法分为迭代优化方法和贝叶斯推断方法两大类。本文对这两类方法进行了深入分析和比较,归纳总结了相关研究的最新进展,并在综合评估各类方法性能的基础上提出了未来的研究方向。In recent years,radioactive leakage incidents from unknown sources have garnered widespread attention.In response to such events,nuclear emergency responses often lack source term inputs,making it difficult to make radiation consequence assessment based on atmospheric dispersion models.As a result,methods for reconstructing radioactive leakage source parameters based on limited environmental monitoring data have become a research focus.This paper systematically introduces a comprehensive framework for radioactive leakage source parameter inversion,including four key elements:monitoring data,prior information,atmospheric dispersion models,and inversion methods.The inversion methods are classified into two major categories:iterative optimization methods and Bayesian inference methods.This study conducts an in-depth analysis and comparison of these two approaches,summarizes the latest research developments,and proposes future research direction based on a comprehensive evaluation of the performance of various methods.

关 键 词：放射性泄漏源参数反演 环境监测数据 大气扩散模型 迭代优化 贝叶斯推断 

分 类 号：X830[环境科学与工程—环境工程]