同位素2024，Vol.37Issue(4)：372-378,7.DOI:10.7538/tws.2024.youxian.0372
基于中子/瞬发γ射线联合测量的中子剂量监测模拟研究
Simulation Study on Neutron Dose Monitoring Based on Joint Measurement of Neutron and Prompt Gamma-Rays
摘要
Abstract
The monitoring of neutron ambient dose equivalent rate in a radiation field is of significant importance as it can reflect the operational status of nuclear facilities and provide radiation protection information.Currently,the commonly used monitoring instrument is the A-B type dose equivalent rate meter based on a single detector and a single moderator.However,its response curve differs from the"neutron fluence-ambient dose equivalent conversion coefficient,"leading to measurement errors.In this study,in order to improve the accuracy of neutron dosimeter measurement,a feasibility study was carried out on the joint monitoring of neutron dose rate based on neutrons and instant γ-rays.Lead,borated polyethylene,polymethyl methacrylate,and sodium chloride were used to establish a conversion object.Monte Carlo simulations were performed to calculate the neutron responses of elements B,H,Cl,Pb,C and O.Then,these response curves were combined with the response curves of the LB6411 dosimeter to obtain a new response curve closer to the"neutron fluence-ambient dose equivalent conversion coefficient".The linear fitting coefficients were calculated by using the differential evolution algorithm.The results demonstrate that the modified response curve is closely to the hø response curve.The relative discrepancies are within 50％for the energy range of 1×10-8-16 MeV.The study indicates the feasibility of joint measurement of neutron and prompt gamma-ray for monitoring neutron ambient dose equivalent rate,providing new directions and support for neutron dosimeter calibration and development.关键词
中子周围剂量当量/瞬发γ射线/响应曲线/差分进化算法Key words
neutron ambient dose equivalent/prompt gamma rays/response curve/differential evolution algorithm分类
能源科技引用本文复制引用
程璨,贾文宝,顾加雨,邢立腾,胡尊浩,马靖武,夏勋荣..基于中子/瞬发γ射线联合测量的中子剂量监测模拟研究[J].同位素,2024,37(4):372-378,7.基金项目
国家自然科学基金(12105143) （12105143）
中国博士后科学基金(2023M741453) （2023M741453）
江苏省卓越博士后计划(JB23057) （JB23057）
江苏省市场监督管理局科技计划项目(KJ2024009,KJ2024044,KJ2023015) （KJ2024009,KJ2024044,KJ2023015）
