Predictive analysis of shaft station radon concentrations in underground uranium mine: A case study

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成果类型：

期刊论文

作者：

Zhao, Guoyan;Hong, Changshou*;Li, Xiangyang;Lin, Chunping;Hu, Penghua

通讯作者：

Hong, Changshou

作者机构：

[Lin, Chunping; Zhao, Guoyan; Hong, Changshou] Cent S Univ, Sch Resources & Safety Engn, Changsha 410083, Peoples R China.

[Li, Xiangyang] Univ South China, Sch Environm Protect & Safety Engn, Hengyang 421001, Peoples R China.

[Hu, Penghua] China Natl Nucl Corp, Beijing Res Inst Chem Engn & Met, Beijing 101149, Peoples R China.

通讯机构：

[Hong, Changshou] C

Cent S Univ, Sch Resources & Safety Engn, Changsha 410083, Peoples R China.

语种：

英文

关键词：

Intelligent systems;Mining;Monte Carlo methods;Queueing theory;Radon;Uranium;Uranium mines;Average waiting-time;Mathematical derivation;Predictive analysis;Predictive modeling;Queuing theory;Radiation safety;Radon concentrations;Shaft station;Mine shafts;radon;air pollutant;radon;uranium;concentration (composition);model validation;Monte Carlo analysis;numerical model;radon;shaft;uranium;Article;concentration (parameters);mathematical analysis;Monte Carlo method;predictive value;radiation safety;simulation;theoretical model;uranium mine;air pollutant;analysis;computer simulation;mining;radiation monitoring;theoretical model;China;Air Pollutants, Radioactive;Computer Simulation;Mining;Models, Theoretical;Monte Carlo Method;Radiation Monitoring;Radon;Uranium

期刊：

Journal of Environmental Radioactivity

ISSN：

0265-931X

年：

2016

卷：

158-159

页码：

129-137

DOI：

10.1016/j.jenvrad.2016.04.007

基金类别：

The authors wish to express sincere thanks to the financial support provided by National Natural Science Foundation of China (Grant No. 51374244 and No. 11475081 ) in conduction of on-site surveys and decision to submit this paper for publication. Authors are also thankful to the anonymous reviewers for their thoughtful and constructive suggestions that would in no doubt result in a much improved revision of this paper.

机构署名：

本校为其他机构

院系归属：

环境与安全工程学院

摘要：

This paper presented a method for predicting shaft station radon concentrations in a uranium mine of China through theoretical analysis, mathematical derivation and Monte-Carlo simulation. Based upon the queuing model for tramcars, the average waiting time of tramcars and average number of waiting tramcars were determined, which were further used in developing the predictive model for calculating shaft station radon concentrations. The results exhibit that the extent of variation of shaft station radon concentration in the case study mine is no...

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Predictive analysis of shaft station radon concentrations in underground uranium mine: A case study

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