摘要
为了改善移动打磨作业场所粉尘浓度超标的现状,以中车长客打磨车间为研究背景,利用高斯扩散模型,建立非稳态单尘源粉尘扩散模型,采用线性回归方法,研究多尘源耦合扩散规律;根据实验测定的不同高度单点和多点打磨的粉尘浓度,结合气溶胶粒子的运动方程和梯度下降法,求解出粒子扩散系数和多尘源耦合系数.将得到的粉尘扩散模型与对照实验进行验证,结果表明,多点打磨在两个打磨点中间向前一定距离处会出现聚集点,且不同高度聚集点位置不同;多点打磨空间粉尘浓度是单点打磨的2~3倍,且最大值高达45.73 mg/m3,远高于国家卫生标准;多尘源打磨作业粉尘扩散模型平均误差为14.67%,具有一定可靠性,可用于后续对打磨车间粉尘防护技术和空间优化布置的研究.
To improve the current situation of excessive dust concentration in the places of mobile grinding,this thesis,based on the research background of CRCC Changke grinding workshop,establishes an unsteady single-dust diffusion model with the guidance of Gaussian diffusion model.The liner regression method is used to investigate the rules on the diffusion of multi-point dust interactions.It makes a comparative analysis of the data on the dust concentration in single point or multi points,which varies with the height.And combined with the equation for Groundwater Flow and the method of Gradient Decent,it finds out the coefficient of particle diffusion and multipoint dust interactions.The result shows that a gathering point can form between any two grinding points and it may also change with the altitude.The dust concentration of the multi-point grinding is 2 to 3 times of the single point grinding,and the maximum value is up to 45.73 mg/m3,which is higher than the standard of the state health.The average error of the dust diffusion model is verified as 14.67%,and it can be used for subsequent research on the protection technology from the dust and workshop spatial structure.
作者
蒋仲安
张国梁
陈建武
杨斌
陈记合
JIANG Zhongan;ZHANG Guoliang;CHEN Jianwu;YANG Bin;CHEN Jihe(School of Civil and Resource Engineering,University of Science and Technology Beijing,Beijing 100083,China;China Academy of Safety Science and Technology,Beijing 100029,China)
出处
《湖南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2020年第10期124-131,共8页
Journal of Hunan University:Natural Sciences
基金
国家重点研发计划资助项目(2016YFC0801700)
中国安全生产科学研究院基本科研业务费专项资金项目(2019JBKY04,2019JBKY11)。
关键词
打磨场所
扩散模型
多尘源耦合
浓度分布
扩散系数
梯度下降法
grinding workplace
diffusion model
multi-dust source coupling
concentration distribution
diffusion coefficient
gradient descent
