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作 者:彭亮 PENG Liang(School of Resources and Safety Engineering,Central South University,Changsha,Hunan 410083,China;Changsha Institute of Mining Research Co.,Ltd.,Changsha,Hunan 410012,China;National Engineering Technology Research Center of Metal Mining,Changsha,Hunan 410012,China)
机构地区:[1]中南大学资源与安全工程学院,湖南长沙410083 [2]长沙矿山研究院有限责任公司,湖南长沙410012 [3]国家金属采矿工程技术研究中心,湖南长沙410012
出 处:《矿业研究与开发》2023年第12期65-69,共5页Mining Research and Development
基 金:“十四五”国家重点研发计划项目(2020YFC1909205);湖南省科技创新计划项目(2022GK4057)。
摘 要:为了探究某矿山充填材料的各影响因素对充填料浆输送性能的影响规律,以全尾砂料浆质量浓度、充填管道直径以及充填流量为影响因素,充填料浆输送性能为响应指标开展了L管试验,通过响应面分析法分析确定了各因素及交互作用对充填料输送性能的影响规律,并确定了充填料浆最佳输送参数。结果表明:(1)通过全尾砂粒径分析以及化学成分分析,确定该全尾砂适合作为充填材料用于井下充填;(2)通过响应面分析法得出影响充填料浆输送性能的敏感性因素依次为管道直径、料浆质量浓度、充填流量;(3)试验结果及响应分析表明,某矿山在管径为DN150 mm时,最佳输送参数为充填流量100 m^(3)/h,充填料浆质量浓度72%,此时流动阻力试验值与预测值相近,误差为3.92%,表明回归模型可靠性较高。In order to explore the influence of various influencing factors of filling materials on the conveying characteristics of filling slurry in a mine,the L-pipe test was designed with the mass concentration of full tailings slurry,the filling pipe diameter and the filling flow as the influencing factors,and the conveying characteristics of filling slurry as the response index.The influence of various factors and interactions on the conveying characteristics of filling slurry was determined by response surface methodology,and the optimal conveying parameters of filling slurry were determined.The results show that through the analysis of the particle size and chemical composition of the full tailings,it is determined that the full tailings is suitable as a filling material for underground filling.Through the response surface methodology,the sensitivity factors affecting the conveying characteristics of filling slurry are pipe diameter,slurry concentration and filling flow in order.The test results and response analysis show that when the pipe diameter of a mine is DN150 mm,the optimal conveying parameters are flling flow 100 m^(3)/h and flling slurry mass concentration 72%.At this time,the test value of flow resistance is close to the predicted value,and the error is 3.92%,which indicates that the regression model has high reliability.
分 类 号:TD853.34[矿业工程—金属矿开采]
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