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| 1 | Determination of optimal blowing-to-suction flow ratio in mechanized excavation face with wall-mounted swirling ventilation using numerical simulations显示文摘Wall-mounted swirling ventilation is a new type of system in mechanized excavation faces with a dust sup-pression performance that is closely related to the blowing-to-suction flow ratio.Physical and simulation models were developed according to the No.C103 mechanized excavation face in the Nahe Coal Mine of the Baise Mining Bureau,Guangxi Province to optimize the blowing-to-suction flow ratio for wall-mounted swirling ventilation.Both the k-εturbulence model and the discrete phase model were utilized to simulate airflow field structures and dust concentration distribution patterns at various blowing-to-suction flow ratios.The results suggest that higher blowing-to-suction flow ratios increase the airflow field disturbance around the working face and weaken the intensity of the axial air curtain.On the other hand,both the intensity of the radial air curtain and the dust suppression effect are enhanced.At a blowing-to-suction flow ratio of 0.8,the wall-mounted swirling ventilation system achieved the most favorable dust suppression performance.Both the total dust and respirable dust had their lowest concentrations with maximum efficiencies of reducing both types at 90.33%and 87.16%,respectively. | Runze Gao Pengfei Wang Yongjun Li Ronghua Liu | 2021 | International Journal of Coal Science & Technology2021，8，2： | 2 |
| 2 | Exploration on molecular dynamics simulation methods of microscopic wetting process for coal dust显示文摘Wet dust removal is one of the main technical measures in coal dust control,and coal dust wetting is the key factor to determine the effect of wet dust removal.In order to explore the micro-wetting process of coal dust,this paper uses molecular dynamics simulation to study the micro-wetting process of coal dust in different simulation conditions.The molecular dynamics simulation was carried out under different ensemble,thermodynamic states as well as relaxation pretreatment methods,then the H_(2)O molecular layer and coal dust molecular layer in each simulation were quantitatively analyzed by relative concentration.The research results show that a method for establishing molecular model of lignite is proposed and the 2D periodic surface structure is more reasonable.The surface system of coal-H_(2)O molecule is established by NVT aeration method,where the simulation result is close to the actual coal dust wetting process.The simulation effect of medium and large coal dust-H_(2)O molecular system is better than that of small coal dust-H_(2)O molecular system.This study provides a new solution for changing the empirical method of molecular dynamics simulation of coal system wetting and oversimplification of coal system. | Qi Zhang Xinyi Chen Hetang Wang Chaohang Xu | 2021 | International Journal of Coal Science & Technology2021，8，2： | 0 |
| 3 | Experimental study of the dust-removal performance of a wet scrubber显示文摘A variety of dust control methods are often applied in coal mines,among which the application of wet scrubbers has proven to be an efficient technology for the removal of dust in airstreams,rather than diluting or confining the dust.In this paper,a wet scrubber design was developed.Based on a self-designed experimental test platform,the total dust concentration,respirable dust concentration,air volume,and average pressure drops of wet scrubbers with 12,16,20,and 24 blades were measured under different water intake conditions.The results show that the different water intake levels have only minimal effects on the air volume of the wet scrubbers.However,increased water intake had improved the dust removal efficiency of the wet scrubbers with the same number of blades.The wet scrubber with 16 blades was found to have the best dust removal efficiency at a water intake level of 1.35 m^(3)/h.Its total dust and respirable dust removal efficiency reached 96.81%and 95.59%,respectively.The air volume was 200.4 m^(3)/min,and the average pressure drop was determined to be 169.4 Pa.In addition,when the wet scrubber with 16 blades was applied in a coal preparation plant in China's Shanxi Province,it was observed that the total dust concentration had fallen below 8.1 mg/m^(3),and the respirable dust concentration had fallen below 5.9 mg/m^(3).Therefore,the results obtained in this research investigation provide important references for the use of wet scrubbers to improve coal production environmental conditions. | Shengyong Hu Yang Gao Guorui Feng Fei Hu Changhe Liu Jihua Li | 2021 | International Journal of Coal Science & Technology2021，8，2： | 0 |
| 4 | 煤尘云对瓦斯爆炸6种中间产物相对辐射强度的影响显示文摘煤矿井下瓦斯煤尘共存爆炸是典型的气固两相化学反应。为了突出了解含煤尘瓦斯爆炸过程中反应中间产物的发展规律,采用瞬态火焰传播实验系统从微观火焰光谱探测角度进行含煤尘瓦斯爆炸现象研究,揭示煤尘云加入后对瓦斯爆炸中间产物光谱特性的影响。体积分数为7%、8%、9%、10%、11%瓦斯分别与130 g/m^(3)煤尘质量浓度的长焰煤、焦煤、无烟煤煤尘云形成混合体系,分析混合体系爆炸过程中关键中间产物的相对辐射强度。实验结果表明,130 g/m^(3)煤尘质量浓度的长焰煤/焦煤/无烟煤煤尘云与不同体积分数瓦斯形成的混合体系爆炸,与瓦斯中间产物辐射强度峰值相比,中间产物辐射强度增强,下部光纤峰值增强幅值比上部光纤的峰值增幅幅度大,6种反应中间产物相对辐射强度峰值由大到小排序为C_(2)·>O·>CH_(2)O>CH·>O_(2)>CHO·。煤种变质程度对中间产物相对辐射强度峰值影响幅度从大到小排序为:长焰煤>焦煤>无烟煤煤尘云。煤尘云参与瓦斯爆炸,增强了瓦斯爆炸体系6种中间产物的相对辐射强度,煤尘云对低浓度瓦斯爆炸中间产物相对辐射强度峰值的影响比高浓度瓦斯强烈,不同变质程度煤尘云对CH_(2)O、O·、C_(2)·的累积速率影响作用大于CHO·、O_(2)。可以在后期研发针对瓦斯爆炸的新型抑爆剂时,综合考虑将CH_(2)O、O·、C_(2)·三种反应中间产物作为靶向抑制目标之一,提升新型抑爆剂的抑爆效率。 | 王秋红 潘婷 罗振敏 代爱萍 蒋夏夏 | 2023 | 煤炭学报2023，48，3： | 0 |
| 5 | Integrating image processing and deep learning for effective analysis and classification of dust pollution in mining processes显示文摘A comprehensive evaluation method is proposed to analyze dust pollution generated in the production process of mines.The method employs an optimized image-processing and deep learning framework to characterize the gray and fractal features in dust images.The research reveals both linear and logarithmic correlations between the gray features,fractal dimension,and dust mass,while employing Chauvenel criteria and arithmetic averaging to minimize data discreteness.An integrated hazardous index is developed,including a logarithmic correlation between the index and dust mass,and a four-category dataset is subsequently prepared for the deep learning framework.Based on the range of the hazardous index,the dust images are divided into four categories.Subsequently,a dust risk classifcation system is established using the deep learning model,which exhibits a high degree of performance after the training process.Notably,the model achieves a testing accuracy of 95.3%,indicating its efectiveness in classifying diferent levels of dust pollution,and the precision,recall,and F1-score of the system confrm its reliability in analyzing dust pollution.Overall,the proposed method provides a reliable and efcient way to monitor and analyze dust pollution in mines. | JiangJiang Yin Jiangyang Lei Kaixin Fan Shaofeng Wang | 2023 | International Journal of Coal Science & Technology2023，10，4： | 0 |
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