No abstract

To examine the diffusion characteristics of airflow and dust particles, a multi-factor and multi-level physical self-developed testing system is established. In this study, bunker height, chute angle, feeding speed, coal granularity, and belt speed are selected as independent variables, and airflow velocity and dust concentration are the response variables. The two-factor interactive model is established to analyze the primary and secondary relationship between the independent variables and the response variables. The results demonstrate a denser contour distribution of three-dimensional curved surfaces, suggesting an obvious interaction between the factors. The bunker height increases from 0.75 m to 1.15 m, the maximum increment of the induced airflow velocity at the outlet of the guide chute is observed to be 0.35 m/s, meanwhile, and with the increase in the feed speed from 2t/h to 8t/h, the increment of the induced airflow velocity at the outlet of the guide chute is recorded to be 51%. The coal granularity and bunker height depicted the highest influence on induced air velocity and dust concentration, and the feeding speed proved to be the secondary parameter. This two-factor interactive model can accurately forecast the actual values with a deviation of the calculated values limited to 9%. These research results support the existing research and provide a theoretical foundation to guide the dust control at belt conveyor transfer stations.

To effectively improve the dust reduction rate of fine dust and prevent the occurrence of secondary dust, surfactant-charged water mist dust reduction technology is proposed. First, the water mist induction-charged atomization mechanism was perfected by an induction-charged spray experiment and the optimal atomization-charged voltage was determined to be 10 kV. Second, by surface tension and spray experiments on AEO-9-charged solutions, the lower the surface tension and viscosity of the solution, the better the atomization effect; the best atomization solution was 10 kV and 0.02% AEO-9. Finally, according to an electrostatic adsorption experiment, it was identified that there was an electrostatic interaction between coal dust and charged droplets. The contact angle experiment showed that the contact angle of the AEO-9 droplets decreased by 68.44% compared with water after 3 s of contact with coal dust. The wetting effect of bituminous coal was significantly improved by adding AEO-9 to water. A molecular simulation was used to study the molecular interaction mechanism among the H2O, AEO-9, and bituminous coal molecules. The simulation results showed that AEO-9 was more active than water, it easily interacted with bituminous coal, and the hydrophilic group covered the surface of the bituminous coal molecules, which increased the electrostatic interaction between the water molecules and bituminous coal surface molecules. After adding AEO-9 to H2O, the intermolecular interaction energy of the H2O/AEO-9/bituminous coal system was enhanced more than that of the H2O/bituminous coal system. This study provides the basis for the application of surfactant-charged water mist dust reduction technology.

In order to accurately characterize and evaluate dust particle diffusion in the dynamic tunneling process of a boring machine, this study considers the 31,116 main transport chute heaving face of the Lijiahao coal mine as a case study. A dynamic tunneling model is developed considering the real dynamic tunneling state of the header, to carry out an in-depth analysis of the spatial and temporal evolution of wind flow and dust dispersion in the tunnel under dynamic excavation. In addition, the results were compared against the calculations of a static standard excavation model of a conventional header. Employing CFD analysis accompanied by field measurements, it was highlighted that the dynamic tunneling of the header leads to an increase in the pressure difference and the turbulent kinetic energy at the working face. Moreover, an increase in the number of vortices was reported, and a higher concentration of dust spreads more quickly along the return wind side wall to the return flow area. On the other hand, the high concentration of dust under the standard tunneling model was found to accumulate a lot on the return wind side. Simultaneously, as the distance between the pressurized air outlet and the working face increases, the average wind speed in the vortex-type wind flow area at the front of the tunnel decreases. When t = 60 s, the return flow area expands to a space of 8 m~24 m from the head, and the dust accumulated above the header spreads to the back of the header to form a high concentration dust region of more than 500 mg/m³. It was shown that the range of high-concentration dust clouds in the breathing zone decreases compared to the results of the standard tunneling model. Moreover, the dust concentration in the breathing zone of the driver is significantly lower than that reported by the standard tunneling model. Based on the results of the field test, the average error between the simulated and measured data of the dynamic tunneling model was calculated to be around 6.46%, thus demonstrating the model’s capability in describing the real working conditions of the heave tunnel.