The Aerodynamic Drag Coefficient Effect on the Working Area Ventilation Status
Source abstract
Abstract
In the present-day mining conditions, the ensuring of effective ventilation is the key factor in mine safety and energy efficiency. Calculating the aerodynamic drag of mine workings is the basis for designing and optimizing ventilation systems. Aerodynamic drag is determined by the aerodynamic drag coefficient, whose values in classical theory do not always correspond to actual mining conditions. This study examines the effect of the working cross-sectional area, the air flow velocity (taking into account leaks through the mined space), the support density, and the presence of reinforcement elements on the aerodynamic drag coefficient. Using statistical analysis, multivariate relationships were obtained for calculating the aerodynamic drag coefficient. The practical significance of the results consists of improving the accuracy of ventilation parameter calculations, optimizing the air flow and ventilation modes, and reducing risks in controlling aero-gas conditions in mining areas.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Coal Properties and Utilization · Underground infrastructure and sustainability · Mining and Gasification Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Industrial Safety and Ecology, Abylkas Saginov Karaganda Technical University, 58/1 Nursultan Nazarbayev Avenue, Office 507, Karaganda 100027, Kazakhstan
Faculty of Civil Engineering and Resource Management, AGH University of Krakow, Mickiewicza 30 Av., 30-059 Kraków, Poland
Faculty of Mechanical Engineering and Robotics, AGH University of Krakow, Mickiewicza 30 Av., 30-059 Kraków, Poland
Funding
Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan
References (25)
Show source-provided references
1. Economic Commission for Europe Methane to Markets Partnership (2010). Best Practice Guidance for Effective Methane Drainage and Use in Coal Mines, United Nations. Available online: https://www.unece.org/fileadmin/DAM/energy/se/pdfs/cmm/pub/BestPractGuide_MethDrain_es31.pdf.
2. A statistical analysis of coalmine fires and explosions in China10.1016/j.psep.2018.11.013 ↗
3. Zhang, C., Wang, E., Xu, J., and Peng, S. (2020). Research on Temperature Variation during Coal and Gas Outbursts: Implications for Outburst Prediction in Coal Mines. Sensors, 20.10.3390/s20195526 ↗
4. Improving Coal Mine Safety via Aerodynamic Resistance Control in Longwall Faces: A Quasi-Network Model Approach
5. Suleimenov, N., Sattarova, G., Sarsenbekov, N., Ermukhanova, N., Portnov, V., Zamaliyev, N., Batessova, F., Imanbayeva, S., Zakharov, A., and Abdirashit, A. (2025). Recognition of Stages of Endogenous Fire Outbreak and Development in Coal Mines. Appl. Sci., 15.10.3390/app152011114 ↗
6. Numerical simulation modelling of temperature distribution in the process of coal self-heating in the mined-out spaces
7. Akhmatnurov, D., Zamaliyev, N., Mussin, R., Demin, V., Tolovkhan, B., Ganyukov, N., Skrzypkowski, K., Korzeniowski, W., Stasica, J., and Rak, Z. (2025). Geomechanical Modeling of the Northern Katpar Deposit (Kazakhstan): Assessing the Impact of Rock Mass Disturbance on Stability Safety Factor. Mining, 5.10.3390/mining5040073 ↗
8. Application of mine geophysics method to solving problems of geology
9. Bibliometric analysis and review of mine ventilation literature published between 2010 and 202310.1016/j.heliyon.2024.e26133 ↗
10. Study of the Geomechanical Conditions for Carrying out and Maintaining Surface Mine Workings10.18796/0041-5790-2023-2-31-33 ↗
11. Experimental study of improving a mine ventilation network model using continuously monitored airflow
12. Experimental study on ventilation supply–demand matching to dispense the stope gas disaster risk of coal mines10.1080/19475705.2020.1788172 ↗
13. Research and design of intelligent mine ventilation construction architecture10.1093/ijlct/ctac104 ↗
14. Estimating underground mine ventilation friction factors from low density 3D data acquired by a moving LiDAR10.1016/j.ijmst.2018.03.009 ↗
15. Szmuk, A., Zwolińska-Glądys, K., Kuczera, Z., and Borowski, M. (2025). Methodological Approach for Determining the Aerodynamic Resistance Using 3D Scanning: Application in Mine Ventilation Modeling. Appl. Sci., 15.10.3390/app152111723 ↗
16. Analysis of the impact of local resistance of mine workings on the total mine airflow resistance
17. New classification of mine ventilation resistance
18. Inversion of mine ventilation resistance coefficients enhanced by deep reinforcement learning10.1016/j.psep.2023.12.005 ↗
19. Semin, M., and Levin, L. (2023). Mathematical Modeling of Air Distribution in Mines Considering Different Ventilation Modes. Mathematics, 11.10.3390/math11040989 ↗
20. Calculation model for ventilation friction resistance coefficient by surrounding rock roughness distribution characteristics of mine tunnel10.1038/s41598-022-07115-5 ↗
21. Dziurzyński, W., Krach, A., and Pałka, T. (2017). Airflow Sensitivity Assessment Based on Underground Mine Ventilation Systems Modeling. Energies, 10.10.20944/preprints201707.0050.v1 ↗
22. Determination of Airways Resistance, Volumetric Efficiency and Development of Ventilation Model of Rosh Pinah Zinc Mine Namibia
23. Study on mine ventilation resistance coefficient inversion based on genetic algorithm
24. Ensuring healthy and safe working conditions in breakage face with direct-flow ventilation scheme
25. Quasianalog transformation of Compound Ventilating Network