Design of Cut-Out Distance for Underground Coal Gallery Using Time-Dependent Constitutive Model | ||
| Journal of Mining and Environment | ||
| مقاله 8، دوره 17، شماره 1، فروردین و اردیبهشت 2026، صفحه 127-141 اصل مقاله (1.99 M) | ||
| نوع مقاله: Short Communication | ||
| شناسه دیجیتال (DOI): 10.22044/jme.2025.16087.3101 | ||
| نویسندگان | ||
| Sonu Saran* 1؛ Prudhvi Raju Gadepaka2؛ Ashok Jaiswal1 | ||
| 1Department of Mining Engineering, IIT (BHU), Varanasi, India | ||
| 2Central Institute of Mining and Fuel Research (CIMFR), Nagpur, India | ||
| چکیده | ||
| The stability of underground coal galleries is critically influenced by time-dependent deformation behavior of surrounding rock masses, particularly in deep mining environments where long-term stress redistribution can lead to delayed failure. In continuous miner-based mining systems, determining an appropriate cut-out distance is essential to ensure productivity and safety, especially for weak rock mass. This study proposes a novel numerical–statistical framework for the optimal design of cut-out distance (COD) in room-and-pillar coal mining using continuous miners. A time-dependent viscoelastic-viscoplastic constitutive model was implemented in FLAC3D to simulate roof deformation across varying geo-mining conditions, including gallery widths (5 & 6 m), depths (100 to 400 m), and COD values (4 to 12 m). The Coal Roof Index (CRI), a composite geotechnical classification parameter, was incorporated to evaluate roof integrity. Results from the numerical simulations were used to develop two empirical models, COD₁ for depths ≤ 200 m and COD₂ for depths > 200 m, via multivariate nonlinear regression. The models demonstrated high predictive accuracy, with R² values of 0.95 and 0.90, respectively. The results reveal a strong correlation between the cut-out distance and various influencing parameters, i.e., width, depth, and CRI classification. Statistical validation through t-tests and ANOVA confirms the significance and reliability of the proposed model. Both proposed models have been validated by two field cases of the Indian coal mine. Critical CRI thresholds were quantified for safe CODs, offering actionable insights for field implementation. The proposed design approach provides a robust framework for improving the safety and sustainability of underground coal mine development, particularly under weak roof conditions. | ||
| کلیدواژهها | ||
| Underground gallery؛ Coal Roof Index (CRI)؛ Cut-out distance؛ Numerical method؛ Multivariate nonlinear regression | ||
| مراجع | ||
|
[1]. Avinash Paul, V. M. S. R. M. A. P. & A. K. S. (2024). Support design in underground coal mines using modified rock mass classification system (RMRdyn) for enhanced safety– an approach from stable and failed roof cases. Environmental Earth Science, pp. 83–103.
[2]. Sazid, M., & Kumar, R. (2010). Designing Cut Out Distance for Continuous Miners Operation using Numerical Modelling and Rock Mechanics Instrumentation. Available: https://www.researchgate.net/publication/257924402
[3]. Mandal, P. K., Das, A. J., Kumar, N., Bhattacharjee, R., Tewari, S., & Kushwaha, A. (2018). Assessment of roof convergence during driving roadways in underground coal mines by continuous miner. International Journal of Rock Mechanics and Mining Sciences, 108, 169–178.
[4]. Cristopher Mark. (n.d.). Application of coal mine roof rating (CMRR) to extended cuts. In National Institute for Occupational Safety and Health. Pittsburgh, National Institute for Occupational Safety and Health.
[5]. Sonu, & Jaiswal, A. (2024). Time-Dependent Stability Assessment of Coal Mine’s Gallery Using New Geotechnical Classification. Journal of The Institution of Engineers (India): Series D.
[6]. Majdi, A. R. M. (2013). Application of artificial neural networks for predicting the height of destressed zone above the mined panel in longwall coal mining. In 47th US Rock Mechanics / Geomechanics Symposium (pp. 23–26). San Francisco, CA, USA.
[7]. Rezaei, Mohammad. (2018). Development of an intelligent model to estimate the height of caving–fracturing zone over the longwall gobs. Neural Computing and Applications, 30(7), 2145–2158.
[8]. Rezaei, Mohammad, Farouq Hossaini, M., Majdi, A., & Najmoddini, I. (2017). Determination of the height of destressed zone above the mined panel: An ANN model, 1–7.
[9]. Rezaei, Mohammad, Habibi, H., & Asadizadeh, M. (2024). Determination of the stress concentration factor adjacent an extracted underground coal panel using the CART and MARS algorithms. Earth Science Informatics.
[10]. Rezaei, M. (2018). Long-term stability analysis of goaf area in longwall mining using minimum potential energy theory. Journal of Mining & Environment, 9(1), 169–182.
[11]. Ray, A. K. (2009). Influence of cutting sequence and time effects on cutters and roof falls in underground coal mine-numerical approach roof falls in underground coal mine-numerical approach. Retrieved from https://researchrepository.wvu.edu/etd
[12]. Gadepaka, Prudhvi Raju, Sonu, & Jaiswal, A. (2025). A Comprehensive Study Using Field Observations and Numerical Simulation Techniques to Design a Mechanised Depillaring Panel. Mining, Metallurgy and Exploration.
[13]. Sonu, P. R. G. A. J. (2024). Estimation of Hoek-Brown Strength Parameters from Time-Dependent Geotechnical Classification as Coal Roof Index (CRI) using Critical Plastic Strain Technique. Pre-Print “Research Square.”
[14]. Gadepaka, Prudhvi Raju, & Jaiswal, A. (2023). A novel approach for the assessment of caving behaviour in a bord and pillar depillaring panel by using continuum modelling. International Journal of Rock Mechanics and Mining Sciences, 170.
[15]. Paul, A., Murthy, V. M. S. R., Prakash, A., Singh, A. K., & Porathur, J. L. (2023). Modelling of Fragile Coal Mine Roof and Estimation of Rock Loads—Some Empirical and Numerical Methods. Mining, Metallurgy and Exploration, 40(5), 1879–1897.
[16]. Murmu, S., & Budi, G. (2022). Analysis of failure associated with longwall face during the main weighting period using a numerical modelling approach. Mining Technology: Transactions of the Institutions of Mining and Metallurgy, 131(4), 210–227.
[17]. Kumar, S., Kumar Sinha, R., & Jawed, M. (2023). Numerical simulation of depillaring panel at higher depth- Jamadoba mine case study. Ain Shams Engineering Journal, 14(4).
[18]. P. R. Sheorey, M. N. D. ~, S. K. B. and B. S. (1986). Pillar strength approaches based on a new failure criterion for coal seams. International Journal of Mining and Geological Engineering, 4, 273–290.
[19]. Murali Mohan, G., Sheorey, P. R., & Kushwaha, A. (2001). Numerical estimation of pillar strength in coal mines. International Journal of Rock Mechanics and Mining Sciences, 38(8), 1185–1192.
[20]. Loui, J. P., Jhanwar, J. C., & Sheorey, P. R. (2007). Assessment of roadway support adequacy in some Indian manganese mines using theoretical in situ stress estimates. International Journal of Rock Mechanics and Mining Sciences, 44(1), 148–155.
[21]. Singh, A. K., Singh, R., Maiti, J., Kumar, R., & Mandal, P. K. (2011). Assessment of mining induced stress development over coal pillars during depillaring. International Journal of Rock Mechanics and Mining Sciences, 48(5), 805–818.
[22]. Das, A. J., Mandal, P. K., Bhattacharjee, R., Tiwari, S., Kushwaha, A., & Roy, L. B. (2017). Evaluation of stability of underground workings for exploitation of an inclined coal seam by the ubiquitous joint model. International Journal of Rock Mechanics and Mining Sciences, 93, 101–114.
[23]. Paul, A., Singh, A. P., John, L. P., Singh, A. K., & Khandelwal, M. (2012). Validation of RMR-based support design using roof bolts by numerical modeling for underground coal mine of Monnet Ispat, Raigarh, India- a case study. Arabian Journal of Geosciences, 5(6), 1435–1448.
[24]. Ghosh, C. N., & Ghose, A. K. (1992). Estimation of critical convergence and rock load in coal mine roadways-an approach based on rock mass rating. Geotechnical and Geological Engineering, 10, 185–202.
[25]. Mohan, G. M., Sheorey, P. R., & Kushwaha, A. (2001). Numerical estimation of pillar strength in coal mines. International Journal of Rock Mechanics & Mining Sciences (Vol. 38).
[26]. Kumar, S., Sinha, R. K., Jawed, M., & Murmu, S. (2023). Assessment of coal pillar strength under the influence of sand stowing in deep coal mines. Geotechnical and Geological Engineering.
[27]. Jaiswal, A., & Shrivastva, B. K. (2009). Numerical simulation of coal pillar strength. International Journal of Rock Mechanics and Mining Sciences, 46(4), 779–788.
[28]. Gadepaka, P.R., Sonu, & Jaiswal, A. (2024). Assessment of the strength deterioration of a coal pillar using a strain-softening time-dependent constitutive model. Mechanics of Time-Dependent Materials.
[29]. Hoek, E., & Brown, E. T. (1980). Empirical strength criterion for rock masses. Journal of the Geotechnical Engineering Division, ASCE, 106(GT9, Proc. Paper, 15715), 1013–1035.
[30]. Zhang, S., Rodriguez-Dono, A., Song, F., & Zhou, Z. (2025). Time-dependent tunnel deformations: Insights from in-situ tests and numerical analyses. Tunnelling and Underground Space Technology, 157.
[31]. Khoshmagham, A., Hosseini, N., Shirinabadi, R., Bangian Tabrizi, A. H., Gholinejad, M., & Kianoush, P. (2024). Unraveling time-dependent roof stability dynamics in Iran’s coal mines through laboratory-based rock displacement testing. Scientific Reports, 14(1).
[32]. Satheesh, P. V., Lohar, G. K., & Kumar, A. (2024). Analyzing Creep Behavior of Storage Caverns in Weak Rocks. Geotechnical and Geological Engineering, 42(6), 4609–4626.
[33]. Liu, J., Feng, Q., Wang, Y., Zhang, D., Wei, J., & Kanungo, D. P. (2018). Experimental study on unconfined compressive strength of organic polymer reinforced sand. International Journal of Polymer Science, 2018.
[34]. Goyal, P., Chan, A. T., & Jaiswal, N. (2006). Statistical models for the prediction of respirable suspended particulate matter in urban cities. Atmospheric Environment, 40(11), 2068–2077. https://doi.org/10.1016/J.ATMOSENV.2005.11.041
[35]. Cardinal, R. N., & A. M. R. F. (2006). ANOVA for the Behavioral Sciences Researcher (1st ed.). Psychology Press. Lawrence Erlbaum Associates, Inc. | ||
|
آمار تعداد مشاهده مقاله: 438 تعداد دریافت فایل اصل مقاله: 169 |
||