Mining of Mineral Deposits

ISSN 2415-3443 (Online)

ISSN 2415-3435 (Print)

Flag Counter

Multifactorial analysis of a gateroad stability at goaf interface during longwall coal mining – A case study

Dmytro Babets1, Olena Sdvyzhkova1, Serhii Hapieiev1, Oleksandr Shashenko1, Vasyl Prykhodchenko1

1Dnipro University of Technology, Dnipro, Ukraine


Min. miner. depos. 2023, 17(2):9-19


https://doi.org/10.33271/mining17.02.009

Full text (PDF)


      ABSTRACT

      Purpose. Creating a generalized algorithm to account for factors (coal seam thickness, enclosed rock mechanical properties, the dimension and bearing capacity of artificial support patterns) causing a gateroad state under the effect of longwall face and goaf.

      Methods. The assessment of the gateroad stability is based on numerical simulation of the rock stress-strain state (SSS). The finite element method is used to find out the changes in the SSS of surrounding rocks at various stages of longwall mining. The elastic-plastic constitutive model and Hoek-Brown failure criterion implemented in codes RS2 and RS3 (Rocscience) are applied to determine rock displacements dependently on the coal seam thickness, enclosed rock strength, width and strength of artificial support (a packwall comprised of hardening mixture “BI-lining”). To specify the mechanical properties of the packwall material a series of experimental tests were conducted. A computational experiment dealing with 81 combinations of affecting factors was carried out to estimate the roof slag and floor heaving in the gateroad behind the longwall face. A group method of data handling (GMDH ) is employed to generalize the relationships between rock displacements and affecting factors.

      Findings. The roof-to-floor closure in the gateroad has been determined at the intersection with the longwall face and goaf dependently on the coal seam thickness, enclosed rock strength, width of the packwall, and strength of hardening material. It is revealed that the support material gains the strength value of 30 MPa on the 3rd day from its beginning to use which is fully corresponding to the requirements of protective element bearing capacity. The possibility of using untreated mine water to liquefy the mixture is proved, that allows simplifying and optimizing the solute mixing and pumping technology.

      Originality. This study contributes to improving the understanding of the factors that influence the stability of underground mining operations and highlights the importance of utilizing numerical simulations in optimizing mining designs. The impact of each factor on the resulting variable (decrease in cross-section of gate road by height) based on the combinatorial algorithm of structural identification of the model is estimated as follows: the packwall width is 48%, the thickness of coal seam is 25%, the strength of enclosing rocks is 23%, and the strength of the packwall material is 4%.

      Practical implications. The findings provide stakeholders with a technique to determine reasonable parameters for support and protective systems, and the predictive model developed can be used to mitigate potential instability issues in longwall mining excavations. The results have implications under similar geological settings and can be valuable for mine design and optimization in other regions.

      Keywords: longwall, gateroad, stability, numerical simulation, GMDH, predictive model


      REFERENCES

  1. Jangara, H., & Ozturk, C. A. (2021). Longwall top coal caving design for thick coal seam in very poor strength surrounding strata. International Journal of Coal Science & Technology, 8(4), 641-658. https://doi.org/10.1007/s40789-020-00397-y
  2. Wang, J., Yang, S., Wei, W., Zhang, J., & Song, Z. (2021). Drawing mechanisms for top coal in longwall top coal caving (LTCC): A review of two decades of literature. International Journal of Coal Science & Technology, 8(6), 1171-1196. https://doi.org/10.1007/s40789-021-00453-1
  3. Petlovanyi, M.V., Lozynskyi, V.H., Saik, P.B., & Sai, K.S. (2018). Modern experience of low-coal seams underground mining in Ukraine. International Journal of Mining Science and Technology, 28(6), 917-923. https://doi.org/10.1016/j.ijmst.2018.05.014
  4. Petlovanyi, M., Lozynskyi, V., Saik, P., & Sai, K. (2019). The influence of geology and ore deposit occurrence conditions on dilution indicators of extracted reserves. Rudarsko-Geološko-Naftni Zbornik, 34(1), 83-91. https://doi.org/10.17794/rgn.2019.1.8
  5. Prusek, S., Rajwa, S., Wrana, A., & Krzemień, A. (2016). Assessment of roof fall risk in longwall coal mines. International Journal of Mining, Reclamation and Environment, 31(8), 558-574. https://doi.org/10.1080/17480930.2016.1200897
  6. Sdvyzhkova, O., Dmytro, B., Moldabayev, S., Rysbekov, K., & Sarybayev, M. (2020). Mathematical modeling a stochastic variation of rock properties at an excavation design. SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings, 20(1.2). https://doi.org/10.5593/sgem2020/1.2/s03.021
  7. Sdvyzhkova, O., & Patyńska, R. (2016). Effect of increasing mining rate on longwall coal mining – Western Donbass case study. Studia Geotechnica et Mechanica, 38(1), 91-98. https://doi.org/10.1515/sgem-2016-0010
  8. Song, G., Wang, Z., & Ding, K. (2020). Evaluation of the face advance rate on ground control in the open face area associated with mining operations in Western China. Journal of Geophysics and Engineering, 17(2), 390-398. https://doi.org/10.1093/jge/gxz124
  9. Li, Y., Zhu, E., Zhang, K., Li, M., Wang, J., & Li, C. (2017). Longwall mining under Gateroads and gobs of abandoned small mine. International Journal of Mining Science and Technology, 27(1), 145-152. https://doi.org/10.1016/j.ijmst.2016.11.004
  10. Shi, X., & Zhang, J. (2021). Characteristics of overburden failure and fracture evolution in shallow buried working face with large mining height. Sustainability, 13(24), 13775. https://doi.org/10.3390/su132413775
  11. Song, Z., Liu, H., Tang, C., & Kong, X. (2021). Development of excavation damaged zones around a rectangular roadway under mining-induced pressure. Tunnelling and Underground Space Technology, (118), 104163. https://doi.org/10.1016/j.tust.2021.104163
  12. Yang, X., Yang, G., Huang, R., Wang, Y., Liu, J., Zhang, J., & Hou, S. (2021). Comprehensive study on surrounding rock failure characteristics of longwall roadway and control techniques. Applied Sciences, 11(21), 9795. https://doi.org/10.3390/app11219795
  13. Kovalevska, I., Barabash, M., & Snihur, V. (2018). Development of a research methodology and analysis of the stress state of a parting under the joint and downward mining of coal seams. Mining of Mineral Deposits, 12(1), 76-84. https://doi.org/10.15407/mining12.01.076
  14. Bondarenko, V., Fomychov, V., & Kovalevs’ka, I. (2012). Features of carrying out experiment using finite-element method at multivariate calculation of “mine massif – combined support” system. Geomechanical Processes during Underground Mining, 17-24. https://doi.org/10.1201/b13157-4
  15. Małkowski, P., & Ostrowski, L. (2019) Convergence monitoring as a basis for numerical analysis of changes of rock-mass quality and Hoek-Brown failure criterion parameters due to longwall excavation. Archives of Mining Sciences, 64(1), 93-118. https://doi.org/10.24425/ams.2019.126274
  16. Wu, R., He, Q., Oh, J., Li, Z., & Zhang, C. (2018). A new gob-side entry layout method for two-entry longwall systems. Energies, 11(8), 2084. https://doi.org/10.3390/en11082084
  17. Wu, R., Zhang, P., Kulatilake, P.H., Luo, H., & He, Q. (2021). Stress and deformation analysis of gob-side pre-backfill driving procedure of longwall mining: A case study. International Journal of Coal Science & Technology, 8(6), 1351-1370. https://doi.org/10.1007/s40789-021-00460-2
  18. Tereshchuk, R.M., Khoziaikina, N.V., & Babets, D.V. (2018). Substantiation of rational roof-bolting parameters. Scientific Bulletin of National Mining University, (1), 19-26. https://doi.org/10.29202/nvngu/2018-1/18
  19. Prusek, S. (2015). Changes in cross-sectional area of gateroads in longwalls with roof caving, ventilated with “U” and “Y” systems. Archives of Mining Sciences, 60(2), 549-564. https://doi.org/10.1515/amsc-2015-0036
  20. Niedbalski, Z., Małkowski, P., & Majcherczyk, T. (2013). Monitoring of stand-and-roof-bolting support – design optimization. Acta Geodynamica et Geomaterialia, 10(2), 215-226. https://doi.org/10.13168/agg.2013.0022
  21. Malkowski, P., Niedbalski, Z., & Majcherczyk, T. (2016). Roadway design efficiency indices for hard coal mines. Acta Geodynamica et Geomaterialia, 13(2), 201-211. https://doi.org/10.13168/agg.2016.0002
  22. Niedbalski, Z., & Majcherczyk, T. (2021). Indicative assessment of design efficiency of mining roadways. Journal of Sustainable Mining, 17(3), 5. https://doi.org/10.46873/2300-3960.1131
  23. Sdvyzhkova, O, Babets, D., Kravchenko, K., & Smirnov, A. (2015). Rock state assessment at initial stage of longwall mining in terms of poor rocks of Western Donbass. New Developments in Mining Engineering 2015: Theoretical and Practical Solutions of Mineral Resources Mining, 65-70. https://doi.org/10.1201/b19901-13
  24. Korzeniowski, W., Skrzypkowski, K., & Zagórski, K. (2017). Reinforcement of underground excavation with expansion shell rock bolt equipped with deformable component. Studia Geotechnica Et Mechanica, 39(1), 39-52. https://doi.org/10.1515/sgem-2017-0004
  25. Shashenko, A.N., Zhuravlev, V.N., Sdvizhkova, Ye.A., & Dubitska, M.S. (2015). Forecast of disjunctives based on mathematical interpretation of acoustic signal phase characteristics. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (2), 61-66.
  26. Babets, D., Sdvyzhkova, O., Shashenko, O., Kravchenko, K., & Cabana, E.C. (2019). Implementation of probabilistic approach to rock mass strength estimation while excavating through fault zones. Mining of Mineral Deposits, 13(4), 72-83. https://doi.org/10.33271/mining13.04.072
  27. Prykhodchenko, V.F., Shashenko, O.M., Sdvyzhkova, O.O., Prykhodchenko, O.V., & Pilyugin, V.I. (2020). Predictability of a small-amplitude disturbance of coal seams in Western Donbas. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (4), 24-29. https://doi.org/10.33271/nvngu/2020-4/024
  28. Aitkazinova, S., Sdvyzhkova, O., Imansakipova, N., Babets, D., & Klymenko, D. (2022). Mathematical modeling the quarry wall stability under conditions of heavily jointed rocks. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (6), 18-24. https://doi.org/10.33271/nvngu/2022-6/018
  29. Moldabayev, S.K., Sdvyzhkova, O.O., Babets, D.V., Kovrov, O.S., & Adil, T.K. (2021). Numerical simulation of the open pit stability based on probabilistic approach. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (6), 29-34. https://doi.org/10.33271/nvngu/2021-6/029
  30. Wang, C., Hu, M., Zhang, N., & Wang, X. (2021). Optimization of gateroad layout under remnant structures in longwall undermining based on slip line field theory. Arabian Journal of Geosciences, 14(17), 1704. https://doi.org/10.1007/s12517-021-08132-w
  31. Wang, X., Zhu, S., Yu, H., & Liu, Y. (2021). Comprehensive analysis control effect of faults on the height of fractured water-conducting zone in longwall mining. Natural Hazards, 108(2), 2143-2165. https://doi.org/10.1007/s11069-021-04772-z
  32. Yang, X., Wang, E., Wang, Y., Gao, Y., & Wang, P. (2018). A study of the large deformation mechanism and control techniques for deep soft rock roadways. Sustainability, 10(4), 1100. https://doi.org/10.3390/su10041100
  33. Babets, D.V., Kovrov, O.S., Moldabayev, S.K., Tereschuk, R.M., & Sosna, D.O. (2020). Impact of water saturation effect on sedimentary rocks strength properties. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (4), 76-81. https://doi.org/10.33271/nvngu/2020-4/076
  34. Jiang, H., Miao, X., Zhang, J., & Liu, S. (2016). Gateside packwall design in solid backfill mining – A case study. International Journal of Mining Science and Technology, 26(2), 261-265. https://doi.org/10.1016/j.ijmst.2015.12.012
  35. Singh, G.S.P. (2015). Conventional approaches for assessment of caving behavior and support requirement with regard to strata control experiences in longwall workings. Journal of Rock Mechanics and Geotechnical Engineering, 7(3), 291-297. https://doi.org/10.1016/j.jrmge.2014.08.002
  36. Kuz’menko, O., Petlyovanyy, M., & Stupnik, M. (2013). The influence of fine particles of binding materials on the strength properties of hardening backfill. Annual Scientific-Technical Collection – Mining of Mineral Deposits 2013, 45-48. https://doi.org/10.1201/b16354-9
  37. Wang, D., Shi, C., Farzadnia, N., Shi, Z., Jia, H., & Ou, Z. (2018). A review on use of limestone powder in cement-based materials: Mechanism, hydration and microstructures. Construction and Building Materials, (181), 659-672. https://doi.org/10.1016/j.conbuildmat.2018.06.075
  38. Amiri, M., & Soleimani, S. (2021). ML-based group method of data handling: An improvement on the conventional GMDH. Complex & Intelligent Systems, (7), 2949-2960. https://doi.org/10.1007/s40747-021-00480-0
  39. Elbaz, K., Shen, S.-L., Zhou, A., Yin, Z.-Y., & Lyu, H.-M. (2021). Prediction of disc cutter life during shield tunneling with AI via the incorporation of a genetic algorithm into a GMDH-type neural network. Engineering, 7(2), 238-251. https://doi.org/10.1016/j.eng.2020.02.016
  40. Chang, J.-R., & Hung, C.-T. (2007). Development of pavement maintenance and rehabilitation decision model by group method of data handling (GMDH). Computing in Civil Engineering. https://doi.org/10.1061/40937(261)7
  41. Madala, H.R., & Ivakhnenko, A.G. (2018). Inductive learning algorithms for complex systems modeling. London, United Kingdom: CRC Press, 384 p. https://doi.org/10.1201/9781351073493
  42. Band, S.S., Al-Shourbaji, I., Karami, H., Karimi, S., Esfandiari, J., & Mosavi, A. (2020). Combination of group method of data handling (GMDH) and computational fluid dynamics (CFD) for prediction of velocity in channel intake. Applied Sciences, 10(21), 7521. https://doi.org/10.3390/app10217521
  43. Farlow, S.J. (1984). Self-organizing methods in modeling: GMDH type algorithms. Boca Raton, United States: CRC Press, 368 p.
  44. Shashenko, O.M., Sdvyzhkova, O.O., & Babets, D.V. (2010). Method of argument group account in geomechanical calculations. 12th International Symposium on Environmental Issues and Waste Management in Energy and Mineral Production, 488-493.
  45. Mahdavi-Meymand, A., & Zounemat-Kermani, M. (2020). A new integrated model of the group method of data handling and the firefly algorithm (GMDH-FA): Application to aeration modelling on spillways. Artificial Intelligence Review, (53), 2549-2569. https://doi.org/10.1007/s10462-019-09741-4
  46. Parsa, M., Carranza, E.J., & Ahmadi, B. (2021). Deep GMDH neural networks for predictive mapping of mineral prospectivity in terrains hosting few but large mineral deposits. Natural Resources Research, 31(1), 37-50. https://doi.org/10.1007/s11053-021-09984-5

    47. Лицензия Creative Commons

Copyright © 2023 Dnipro University of Technology

Underground Mining Department

All Rights Reserved.

Journal homepage Authors