Rock Mass Strength Estimation Using Structural Factor Based on Statistical Strength Theory

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Abstract:

Quantitative estimation of scale effect is a complex problem which contained many uncertainties and should be solved using probability calculus and statistical approach. This paper aims to derive the structural factor according statistical strength theory involving discontinuity surface conditions account to estimate the design rock mass strength. A short review of scale effect estimation techniques based on statistical strength theory is given. A new method of structural factor evaluation is proposed. This technique allows accounting discontinuity conditions by changing the variation of tested specimen random sample. A function that describes the decreasing of strength due to poor discontinuity surface quality is introduced to correct the initial and central statistical moments of strength random distribution. The evaluation of the joints condition function based on analysis of the results of uniaxial compressive strength tests and petrographic structure of specimens is shown. Improving the statistical approach of structural factor evaluating increase the accuracy of the rock mass strength assessment and allow avoiding costly modifications of the mining excavation support design. A case of rock mass strength estimation under conditions of coal mine “Komsomolets Donbassa” according to proposed statistical method is studied.

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Solid State Phenomena (Volume 277)

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111-122

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June 2018

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© 2018 Trans Tech Publications Ltd. All Rights Reserved

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[1] Rules of technical operation in coal mines: SOU 10.1-00185790-002-2005, Ukraine.

Google Scholar

[2] Shashenko, A.N., & Sdvizhkova, E.A. (2008). Analysis of some failure criterions and estimation of scale effect in rocks. 21 World mining congress & expo 2008 – New challenges and visions for mining,, 247-255.

Google Scholar

[3] Sdvyzhkova, O., Gapeiev, S., & Tykhonenko, V. (2015). Stochastic model of rock mass strength in terms of random distance between joints. New Developments in Mining Engineering, 299-303.

DOI: 10.1201/b19901-53

Google Scholar

[4] Shashenko, O.M., Sdvyzhkova, O.O., & Gapeev, S.N. (2008). Deformation models in geomechanics. Dnepropetrovsk: NMU.

Google Scholar

[5] Hoek, E., Carter, T.G., & Diederichs, M.S. (2013). Quantification of the geological strength index chart. Proceedings of the 47th US Rock Mechanics, 1-8.

Google Scholar

[6] Palmström, A. (2000). Recent development in rock support estimates by the RMi. J. Rock Mech. & Tun. Technol., 6(1), 1-19.

Google Scholar

[7] Babets, D.V., Sdvyzhkova, О.О., Larionov, M.H., & Tereshchuk, R.M. (2017). Estimation of rock mass stability based on probability approach and rating systems. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. (2), 58-64.

DOI: 10.33271/nvngu/2021-6/029

Google Scholar

[8] Shashenko, A.N. (1089). Elastoplastic problem for a structurally inhomogeneous rock mass weakened by a circular working. Soviet Applied Mechanics. 6(25), 573-579.

DOI: 10.1007/bf00887061

Google Scholar

[9] Shashenko, O.M., Sdvyzhkova, O.O., & Kovrov, O.S. (2010). Modelling of the rock slope stability at the controlled failure. Rock Mechanics in Civil and Environmental Engineering - Proceedings of the European Rock Mechanics Symposium, 581-584.

DOI: 10.1201/b10550-138

Google Scholar

[10] Sdvyzhkova, О.О., Babets, D.V., & Smirnov, A.V. (2014). Support loading of assembly chamber in terms of Western Donbas plough longwall. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. (5), 26-32.

DOI: 10.33271/nvngu/2020-4/024

Google Scholar

[11] Marinos, P., & Hoek, E. (2000). GSI – A geologically friendly tool for rock mass strength estimation. Proc. GeoEng2000 Conference, 1422-1446.

Google Scholar

[12] Babets, D., Ivanov, O., Szuminski, A., Klisowski, R. (2010). Experimental studies of the Lvovsko-Volynskii rock post-failure behavior. Scientific reports of resource issues, Freiberg: International university of resources. (2), 65-70.

Google Scholar

[13] Sdvyzhkova, O., & Patyńska, R. (2016). Effect of increasing mining rate on longwall coal mining - Western Donbass case study. Studia Geotechnica et Mechanica. (38), 91-98.

DOI: 10.1515/sgem-2016-0010

Google Scholar

[14] Malkowski, P. (2016). Endoscopic Rock Mass Factor (ERMF) – a new rock mass classification. Selected Issues Related To mining and Clean Coal Technology, 39-46.

Google Scholar

[15] Bieniawski, Z.T. (1989). Engineering Rock Mass Classifications. New York: John Wiley & Sons.

Google Scholar

[16] Lowson, A., & Bieniawski, Z. (2013). Critical assessment of RMR-based tunnel design practices: A practical engineer's approach. Society of Mining Engineers, 180-198.

Google Scholar