scholarly journals Rock mass rating in Bükk Mts., N Hungary based on petrophysical parameters and parting conditions

2016 ◽  
Vol 10 (3-4) ◽  
pp. 161-168
Author(s):  
Richard William Mcintosh ◽  
Balázs Encs
Keyword(s):  
Rock Mass ◽  
Rock Mass Rating ◽  
Rock Masses ◽  
Petrophysical Parameters ◽  
Bükk Mts

In the region of Bánkút and Ómassa, Bükk Mountains the strength of the rocks of 29 outcrops was studied based on Rock Mass Rating (RMR). Strength of the rock masses showed no correlation with the material of the Formations they exposed, however, correlation between the orientation of valleys and ridges and the location of the most deformed rocks and thus that of the rock masses with poorest qualification could be observed.

scholarly journals Rock Mass Rating and Geological Strength Index of rock masses of Thopal-Malekhu River areas, Central Nepal Lesser Himalaya

2013 ◽  
Vol 16 ◽  
pp. 29-42 ◽  
Author(s):  
Jaya Laxmi Singh ◽  
Naresh Kazi Tamrakar
Keyword(s):  
Rock Mass ◽  
Surface Condition ◽  
Geological Strength Index ◽  
Rock Mass Rating ◽  
Rock Slopes ◽  
Lesser Himalaya ◽  
Rock Masses ◽  
Strength Index ◽  
Rock Mass Structure ◽  
Exposed Rock

The rock slopes of the Thopal-Malekhu River areas, Lesser Himalaya, were characterized applying various systems of rock mass classification, such as Rock mass Rating (RMR) and Geological Strength Index (GSI), because the study area comprises well exposed rock formations of the Nawakot and Kathmandu Complexes, across the Thopal-Malekhu River areas. In RMR system, mainly five parameters viz. Uniaxial Compressive Strength (UCS) of rock, Rock Quality Designation (RQD), spacing of discontinuity, condition of discontinuity, and groundwater condition were considered. The new GSI charts, which were suitable for schistose and much disintegrated rock masses, were used to characterize rock slopes based on quantitative analysis of the rock mass structure and surface condition of discontinuities. RMR ranged from 36 to 82 (poor to very good rock mass) and GSI from 13.5±3 to 58±3 (poor to good rock mass). Slates (of the Benighat Slate) are poor rock masses with low strength, very poor RQD, and close to very close spacing of discontinuity, and dolomites (Dhading Dolomite) are fair rocks with disintegrated, poorly interlocked, and heavily broken rock masses yielding very low RMR and GSI values. Phyllites (Dandagaun Phyllite), schist (Robang Formation) and quartzite (Fagfog Quartzite, Robang Formation and Chisapani Quartzite), dolomite (Malekhu Limestone), and metasandstone (Tistung Formation) are fair rock masses with moderate GSI and RMR values, whereas quartzose schist and gneiss (Kulekhani Formation) are very good rock masses having comparatively higher RMR and GSI. The relationship between GSI and RMR shows positive and good degree of correlation. DOI: http://dx.doi.org/10.3126/bdg.v16i0.8882   Bulletin of the Department of Geology Vol. 16, 2013, pp. 29-42

scholarly journals Geology and rockmass condition of Dhulikhel-Panchkhal area, Kavre District, Central Nepal Lesser Himalaya

2013 ◽  
Vol 15 ◽  
pp. 1-14
Author(s):  
Prem Nath Paudel ◽  
Naresh Kazi Tamrakar
Keyword(s):  
Rock Mass ◽  
Rock Type ◽  
Physical And Mechanical Properties ◽  
Geological Mapping ◽  
Rock Mass Rating ◽  
Lesser Himalaya ◽  
Rock Masses ◽  
Northern Limb ◽  
Rock Types ◽  
Central Nepal

A geological mapping was carried out and the rock mass characteristics of the Lesser Himalayan rocks distributed in the Dhulikhel-Panchkhal area (Kavre Distric) were studied along with their physical and mechanical properties. The lithological units distributed in the study area belong to the Benighat Slate of the Upper Nawakot Group and the Bhimphedi Group as separated by the Chak-Rosi Thrust. The lithological units strike NW-SE and dip southwards forming the eastern closure of part of the northern limb of the Mahabharat synclinorium. The area comprises mainly micaceous quartzite, psammitic schist, metasandstone and metasiltstone. Micaceous quartzite is a rock type of the Kalitar Formation, Chisapani quartzite and the Markhu Formation. The Markhu quartzite is slightly calcareous. Psammitic schist is a rock type of the Kulekhani Formation and the Markhu Formation. Metasandstone and metasiltstone are the rock types of the Tistung Formation. The rock masses consist mainly of three to four major joint sets including the joint parallel to foliation. The discontinuity characteristics indicate that the rocks are blocky in nature, and nearly smooth to rough surface with soft filling aperture. The rock mass is nearly fresh, indurated and stiff. The slopes are influenced by stable and unstable wedges, plane and toppling failures. The rock masses are classified into fair to good rock classes according to rock mass rating system. DOI: http://dx.doi.org/10.3126/bdg.v15i0.7412 Bulletin of the Department of Geology, Vol. 15, 2012, pp. 1–14

scholarly journals Finite-difference based response surface methodology to optimize tailgate support systems in longwall coal mining

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Satar Mahdevari ◽  
Mohammad Hayati
Keyword(s):  
Compressive Strength ◽  
Response Surface Methodology ◽  
Rock Mass ◽  
Finite Difference ◽  
Longwall Mining ◽  
Support Systems ◽  
Rock Mass Rating ◽  
Slake Durability Index ◽  
Proposed Model ◽  
Durability Index

AbstractDesigning a suitable support system is of great importance in longwall mining to ensure the safe and stable working conditions over the entire life of the mine. In high-speed mechanized longwall mining, the most vulnerable zones to failure are roof strata in the vicinity of the tailgate roadway and T-junctions. Severe roof displacements are occurred in the tailgate roadway due to the high-stress concentrations around the exposed roof span. In this respect, Response Surface Methodology (RSM) was utilized to optimize tailgate support systems in the Tabas longwall coal mine, northeast of Iran. The nine geomechanical parameters were obtained through the field and laboratory studies including density, uniaxial compressive strength, angle of internal friction, cohesion, shear strength, tensile strength, Young’s modulus, slake durability index, and rock mass rating. A design of experiment was developed through considering a Central Composite Design (CCD) on the independent variables. The 149 experiments are resulted based on the output of CCD, and were introduced to a software package of finite difference numerical method to calculate the maximum roof displacements (dmax) in each experiment as the response of design. Therefore, the geomechanical variables are merged and consolidated into a modified quadratic equation for prediction of the dmax. The proposed model was executed in four approaches of linear, two-factor interaction, quadratic, and cubic. The best squared correlation coefficient was obtained as 0.96. The prediction capability of the model was examined by testing on some unseen real data that were monitored at the mine. The proposed model appears to give a high goodness of fit with the accuracy of 0.90. These results indicate the accuracy and reliability of the developed model, which may be considered as a reliable tool for optimizing or redesigning the support systems in longwall tailgates. Analysis of variance (ANOVA) was performed to identify the key variables affecting the dmax, and to recognize their pairwise interaction effects. The key parameters influencing the dmax are respectively found to be slake durability index, Young’s modulus, uniaxial compressive strength, and rock mass rating.

Analysis of Unstable Rock-Mass Stability Based on Limit Equilibrium Method and Strength Reduction Method

2016 ◽  
Vol 858 ◽  
pp. 73-80
Author(s):  
Ying Kong ◽  
Hua Peng Shi ◽  
Hong Ming Yu
Keyword(s):  
Rock Mass ◽  
Failure Mode ◽  
Posterior Margin ◽  
Reduction Method ◽  
Limit Equilibrium ◽  
Limit Equilibrium Method ◽  
Strength Reduction ◽  
Strength Reduction Method ◽  
Rock Masses ◽  
Unstable Rock

With the slope unstable rock masses of a stope in Longsi mine, Jiaozuo City, China as the target, we computed and analyzed the stability of unstable rock masses using a limit equilibrium method (LEM) and a discrete element strength reduction method (SRM). Results show that the unstable rock masses are currently stable. Under the external actions of natural weathering, rainfall and earthquake, unstable rock mass 1 was manifested as a shear slip failure mode, and its stability was controlled jointly by bedding-plane and posterior-margin steep inclined joints. In comparison, unstable rock mass 2 was manifested as a tensile-crack toppling failure mode, and its stability was controlled by the perforation of posterior-margin joints. From the results of the 2 methods we find the safety factor determined from SRM is larger, but not significantly, than that from LEM, and SRM can simulate the progressive failure process of unstable rock masses. SRM also provides information about forces and deformation (e.g. stress-strain, and displacement) and more efficiently visualizes the parts at the slope that are susceptible to instability, suggesting SRM can be used as a supplementation of LEM.

scholarly journals Weightage Effect during Back-Calculation of Rock-Mass Quality from the Installed Tunnel Support in Rock-Mass Rating and Tunneling Quality Index System

2019 ◽  
Vol 9 (10) ◽  
pp. 2065 ◽  
Author(s):  
Jonguk Kim ◽  
Hafeezur Rehman ◽  
Wahid Ali ◽  
Abdul Muntaqim Naji ◽  
Hankyu Yoo
Keyword(s):  
Rock Mass ◽  
Quality Index ◽  
Rock Bolt ◽  
Rock Mass Rating ◽  
Rock Mass Quality ◽  
Back Calculation ◽  
The Difference ◽  
Bolt Spacing ◽  
Q System ◽  
Selection Of

In extensively used empirical rock-mass classification systems, the rock-mass rating (RMR) and tunneling quality index (Q) system, rock-mass quality, and tunnel span are used for the selection of rock bolt length and spacing and shotcrete thickness. In both systems, the rock bolt spacing and shotcrete thickness selection are based on the same principle, which is used for the back-calculation of the rock-mass quality. For back-calculation, there is no criterion for the selection of rock-bolt-spacing-based rock-mass quality weightage and shotcrete thickness along with tunnel-span-based rock-mass quality weightage. To determine this weightage effect during the back-calculation, five weightage cases are selected, explained through example, and applied using published data. In the RMR system, the weightage effect is expressed in terms of the difference between the calculated and back-calculated rock-mass quality in the two versions of RMR. In the Q system, the weightage effect is presented in plots of stress reduction factor versus relative block size. The results show that the weightage effect during back-calculation not only depends on the difference in rock-bolt-spacing-based rock-mass quality and shotcrete along with tunnel-span-based rock-mass quality, but also on their corresponding values.

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