National Institute of Rock Mechanics
National Institute of Rock Mechanics
Naithani A.K.,National Institute of Rock Mechanics
Geotechnical and Geological Engineering | Year: 2017
For better rock mass classification and support design of supporting system, geotechnical investigations were carried out for the proposed 196.80 m long, 50.30 m high and 25.24 m wide underground pump house cavern of a lift irrigation scheme. Geotechnical site investigations, rock support design, excavation and related works and modification of supports design according to the observational construction method are the principal activities for the construction of underground rock cavern. The investigation includes engineering geological mapping, geological logging of drill holes, in situ permeability test and laboratory testing on core samples. Detailed geotechnical investigations carried out supporting the feasibility of underground excavations of cavern within the hillock. Support system recommended is the rock bolt and steel fibre reinforced shotcrete based on empirical approaches and their capacity is determined. Capacity of support system was conducted to evaluate the efficacy of the proposed support system. © 2017 Springer International Publishing Switzerland
Adhikari G.R.,National Institute of Rock Mechanics
Journal of Mines, Metals and Fuels | Year: 2017
The Jezero crater is located in the Nili Fossae region of Mars with a 45-km diameter. Since the Jezero crater has a fan-delta deposit rich clays, it was one of the sites considered for in situ exploration by the Mars Science Laboratory. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter (MRO) is a visible and near infrared spectrometer with enhanced spectral resolution, which provides the ability to map the detailed and large-area the minerals on Mars. In this paper, Using spectral angle mapper (SAM) based on the CRISM near-infrared spectral data, minerals and rocks components at Martian Jezero region are recognized in details. The dominated minerals in Jezero Crater are silicate and carbonate minerals. Silicate minerals include pyroxene, actinolite, and hornblende, while carbonate minerals include ankerite, calcite, siderite and northupite. These minerals suggest that the Jezero Crater has experienced the sedimentation and metamorphism.
Gupta R.N.,National Institute of Rock Mechanics |
Tunnelling in Rock by Drilling and Blasting: Workshop Hosted by FRAGBLAST 10 - The 10th International Symposium on Rock Fragmentation by Blasting | Year: 2013
The paper describes a controlled blasting strategy adopted to excavate open cut (for tunnel portal) and a new tunnel near an existing railway tunnel with a parting/barrier of about 16 m. The area lies in highly populated vicinity, with an operational railway track passing through an old tunnel with brick lining, high tension electric traction and small hutments. The objective of the study was to prevent any fly rock from the surface blasting and damage to the existing tunnel from the blasting for the new tunnel.
Lokhande R.D.,National Institute of Rock Mechanics |
Murthy V.M.S.R.,Indian School of Mines |
Singh K.B.,Indian Central Institute of Mining and Fuel Research
Geotechnical and Geological Engineering | Year: 2013
Subsidence is a gradual or sudden depression of the ground on the surface due to extraction of minerals from underground. It occurs in two forms, namely, trough and pot-hole subsidence. Trough subsidence is a depression covering a large surface area, whereas pot-hole subsidence is a localized phenomenon which occurs due to sudden collapse of overburden into the underground voids. Pot hole is extremely hazardous as it does not give any prior indication before its occurrence. Several pot-holes have occurred in the recent past in the coal mines of South Eastern Coalfield Limited and therefore the study assumes great importance. This paper presents the mechanism, behaviour and critical influencing parameters concerning pot-holes. Field investigations and analysis carried out on pot-holes which occurred in some of the Indian coal mines are presented for highlighting the importance of the same. © 2012 Springer Science+Business Media Dordrecht.
Roy S.,National Institute of Rock Mechanics |
Adhikari G.R.,National Institute of Rock Mechanics |
Renaldy T.A.,National Institute of Rock Mechanics |
Jha A.K.,Central Mine Planning and Design Institute Ltd
Journal of Environmental Science and Technology | Year: 2011
Blasting is one of the essential operations at surface coal mines but it emits large amount of dust into the atmosphere. Prediction of dust concentrations can help in air quality management in mining. In this study, particulate matter generated due to blasting was monitored in different seasons at a large opencast coal mines in India. Blast design parameters, moisture content of the benches and distance of dust samplers from blast locations were recorded. Unlike ambient dust monitoring for industrial activities, blast monitoring was carried out for a period of dust accumulation at various locations in the downwind direction. Blast site varied from one location to other in the mine. Based on the observations of many blasts, monitoring period was determined. Scatterplots and correlation matrices for different variables were plotted. Stepwise regression procedure was carried out for selection of most influencing variables. Incorporating selected variables, multiple regression and neural network models were developed for prediction of particulate matter. The performance of the multiple regression models was assessed. For the development of neural network models, a feed forward with back propagation learning algorithm was used to train the network. The performance of neural network was determined in terms of correlation coefficient (R) and Mean Square Error (MSE). The optimum number of hidden neurons was found out for obtaining the lowest value of MSE and the highest value of R. The results indicated that the network can predict particulate concentrations better than multiple regression models. © 2011 Asian Network for Scientific Information.
Rajendran C.P.,Jawaharlal Nehru Centre for Advanced Scientific Research |
John B.,National Institute of Rock Mechanics |
Rajendran K.,Indian Institute of Science
Journal of Geophysical Research B: Solid Earth | Year: 2015
The Himalaya has experienced three great earthquakes during the last century - 1934 Nepal-Bihar, 1950 Upper Assam, and arguably the 1905 Kangra. Focus here is on the central Himalayan segment between the 1905 and the 1934 ruptures, where previous studies have identified a great earthquake between thirteenth and sixteenth centuries. Historical data suggest damaging earthquakes in A.D. 1255, 1344, 1505, 1803, and 1833, although their sources and magnitudes remain debated. We present new evidence for a great earthquake from a trench across the base of a 13 m high scarp near Ramnagar at the Himalayan Frontal Thrust. The section exposed four south verging fault strands and a backthrust offsetting a broad spectrum of lithounits, including colluvial deposits. Age data suggest that the last great earthquake in the central Himalaya most likely occurred between A.D. 1259 and 1433. While evidence for this rupture is unmistakable, the stratigraphic clues imply an earlier event, which can most tentatively be placed between A.D. 1050 and 1250. The postulated existence of this earlier event, however, requires further validation. If the two-earthquake scenario is realistic, then the successive ruptures may have occurred in close intervals and were sourced on adjacent segments that overlapped at the trench site. Rupture(s) identified in the trench closely correlate with two damaging earthquakes of 1255 and 1344 reported from Nepal. The present study suggests that the frontal thrust in central Himalaya may have remained seismically inactive during the last ~700 years. Considering this long elapsed time, a great earthquake may be due in the region. ©2015. American Geophysical Union. All Rights Reserved.
Bansal A.R.,CSIR - Central Electrochemical Research Institute |
Dimri V.P.,CSIR - Central Electrochemical Research Institute |
Babu K.K.,National Institute of Rock Mechanics
Journal of Seismology | Year: 2013
We analyzed the seismicity of northeastern Himalayan region of latitude (25 to 32° N) and longitude (86-97° E). The US Geological Survey catalogue is used in this study for a period from 1973 to June 2011. The seismicity of the region is modeled using epidemic type aftershock sequence (ETAS) model. The region is divided in three parts: (1) whole region, (2) subregion I, and (3) subregion II. The magnitude of completeness is found to be 4. 6 for all the three regions. The ETAS parameters for all the regions are found same within the standard errors. There is no significant change observed in the seismicity since 1973 based on the ETAS modeling. © 2012 Springer Science+Business Media B.V.
Kumar M.,National Institute of Rock Mechanics |
Samui P.,Vellore Institute of Technology |
Naithani A.K.,Indian National Institute of Engineering
International Journal of Advances in Soft Computing and its Applications | Year: 2013
This article adopts machine learning techniques Relevance Vector Machine (RVM), Gaussian Process Regression (GPR) and Minimax Probability Machine Regression (MPMR)} for determination of Uniaxial Compressive Strength (UCS) and the Modulus of Elasticity (E) of Travertine samples. Point load index (Is(50)), porosity (n), P-wave velocity (Vp), and Schmidt hammer rebound number (Rn) have been taken as inputs of the RVM, GPR and MPMR model. The outputs of RVM, MPMR and GPR are UCS and E. The developed RVM gives equations for prediction UCS and E. The performance of GPR, MPMR and RVM has been compared with the Artificial Neural Network (ANN) models. The simulation results show that the proposed methods give encouraging performance for prediction of UCS and E of Travertine samples.
Kumar M.,National Institute of Rock Mechanics |
Bhatt M.R.,Vellore Institute of Technology |
Samui P.,Vellore Institute of Technology
International Journal of Geomechanics | Year: 2014
The elastic modulus (Ej) of a jointed rock mass is an important parameter for rock mechanics. This study examines the capability of Gaussian process regression (GPR) for determination of the Ej of jointed rock masses. The GPR is a Bayesian nonparametric model. The joint frequency (Jn), joint inclination parameter (n), joint roughness parameter (r), confining pressure (σ3), and elastic modulus (Ei) of intact rock are considered as inputs of the GPR. The output of the GPR is the Ej of jointed rock masses. The developed GPR has been compared with the artificial neural network (ANN) models. Variance of the predicted Ej of jointed rock masses is obtained from the GPR. The results show that the developed GPR is a promising tool for the prediction of the Ej of jointed rock masses. © 2014 American Society of Civil Engineers.
Balasubramaniam V.R.,National Institute of Rock Mechanics |
Jha P.C.,National Institute of Rock Mechanics |
Chandrasekhar E.,Indian Institute of Technology Bombay
Near Surface Geophysics | Year: 2013
Step-Frequency GPR (SFGPR) investigations were carried out at the location of a crude oil storage tank at a petroleum refinery. The storage tank was founded on an elevated platform (tank-pad). Subsidence of a portion of the tank-pad led to cracking of its bottom steel plates and subsequent leakage of crude oil. SFGPR imaging was done within and outside the tank, in the frequency range of 10-260 MHz, to understand the cause of the subsidence. Complex signal analysis was useful in identifying a series of cavities in the subsurface, in the depth range of 2-15 m, close to the location of subsidence of the tank-pad. In order to stabilize the foundation of the tank, the subsurface area infested with cavities was grouted systematically. SFGPR imaging was done again after grouting, in the same area in the same manner to evaluate the efficacy of grouting and check for presence of remnant cavities. Results of the SFGPR investigations, before and after grouting, which aided restoration of the foundation of the oil tank, are discussed. © 2013 European Association of Geoscientists & Engineers.