Areeba Qazi; Kanwarpreet Singh
Abstract
The rock mass classification system is utilized to categorize rocks, and has been used in engineering projects and stability investigations. It focuses on the parameters of rock mass and engineering applications, which include tunnels, slopes, foundations, etc. Rock mass classification is valuable in ...
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The rock mass classification system is utilized to categorize rocks, and has been used in engineering projects and stability investigations. It focuses on the parameters of rock mass and engineering applications, which include tunnels, slopes, foundations, etc. Rock mass classification is valuable in the areas where the collection of samples and yielding of observation is difficult. With the advancement in technology, various machine-based model algorithms have been used, i.e., ANN and MLR in rock mass classification from prior few years. In the present work, the rock mass classification has been discussed, i.e., rock load, stand up time, RQD, RMR, Q, GSI, SMR, and RMi along with their applications. Considering all the parameters, it is concluded that for slope stability in a poor rock condition, the applicability of GSI is sufficient when compared with RMR. GSI also provides a highly accurate valuation of geo-mechanical properties, making it a valuable tool for the engineers and geologists. Also, the RMR values obtained from the ANN model provide better results for tunnels when compared with MLR and the conventional method. The ARMR classification of Slate, Shale, Quartz Schist, Gneiss, and Calcschist at 5 different locations of the world were 51-54, 66-70, 57-60, 35, 65-70, respectively. The range for slate and shale was found to be moderately anisotropic, while quartz schist, gneiss, and calcschist were found to be slightly anisotropic and highly anisotropic.
Omid Frough; Seyed Rahman Torabi; Majid Tajik
Abstract
Successful application of a TBM in a project requires investigating both the ground conditions and the machine and backup system design features. Prediction of the machine performance is very important as it has a big effect on the duration of the project and the costs. In this respect, both penetration ...
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Successful application of a TBM in a project requires investigating both the ground conditions and the machine and backup system design features. Prediction of the machine performance is very important as it has a big effect on the duration of the project and the costs. In this respect, both penetration rate and advance rate must be estimated. Utilization factor, which depends on the type of operation, management, maintenance, geological conditions, mucking delays and other downtimes, correlates the advance rate and penetration rate. Adverse rock mass conditions such as mixed face condition, water problem and instability of rock have a great role in TBM downtimes and reduce the machine utilization considerably. Based on detailed engineering geological reports and maps and daily site reports taken from Karaj-Tehran Water Conveyance Tunnel ( Lots 1 and 2), this paper evaluates, main rock mass properties utilized for the estimation of TBM performance and discusses their effect on the machine utilization. . More specifically it uses the developed database also contains daily boring time, different rock mass related downtimes, daily advance and length of bored tunnel in each engineering geological units. It is concluded that the percentage of the rock mass related downtimes can be estimated via RMR within reliable coefficient of determination.
