Estimation of elastic constant of rocks using an ANFIS approach

The engineering properties of the rocks have the most vital role in planning of rock excavation and construction for optimum utilization of earth resources with greater safety and least damage to surroundings. The design and construction of structure is influenced by physico-mechanical properties of rock mass. Young's modulus provides insight about the magnitude and characteristic of the rock mass deformation due to change in stress field. The determination of the Young's modulus in laboratory is very time consuming and costly. Therefore, basic rock properties like point load, density and water absorption have been used to predict the Young's modulus. Point load, density and water absorption can be easily determined in field as well as laboratory and are pertinent properties to characterize a rock mass. The artificial neural network (ANN), fuzzy inference system (FIS) and neuro fuzzy are promising techniques which have proven to be very reliable in recent years. In, present study, neuro fuzzy system is applied to predict the rock Young's modulus to overcome the limitation of ANN and fuzzy logic. Total 85 dataset were used for training the network and 10 dataset for testing and validation of network rules. The network performance indices correlation coefficient, mean absolute percentage error (MAPE), root mean square error (RMSE), and variance account for (VAF) are found to be 0.6643, 7.583, 6.799, and 91.95 respectively, which endow with high performance of predictive neuro-fuzzy system to make use for prediction of complex rock parameter.     

Comparative study of the deformation modulus of rock masses—a reply to the comments received from Gokceoglu (2018)

Bulletin of Engineering Geology and the Environment - The deformation modulus of a rock mass (E m) is an important parameter in rock mechanics and engineering and its determination is a difficult...     

Numerical analysis of surface subsidence in asymmetric parallel highway tunnels

Tunnelling related hazards are very common in the Himalayan terrain and a number of such instances have been reported. Several twin tunnels are being planned for transportation purposes which will require good understanding for prediction of tunnel deformation and surface settlement during the engineering life of the structure. The deformational behaviour, design of sequential excavation and support of any jointed rock mass are challenging during underground construction. We have raised several commonly assumed issues while performing stability analysis of underground opening at shallow depth. For this purpose, Kainchi-mod Nerchowck twin tunnels (Himachal Pradesh, India) are taken for in-depth analysis of the stability of two asymmetric tunnels to address the influence of topography, twin tunnel dimension and geometry. The host rock encountered during excavation is composed mainly of moderately to highly jointed grey sandstone, maroon sandstone and siltstones. In contrast to equidimensional tunnels where the maximum subsidence is observed vertically above the centreline of the tunnel, the result from the present study shows shifting of the maximum subsidence away from the tunnel centreline. The maximum subsidence of 0.99 mm is observed at 4.54 m left to the escape tunnel centreline whereas the maximum subsidence of 3.14 mm is observed at 8.89 m right to the main tunnel centreline. This shifting clearly indicates the influence of undulating topography and in-equidimensional noncircular tunnel.