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Narendra Kumar Samadhiya

Researcher at Indian Institute of Technology Roorkee

Publications -  59
Citations -  764

Narendra Kumar Samadhiya is an academic researcher from Indian Institute of Technology Roorkee. The author has contributed to research in topics: Rock mass classification & Bearing capacity. The author has an hindex of 13, co-authored 51 publications receiving 565 citations. Previous affiliations of Narendra Kumar Samadhiya include Indian Institutes of Technology & University of Mosul.

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Laboratory model studies on unreinforced and geogrid-reinforced sand bed over stone column-improved soft clay

TL;DR: In this article, a series of laboratory model tests on unreinforced and geogrid-reinforced sand bed resting on stone column-improved soft clay have been presented.
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Blast induced rock mass damage around tunnels

TL;DR: In this article, the authors carried out field investigations at five different tunnels located in Himalaya, India to study blast induced damage for wide range of rock mass quality Q values (0.03-17.8).
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A nonlinear criterion for triaxial strength of inherently anisotropic rocks

TL;DR: A nonlinear strength criterion for transversely isotropic rocks is presented in this article, where the critical state concept Barton (Int J Rock Mech Mining Sci Geomech Abstr 13(9):255-279, 1976) has been used to define the curvature of the criterion.
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Rock mass strength parameters mobilised in tunnels

TL;DR: In this article, mobilised strength parameters and modulus of deformation have been deduced from back analysis of the field experience for the purpose of realistic nonlinear stress analysis of arched underground openings in nearly dry rock masses, and modified correlations have been suggested.
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A PSO-ANN hybrid model for predicting factor of safety of slope

TL;DR: The proposed hybrid model is compared with conventional slope stability methods with the help of a case study and a 6-9-1 network was found to be the most optimum network giving the minimum RMSE and Higher R2 value for both training and testing set of the data.