T
Trilok Singh
Researcher at Indian Institute of Technology Bombay
Publications - 396
Citations - 13468
Trilok Singh is an academic researcher from Indian Institute of Technology Bombay. The author has contributed to research in topics: Slope stability & Rock mass classification. The author has an hindex of 54, co-authored 373 publications receiving 10286 citations. Previous affiliations of Trilok Singh include Indian Institute of Technology Delhi & University of Cologne.
Papers
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A neuro-genetic approach for prediction of time dependent deformational characteristic of rock and its sensitivity analysis
TL;DR: In this article, Artificial Neural Network (ANN) and Co-active neuro-fuzzy inference system (CANFIS) backed genetic algorithm technique have been used for the prediction of creep strain and energy of Jog (B), and a comparative study has made between the two models.
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Investigation of rockfall-prone road cut slope near Lengpui Airport, Mizoram, India
TL;DR: In this paper, a 3D stability analysis has been carried out using 3DEC software package to analyze the failure behavior and to decide the rockfall-prone zone (unstable blocks) for slope.
BookDOI
Geologic carbon sequestration
Vikram Vishal,Trilok Singh +1 more
TL;DR: Carbon capture and storage can simply be defined as capturing of waste CO2 from industrial sources at various stages (ex. pre-, postcombustion etc.), transporting it to a storage site (through pipelines etc.) and then depositing it underground so that the CO2 will not re-enter the atmosphere for a geologically significant long time.
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Prediction of maximum safe charge per delay in surface mining
TL;DR: In this paper, the maximum safe charge per delay (Qmax) was calculated by all predictor equations and compared to the proposed equations, and the coefficient of correlation (r) was high for the proposed equation.
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Pore system, microstructure and porosity characterization of Gondwana shale of Eastern India using laboratory experiment and watershed image segmentation algorithm
TL;DR: In this article, the watershed transform was used to segment the pore network and the pores and throats of Gondwana shale of Barren-Measures Formation in a 2D scan-electron microscopy image.