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Estimating strength parameters of Lower Gondwana coal measure rocks under dry and saturated conditions

Abstract

Coal mining operations below the water table of surface and underground mines are common. Therefore, a better understanding of rock behaviour in dry and water-saturated conditions is critical in rock engineering projects. In this paper, Lower Gondwana coal measure rock (sandstone and shale) samples have been collected from 10 different mines (eight collieries) in Jharia and Raniganj coalfield of Damodar basin, India. The strength parameters (uniaxial compressive strength (UCS) and Brazilian tensile strength (BTS)) primarily govern the design aspects in mining. These are the most common input parameters for any rock mass classification. Hence, changes in the strength parameters of coal measure rocks under dry and water-saturated conditions would adversely lead to the change in the rock mass classification of the rock. Moreover, the direct determination of strength parameters is expensive, time-consuming, field-inaccessible, laborious, destructive, and requires experienced labour, while an indirect method to estimate the strength parameters from ultrasonic pulse velocity (UPV) is cheap, easy, quick, field-accessible, non-destructive, and straightforward. The UPV, UCS, and BTS in dry conditions, density (ρ), porosity (φ) and rock type information were used as input parameters for predicting the UPV, UCS and BTS in saturated conditions using simple regression (SR), multivariate regression (MR) and artificial neural network (ANN). The change in UPV, UCS and BTS from dry to saturated conditions were observed to be a function of the intrinsic properties (ρ and φ) of coal measure rocks. Finally, a comparative analysis between SR, ANN and MR was performed in a measured vs. predicted 1:1 scatter plot.

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Acknowledgements

The authors acknowledge the resources provided by the Indian Institute of Technology (Indian School of Mines) Dhanbad. They are also thankful to the Eastern Coalfields Ltd. and Bharat Coking Coal Ltd. authorities for their support and guidance during the sample collection process.

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Contributions

Tabish Rahman: Conceptualisation, methodology, writing – original draft preparation, formal analysis, and visualisation. Kripamoy Sarkar: Writing – reviewing and validation.

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Correspondence to Kripamoy Sarkar.

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Communicated by Saibal Gupta

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Rahman, T., Sarkar, K. Estimating strength parameters of Lower Gondwana coal measure rocks under dry and saturated conditions. J Earth Syst Sci 131, 175 (2022). https://doi.org/10.1007/s12040-022-01920-2

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  • DOI: https://doi.org/10.1007/s12040-022-01920-2

Keywords

  • Uniaxial compressive strength
  • Brazilian tensile strength
  • ultrasonic pulse velocity
  • simple regression
  • multivariate regression
  • artificial neural network