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Empirical correlations between uniaxial compressive strength and density on the basis of lithology: implications from statistical and machine learning assessments

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Abstract

Uniaxial compressive strength (UCS) is a crucial mechanical parameter in the mining, construction, and petroleum industries. However, determination of the UCS is very tough, expensive, time-consuming, and destructive, requires expert workers for sample preparation, and cannot be determined in the field. As a result, prior researchers have employed different indirect proxy tests to estimate the UCS indirectly. Among these indirect tests, determining density (ρ) is the cheapest, simplest, non-destructive, and does not require sample preparation; also, ρ can easily be determined in the field. Therefore, the correlation between UCS and ρ has been rigorously studied in this paper. A total of 800 data points from 26 previous studies were incorporated and lithology based characteristic simple regression (SR) equations for six rock types (pyroclastic, sandstone, shale, carbonate, plutonic and volcanite) have been proposed. UCS can easily be estimated using the proposed regression equations for the six rock types, which will be helpful in geotechnical and geological engineering projects. The lithological control on the correlation for each rock type has also been validated using principal component analysis (PCA) and descriptive statistics. The obtained database was also used to classify the six rocks on the basis of UCS and ρ as per International Association of Engineering Geologist (IAEG) classification. Soft computing method of artificial neural network (ANN) was also used to estimate the UCS using two ANN models (ANN-1 and ANN-2). Finally, the estimated values of UCS from SR and ANN models were analysed in 1:1 measured vs. estimated plot and statistically assessed.

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Acknowledgements

The authors gratefully acknowledge IIT(ISM) Dhanbad. The authors would also like to thank the anonymous reviewers for their constructive suggestions.

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Authors and Affiliations

  1. Department of Applied Geology, Indian Institute of Technology (Indian School of Mines) Dhanbad, Dhanbad, Jharkhand, 826004, India

    Tabish Rahman & Kripamoy Sarkar

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  1. Tabish Rahman
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  2. Kripamoy Sarkar
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Tabish Rahman. The first draft of the manuscript was written by Tabish Rahman, while Kripamoy Sarkar gave valuable suggestions and corrections. All authors read and approved the final manuscript.

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Correspondence to Kripamoy Sarkar.

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Communicated by: H. Babaie

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Rahman, T., Sarkar, K. Empirical correlations between uniaxial compressive strength and density on the basis of lithology: implications from statistical and machine learning assessments. Earth Sci Inform 16, 1389–1403 (2023). https://doi.org/10.1007/s12145-023-00969-x

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