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2025 | OriginalPaper | Chapter

Estimation of Heavy Compaction Parameters Using Light Compaction Parameters of Granular Soil

Authors : Jitendra Khatti, Kamaldeep Singh Grover

Published in: Proceedings of the Indian Geotechnical Conference 2022 Volume 10

Publisher: Springer Nature Singapore

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Abstract

The maximum dry density and optimum moisture content are the compaction parameters of soil, determined by modified and standard proctor tests. The modified and standard proctor tests are heavy and light compaction tests. In this research, the factor affecting the compaction parameters and the estimation of heavy compaction parameters from light compaction parameters has been studied. The input parameters G, S, FC, \({D}_{60}\), \({D}_{50}\), \({D}_{30}\), \({D}_{10}\), \({C}_{u}\) and \({C}_{c}\), are used to develop the regression models. Furthermore, Pearson's product-moment correlation coefficient depicts multicollinearity between gravel content and D10 for maximum dry density in both compaction conditions. Also, the coefficient of curvature has no relationship with compaction parameters. The results show that the index parameters (\({D}_{60}\), \({D}_{50}\), \({D}_{30}\), \({D}_{10}\), \({C}_{u}\) and \({C}_{c}\)) estimate the maximum dry density of soil better than other parameters (G, S, FC). However, the estimation of optimum moisture content is less accurate than maximum dry density for heavy and light compaction tests. The regression analysis between heavy and light compaction parameters shows that the regression models estimate the heavy compaction parameters with a correlation coefficient of more than 0.95 using light compaction parameters. Finally, this study concludes that the light compaction parameters of granular soil can estimate the heavy compaction parameters with acceptable results.

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Metadata
Title
Estimation of Heavy Compaction Parameters Using Light Compaction Parameters of Granular Soil
Authors
Jitendra Khatti
Kamaldeep Singh Grover
Copyright Year
2025
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-97-6172-2_14