<p>This study investigates the feasibility of using the Puntke test as a rapid alternative to the Standard Proctor compaction (SP) test for optimizing the proportion of river sand (RS) and M-sand dust waste (MSD) mixtures used in geotechnical stabilization applications. Various RS-MSD mix proportions were evaluated to determine their packing density (PD) through the Puntke test and their compaction characteristics, namely maximum dry density (MDD) and optimum moisture content, through the SP test. Multiple linear regression analysis was employed to establish a relationship between MDD and the independent variables, PD and RS-MSD mix proportion. The developed regression model demonstrated excellent predictive capability with an R<sup>2</sup> value of 0.989, indicating that 98.9% of the variability in MDD was explained in the model. The results showed a strong correlation between PD and MDD, enabling reliable prediction of compaction characteristics from the simpler Puntke test, which is an easy test and can be conducted in the site itself with limited resources. The optimum RS-MSD mix proportion identified through maximum PD corresponded well with the proportion yielding maximum MDD. The findings suggest that the Puntke test can serve as a practical and time-efficient tool for preliminary optimization of RS-MSD mixtures, reducing the need for repeated laboratory compaction test and facilitating quicker decision-making in soil stabilization projects.</p>

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Utilizing multilinear regression analysis for prediction of MDD of river sand: M-sand dust waste mix based on the packing density

  • Muthu Lakshmi Subbiah,
  • Vidhya Lakshmi Sivakumar

摘要

This study investigates the feasibility of using the Puntke test as a rapid alternative to the Standard Proctor compaction (SP) test for optimizing the proportion of river sand (RS) and M-sand dust waste (MSD) mixtures used in geotechnical stabilization applications. Various RS-MSD mix proportions were evaluated to determine their packing density (PD) through the Puntke test and their compaction characteristics, namely maximum dry density (MDD) and optimum moisture content, through the SP test. Multiple linear regression analysis was employed to establish a relationship between MDD and the independent variables, PD and RS-MSD mix proportion. The developed regression model demonstrated excellent predictive capability with an R2 value of 0.989, indicating that 98.9% of the variability in MDD was explained in the model. The results showed a strong correlation between PD and MDD, enabling reliable prediction of compaction characteristics from the simpler Puntke test, which is an easy test and can be conducted in the site itself with limited resources. The optimum RS-MSD mix proportion identified through maximum PD corresponded well with the proportion yielding maximum MDD. The findings suggest that the Puntke test can serve as a practical and time-efficient tool for preliminary optimization of RS-MSD mixtures, reducing the need for repeated laboratory compaction test and facilitating quicker decision-making in soil stabilization projects.