Abstract

Necessity of highway infrastructure development has been renowned all over the globe. Key success for highway projects mainly depends on the characterization of subgrade soil intended for thousands of kilometers. In practice, any one of the soil test data may not provide exact characterization of subgrade and at least minimum two tests can be used to develop design values of subgrade for a highway pavement. Also, there is a need to have relationship between two to three soil parameters so as to understand evidently about the soil characteristics and their behavior. Two test data such as CPT and DCP are utilized to develop statistical correlations for better site characterization. Ordinary least squares and the simple arithmetic mean methods are obtained for scatter plots of data pairs and different trends are fitted to the data. Correlation agreements between CPT and DCP for various combinations are plotted for 40 data sets. Liquid limit values ranged from 22 to 56 %, while plastic limits are ranging in between 16 and 43 %. Plasticity index values are varying from minimum 1 % to maximum of 29 %, indicating low to medium swelling potential. Based on the American Association of State Highways and Transportation Officials soil classification system, soil along the chosen highway alignment includes A–2–4, A–4, A–2–5, A–2–7, A–1(a), A–1(b), A–7–6 and A–6. Similarly, according to Unified Soil Classification System, the dominant soils along the highway stretched are placed into inorganic silts or organic clays (MH or OH), inorganic clays (CL), inorganic silts or organic silts (ML and OL), and combinations of the two (CL–ML). Deliberation of sleeve friction measurements resulted minor improvement in correlations and these may be considered trivial. According to Roberson’s chart, the distribution of CPT and DCP data obtained along the highway route encompasses four zones. Zone 4 (i.e., silt mixtures: clayey silt to silty clay), zone 5 (sand mixtures: silty sand to sandy silt), zone 6 (sands: clean sand to silty sand), and zone 8 (very stiff sand to clayey sand), with some scattered data points are located in zone 9 (very stiff, fine–grained). The correlations developed in this study indicates that, CPT (qc + fs) and DCP (qc) correlations are very much enhanced compared to other combinations studied in terms of higher coefficient of correlation and least transformation uncertainty. The CPT and DCP data obtained along the highway route is superimposed in Roberson’s chart to characterize the subgrade soil swiftly.

Highlights

  • Necessity of highway infrastructure development has been renowned all over the globe

  • The correlations developed in this study indicates that, cone penetration test (CPT) and dynamic cone penetrometers (DCP) correlations are very much enhanced compared to other combinations studied in terms of higher coefficient of correlation and least transformation uncertainty

  • The CPT and DCP data obtained along the highway route is superimposed in Roberson’s chart to characterize the subgrade soil swiftly

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Summary

Introduction

Necessity of highway infrastructure development has been renowned all over the globe. Any one of the soil test data may not provide exact characterization of subgrade and at least minimum two tests can be used to develop design values of subgrade for a highway pavement. For most of the highway projects, cone penetration test (CPT) and dynamic cone penetrometers (DCP) are extensively used worldwide. These tests provide continuous and uninterrupted stratigraphic data with the improved resolution along the depth of penetration. Visual inspection to promote the soil classification of subgrade is the only drawback in these tests. These tests are expedient, repeatable, and economical [30]

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