Chart to Estimate California Bearing Ratio (CBR) of Plastic Soils, Study notes of Engineering

Download Chart to Estimate California Bearing Ratio (CBR) of Plastic Soils and more Study notes Engineering in PDF only on Docsity! A CHART TO ESTIMATE CBR OF PLASTIC SOILS Ivan Gratchev 1 , Sameera Pitawala 2 , Netra Gurung 3 and Errol Monteiro 3 1 Senior Lecturer, Griffith School of Engineering, Griffith University 2 Formerly master student, Griffith School of Engineering, Griffith University 3 Senior Engineer, Queensland Rail, Brisbane ABSTRACT California Bearing Ratio (CBR) is an important parameter used in design but it is tedious and time-consuming to obtain. This technical note presents and discusses the results of laboratory tests which were performed on plastic soils to identify the soil parameters with a high degree of correlation with CBR. Analysis of the obtained data and the relevant literature resulted in a chart that can be easily used to estimate the CBR of soil based on its plasticity, maximum dry density and optimum moisture content. 1 INTRODUCTION California Bearing Ratio (CBR) is an important parameter that is required for pavement design. It can be readily obtained from standard laboratory tests; however such tests are rather laborious and time-consuming. Not surprisingly, several attempts (Black, 1962; Agarwal and Ghanekar, 1970; NCHRP, 2001; Look, 2009; McGough, 2010; Patel and Desai, 2010; Datta and Chottopadhyay, 2011; Singh et al., 2011; Talukdar, 2014; Yadav et al., 2014; Nguyen and Mohajerani, 2015) have been made to establish empirical correlations between CBR and physical properties of soil. For example, Black (1962) reported relationships between the CBR, plasticity and suction capacity of some British soils. Semen (2006) examined data from a number of CBR tests conducted in USA and assessed different prediction methods that can be applicable to various site conditions. McGough (2010) analyzed the results from more than 400 CBR tests in Australia and South Africa and reported useful correlations between CBR and the Fine Material Factor (a parameter that considers the soil plasticity and its grading). More recently, several studies were performed to establish correlations between CBR and plasticity of some Indian soils (Ramasubbarao and Sankar, 2013; Yadav et al., 2014). Although the aforementioned works presented laboratory data on CBR of several soils, they were generally restricted to some local areas where the tested soil samples were obtained. It is not yet clear whether these reported correlations between the CBR and soil properties can be of a wider use and applicable to different locations or site conditions. This study proposes an engineering chart that can be easily used to estimate the CBR of plastic soils. This paper first reports the laboratory data obtained for plastic soils from the Thagoona area (Queensland, Australia) and discusses the key relationships between CBR and soil properties, which serve as a basis for development of the chart. This chart also includes data reported by different researchers to make it relevant for more general applications. Table 1: Properties of the studied soils No. Liquid Limit, % Plasticity Index, % Linear Shrinkage, % Optimum Moisture Content, % Maximum Dry Density, g/cm 3 Suction (log kPa) California Bearing Ratio, % 1 36.6 18.7 10.1 12.2 1.87 2.8 3.8 2 38.9 19.6 13.8 18.0 1.66 2.9 2.9 3 43.0 23.6 11.7 15.0 1.78 3.1 3.0 4 44.3 23.3 10.2 17.8 1.63 3.5 2.1 5 46.8 23.7 13.0 18.0 1.54 3.8 1.7 6 53.5 31.9 16.9 22.0 1.56 3.3 1.9 7 55.8 28.7 16.1 23.0 1.47 3.8 1.1 8 55.8 31.1 16.1 22.2 1.54 3.1 1.5 9 79.2 46.3 19.5 25.0 1.46 4.2 1.4 2 SOILS USED AND TEST PROCEDURE Soil samples were collected from a depth of 1m to 1.5m in the Thagoona area (Queensland) as part of an investigation conducted by Griffith University and Queensland Rail to determine the geotechnical properties of local reactive soils. Laboratory examination of soil samples included a series of index property and Proctor compaction tests, whose results are summarized in Table 1. A series of CBR tests (AS 1289.6.1.1:2014) were performed on the studied soils, which were compacted to its maximum dry density and optimum moisture content and allowed to soak for 4 days. After each test, soil specimens were retrieved from the mould and a series of suction tests using filter paper (ASTM D 5298-03) were performed to obtain the relevant value of soil suction. Figure 1: Experimental data plotted as CBR against a) maximum dry density, b) optimum moisture content, c) linear shrinkage, and d) soil suction. Figure 2: Experimental data plotted as CBR against the liquid limit (a), and laboratory data without the outlier point (LL=79.2%) (b). y = 19.41e-0.67x R² = 0.61 0 1 2 3 4 2 3 4 5 y = 7.1754e-0.09x R² = 0.52 0 1 2 3 4 8 12 16 20 y = 10.818e-0.088x R² = 0.78 0 1 2 3 4 10 15 20 25 30 (a) (b) (d) (c) Optimum moisture content, % Linear shrinkage, % Soil suction (Log), kPa C al if o rn ia B ea ri n g R at io , % C al if o rn ia B ea ri n g R at io , % C al if o rn ia B ea ri n g R at io , % C al if o rn ia B ea ri n g R at io , % y = 0.0224e2.7865x R² = 0.89 0 1 2 3 4 1.4 1.5 1.6 1.7 1.8 1.9 Maximum dry density, g/cm 3 y = 6.49e -0.023x R² = 0.54 0 1 2 3 4 30 40 50 60 70 80 Liquid Limit, % C al if o rn ia B ea ri n g R a ti o , % y = 21.197e-0.049x R² = 0.82 0 1 2 3 4 30 40 50 60 C al if o rn ia B ea ri n g R at io , % Liquid Limit, % (a) (b)