Geotechnical Characteristics of Two Different Soils and their Mixture and Relationships between Parameters

Transcription

1 Geotechnical Characteristics of Two Different Soils and their Mixture and Relationships between Parameters Arpan Laskar Post Graduate Student Civil Engineering Department, National Institute of Technology Agartala, India Dr. Sujit Kumar Pal Associate Professor, Civil Engineering Department, National Institute of Technology Agartala, India ABSTRACT This paper describes the physical and engineering properties of three different types of soil. One has been collected from NIT Agartala campus and other from River bank of Howrah from different locations of State of Tripura, India. A mixture of both the soils is also investigated. Laboratory tests have been conducted on grain size analysis, specific gravity, Atterberg s limits, standard Proctor compaction, direct shear, and one-dimensional consolidation to find out various parameters. As clay content increases in the soil, the plasticity index (PI) increases and angle of internal friction (ϕ) decreases; with the increase of plasticity index, optimum moisture content (OMC) of the soil increases. As liquid limit (LL) increases, compression index (C c ) increases. With the increase of OMC, C c also increases. Correlations have also been established; PI, OMC and C c found out with the help of other parameters. KEYWORDS: physical properties, engineering properties, soil, plasticity index, compression index, correlations. INTRODUCTION Every civil engineering structure, i.e., building, bridge, highway, tunnel, dam and tower etc. must be founded in or on the surface of the earth. For stable structure proper foundation soil is necessary. For proper evaluation of the suitability of that soil as foundation and as construction materials, information about its properties is frequently necessary. To know the detailed geotechnical properties, physical and engineering properties are very much essential. Large numbers of studies were done by the previous researchers to find out different physical and engineering behaviour of different soils. Nath and Dalal (2004) has assessed physical and engineering properties of different soil and reported that due to increase of liquid limit, plasticity index of soil increases and frictional angle decreases. Compaction characteristics are very much essential for the field considerations. One of the earlier studies on compaction characteristics of soil was proposed by Jumikis (1946). Jumikis (1958) also reported methods to estimate the

2 Vol. 17 [2012], Bund. U 2822 optimum moisture content (OMC) and maximum dry density (MDD) of fine grained soils for compaction. Johnson and Sallberg (1960) suggested a chart to determine the approximate OMC of different soil. Interrelations between physical and engineering properties of soil may improve the understanding of soil susceptibility to compaction and load support capacity. On the basis of the Unified soil classification system, Casagrande devised a plasticity chart and has been proposed a relation between plasticity index and liquid limit where the A-line separates the clays and silts. Nakase et al. (1988) proposed a correlation between compression index and plastic limit. Jumikis (1946) developed correlation between optimum moisture content and liquid limit, and plasticity index. Ring et al. (1962) used liquid limit, plastic limit and plasticity index of soil and they developed two correlations of OMC and MDD based on approximate average particle diameter, content of particle size finer than mm and fineness average. Correlation between compression index and liquid limit for all types of clay soils have been proposed by Terzaghi and Peck (1967). Sridharan and Nagaraj (2000) established a correlation between coefficient of consolidation and shrinkage index. Previous researchers also developed correlations to study compaction characteristics of fly ash (Kaniraj and Havanagi 2001, Bera et al. 2007). MATERIAL AND METHODS In the present investigation, two different types of soil have been studied which collected from two different locations within the State of Tripura, India. One has been collected from NIT Agartala campus (NITA Soil) and other from River bank of Howrah (River Bank Soil). A mixture of both the soils (Mixed Soil) is also investigated to study the variations in properties and to establish correlations of soil parameters. Both the original soil samples were collected in plastic bag from the depth of m. Specific gravity (G), grain size analysis, Atterberg s limits (i.e., liquid limit (LL), plastic limit (PL) and shrinkage limit (SL)), standard Proctor compaction characteristics (i.e., optimum moisture content and maximum dry density), consolidation characteristics (i.e., compression index (C c )), and shear strength characteristics (i.e., cohesion and angle of internal friction) were evaluated in accordance with ASTM standards. RESULTS AND DISCUSSIONS Results Results of physical and engineering properties of two different types of soil and their mixture are studied in this investigation and has been summarized in Table 1. Table 1: The physical and engineering properties of soils Soil properties NITA Soil River Bank Soil Mixed Soil Physical properties: Grain size Analysis Fine Sand (%) = Silt (%) = Clay (%) = Fine Sand (%) = Silt (%) = Clay (%) = Fine Sand (%) = Silt (%) = Clay (%) = Specific gravity (G) Liquid limit, LL (%)

3 Vol. 17 [2012], Bund. U 2823 Plastic limit, PL (%) Shrinkage limit, SL (%) Plasticity index, PI (%) Engineering properties: Optimum moisture content (OMC) % Maximum Dry density (MDD) kn/m 3 Angle of Internal Friction (ϕ) in degree Cohesion (c) kn/m Compression index (C c ) Physical properties From Fig. 1 it is clear that NITA soil and mixed soil has inorganic clay of low to medium plasticity with plasticity index 5.56 and 9.79%. River bank soil has inorganic clay of high plasticity with plasticity index Percentages of fine sand are 54.74, and 40.15%, of silt 24.00, and 30.90%, and clay 21.26, and 28.95% for NITA soil, River bank soil and Mixed soil respectively. Figure 1: The AASHTO Soil Classification chart for Tripura soil Engineering properties For NITA soil, River bank soil and Mixed soil, MDD and OMC are 18.35, and kn/m 3, and 20.00, and 17.10% respectively. Angle of internal friction of NITA soil, River bank soil and Mixed soil are , and respectively; similarly, values of compression indices are 0.110, and respectively. The values of engineering properties are summarized in Table 1.

4 Vol. 17 [2012], Bund. U 2824 Figure 2: Relationship between plasticity index and liquid limit of soil Discussions Based on above results, discussions have been made in this section. Effects of grain size of soil on plasticity index (PI), plasticity index (PI) on angle of internal friction (ϕ) and on optimum moisture content (OMC) have been discussed herein. Effects of liquid limit (LL), and optimum moisture content (OMC) on compression index (C c ) have also been discussed in this section. Effect of Grain Size on Plasticity Index (PI) of Soil From Table 1, it is revealed that plasticity depends on grain size of soil. With the increase of sand content plasticity index of soil get decreases. It may be due to decrease of inter molecular attraction force. Due to decrease of attraction force liquid limit of the soil decreases and accordingly plasticity index decrease. Again in case of increasing clay content inter molecular attraction force increases and liquid limit also increases. Due to increase of liquid limit plasticity index increases (Nath and Dalal 2004). Effect of Plasticity Index (PI) on Angle of Internal Friction (φ ) of Soil From Fig: 7, it is clear that angle of internal friction of soil depends up on plasticity characteristics of soil. Soil strength is the resistance to mass deformation and which depends up on interlocking of particles, frictional resistance between the soil grains, and adhesion or cohesion between soil particles. This friction and cohesion of soil depends up on the percentages of clay or sand present in the soil. Plasticity index is high for fine grained soil (clay). With the increase of clay content in soil, value of φ decreases, with increases of PI value. Similar trend also observed by Nath and Dalal (2004).

5 Vol. 17 [2012], Bund. U 2825 Effect of Plasticity Index (PI) on Optimum Moisture Content (OMC) of Soil A relationship between plasticity index and optimum moisture content (OMC) is shown in Fig: 3. From the figure it is clear that OMC of soil depends on plasticity of soil. Plasticity index of any soil depends up on the water attraction capacity of that soil (Al-Khafaji and Andersland 1992). In case of River bank soil, amount of clay is higher than NITA soil and that is why water attraction capacity of River bank soil is higher. Due to high water attraction capacity of River bank soil (which contains higher amount of clay w.r.t. NITA soil), its plasticity index increases as well as its OMC. Effect of Liquid Limit (LL) on Compression Index (C c ) of Soil From Fig: 4, it is clear that with increase of liquid limit compression index of soil gets increase. The liquid limit can be considered to be a measure of the quantity of water attracted by these particles for a given value of undrained shear strength (Al-Khafaji and Andersland 1992), thus making it possible to correlate this parameter with the compressibility. Compression index of soil depends up on the plasticity characteristics and density of soil. Plasticity is the property by which the material can undergo large amount of deformation; clay exhibits this property to a greater degree with high liquid limit. That is why soil containing high liquid limit, posses high compression index. Similar trend for clays was observed by Terzaghi and Peck (1967), Sridharan and Nagaraj (2000), and Bowles (1996). Effect of Optimum Moisture Content (OMC) on Compression Index (C c ) of Soil A relationship between OMC with C c is shown in Fig: 5 and from this figure it is clear that with the increase of OMC of soil, compression index of soil increases. With the increase of OMC, the amount of void (in the form of pore water) in soil gets increase and dry density gets decrease and under loading condition expulsion of that pore water will occur and that is why compressibility of soil gets increase. Similar trend was observed by Pal and Ghosh (2011) in case of fly ash. Firm relationship between OMC and C c found out as compression index as well as OMC also controlled by composition, structure and moisture attraction capacity of soil (Terzaghi and Peck 1967). REGRESSION ANALYSIS OF TEST RESULTS Regression analysis for the properties of soil is generally useful for the field engineers for preliminary design, estimates and quality control planning. Regression analysis is a statistical tool for the investigation of relationships between the dependent variable and independent variables. In this study linear regression technique is used to analyse data of test results and establish relations between different variables. Attempts have been made for development of relationship between two variables by fitting a linear equation on observed data. Before attempting to fit a linear model on observed data, it should first determine whether or not there is a relationship between the variables of interest. Assessment of regression relationships can be done through estimation of coefficient of determination, R 2 (Draper and Smith 1998). The real test, of how good the resulting regression relationship is, depends on the ability of the relationship to predict the dependent variable for observation on the independent variables that were not used in estimating the regression coefficients (Haan 1994).

6 Vol. 17 [2012], Bund. U 2826 CORRELATIONS OF PARAMETERS Establishment of correlations between the parameters of the laboratory test results of soil is very important. Various correlations have been established between different parameters shown in the following section. Geotechnical properties of two different types of soil and their mixture have been determined in the laboratory in accordance with relevant ASTM standards to develop relationships between the properties. The test results on the properties like, plasticity index (PI), liquid limit (LL), optimum moisture content (OMC), and compression index (C c ) of two different types of soil and their mixture of the present investigation have been reported for statistical analysis to develop correlations. The relationships have also been validated with the data obtained from past studies. Errors in predicted values based on results of earlier studies are tabulated in this paper. The following sections present the empirical relationships to estimate different properties of soils of present investigation. Relationship between Plasticity Index (PI) and Liquid Limit (LL) of Soil In this study, correlation developed between plasticity index (PI) in percentage and liquid limit (LL) in percentage in the form of linear relationship to assess plasticity index (PI) in percentage based on present test results of all the three different types of soil and are presented through the following equation (Eq.1): PI = (LL ) (1) The value of LL lies within the range of 20.0 to 50.0 % for equation (1). Fig: 2 shows the plot of the above curve. The value of the coefficient of determination (R 2 ) is The present relationship has been verified with three numbers of values of LL of earlier researchers. Details of the observed and predicted values along with errors in percentage have been shown in Table. 2. In comparison with predicted results of previous investigators, errors in the values of LL are within the range of to +2.46%. Relationship between Plasticity Index (PI) and Optimum Moisture Content (OMC) of Soil In this section, empirical relationship developed in the form of linear equation by using the test results of all the three soil to assess optimum moisture content (OMC) in percentage, obtained from standard Proctor compaction, as function of the value of plasticity index (PI) in percentage are presented through the following equation (2): OMC = 0.43 (PI + 30) (2) The value of PI lies within the range of 5.0 to 35.0 % for equation (2). In Fig: 3, the plot of the above curve is shown. The value of the R 2 is The present relationship has been verified with four numbers of values of PI of earlier researchers. Details of the observed and predicted values along with errors in percentage have been shown in Table 2. In comparison with predicted results of previous investigators, errors in the values of PI are within the range of to %.

7 Vol. 17 [2012], Bund. U 2827 Table 2: Observed and predicted values based on Equations (1) to (5) Reference Observed values Observed values Predicted values Giasi et al. (2003) PI (%) = LL (%) = Eq. (1): PI (%) = 14.31( 24.7) ( 14.34) (+2.46) Gunaydm (2009) OMC (%) = Al-Kahdaar and Al-Ameri (2010) Kumar and Sudha rani (2001) C c = C c = Giasi et al. (2003) C c = PI (%) = LL (%) = OMC (%) = PI (%) = Eq. (2): OMC (%) = (+23.11) (+8.80) (+3.45) (+15.13) Eq. (3): C c = 0.163( 8.99) (+4.76) (+27.91) Eq. (4): C c = ( 17.34) ( 32.49) ( 26.66) Eq. (5): C c = (+8.23) ( 9.67) (+20.12) Note: Number in parenthesis indicates error in the predicted value in percentage in comparison with the observed value. Relationship between Liquid Limit (LL) and Compression Index (C c ) of Soil Correlation developed between compression index (C c ) and liquid limit (LL) in percentage in the form of linear relationship to assess compression index (C c ) based on present test results of all three different types of soil and are presented through the following equation: C c = (LL 1.39) (3) The value of LL lies within the range of 20.0 to 50.0 % for equation (3). Fig: 4 shows the plot of the above curve. The value of the R 2 is The present relationship has been verified with three numbers of values of LL of earlier researchers. Details of the observed and predicted values along with errors in percentage have been shown in Table 2. In comparison with predicted results of previous investigators, errors in the values of LL are within the range of 8.99 to %. Relationship between Optimum Moisture Content (OMC) and Compression Index (C c ) of Soil Empirical relationship has been developed in the form of linear equation by using the test results of all the three soil to assess compression index (C c ), as function of the value of optimum moisture content (OMC) in percentage, obtained from standard Proctor compaction are presented through the following equation (4): Cc = (OMC 7.034) (4) The value of OMC lies within the range of 15.0 to 32.0 % for equation (4). In Fig: 5, the plot of the above curve is shown. The value of the R 2 is The present relationship has been

8 Vol. 17 [2012], Bund. U 2828 verified with three numbers of values of OMC of earlier researchers. Details of the observed and predicted values along with errors in percentage have been shown in Table. 2. In comparison with predicted results of previous investigators, errors in the values of OMC are within the range of to 17.34%. Relationship between Plasticity Index (PI) and Compression Index (C c ) of Soil In this section, correlation developed between compression index (C c ) and plasticity index (PI) in percentage in the form of linear relationship to assess compression index (C c ) based on present test results of all the three different types of soil and are presented through the following equation (5): Cc = (PI ) (5) The value of PI lies within the range of 5.0 to 35.0 % for equation (5). Fig: 6 shows the plot of the above curve. The value of the R 2 is The present relationship has been verified with three numbers of values of PI of earlier researchers. Details of the observed and predicted values along with errors in percentage have been shown in Table. 2. In comparison with predicted results of previous investigators, errors in the values of PI are within the range of 9.67 to %. Figure 3: Relationship between optimum moisture content and plasticity index of soil

9 Vol. 17 [2012], Bund. U 2829 Figure 4: Relationship between compression index and liquid limit of soil Figure 5: Relationship between compression index and optimum moisture content of soil

10 Vol. 17 [2012], Bund. U 2830 Figure 6: Relationship between compression index and plasticity index of soil Figure 7: Relationship between shear angle and plasticity index of soil CONCLUSION The following conclusions may be made based on the above test results, discussions and correlations: As clay content increases in the soil, plasticity increases.

11 Vol. 17 [2012], Bund. U 2831 Plasticity increases as optimum moisture content (OMC) of soil increases. With the increase of plasticity, angle of internal friction decreases (ϕ). With the increase of liquid limit (LL), compression index (C c ) also increases. With the increase of OMC, C c also increases. The value of the coefficient of determination (R2) is near about 1.0 for all the five equations established. The empirical relationship, for PI as function of LL has been developed in the form of linear equation. The error in the predicted values of PI (%), verified with the previous studies are within the range of % to +2.46%. The best-fit trend line of OMC with PI of soil as linear relationship has been developed. The errors in the predicted values of OMC (%), verified with the previous studies are within the range of to %. The empirical relationship, for compression index (Cc) as function of liquid limit (LL) of soil has been showed best-fit trend line as linear equation. The error in the predicted values of Cc, verified with the previous investigators test data are within the range of to %. The best-fit trend line of compression index (Cc) with optimum moisture content (OMC) of soil as linear relationship has been developed. The errors in the predicted values of Cc, verified with the previous studies are within the range of to %. The empirical relationship, for compression index (C c ) as function of plasticity index (PI) has been developed in the form of linear equation. The errors in the predicted values of Cc, verified with the previous studies are within the range of to %. REFERENCES 1. Al-Kahdaar, R.M., and Al-ameri, A.F.I. (2010) Correlations between physical and mechanical properties of al-ammarah soil in messan governorate, Journal of Engineering, Vol. 4, Al-Khafaji, A. W. N., and Andersland, O. B. (1992) Equations for compression index approximation, J. Geotech Engg., ASCE, 118(1), Bera, A. K., Ghosh, A., and Ghosh, A. (2007) Compaction characteristics of pond ash, J. Mat. Civil Engg, ASCE, 19(4), Bowles, J. E. (1996) Physical and geotechnical properties of soils, McGraw-Hill international editions. 5. Draper, N. R. and Smith, H. (1998) Applied regression analysis, John Wiley and Sons, New York. 6. Giasi, C.I., Cherubini, C. and Paccapelo, F. (2003) Evaluation of compression index of remoulded clays by means of Atterberg limits, Bull Engg. Geol. Env.. 62, Gunaydm, O. (2009) Estimation of soil compaction parameters by using statistical analyses and artificial neural networks, Environ. Geol. 57,

12 Vol. 17 [2012], Bund. U Haan, C. T. (1994) Statistical methods in hydrology, Affiliated East-West Press Pvt. Ltd., New Delhi, India. 9. Johnson, A.W. and Sallberg, J. R. (1960) Factors that influence field compaction of soils (compaction characteristics of field equipment), Highway Res. Board Bull 272: Jumikis, A. R. (1946) Geology and soils of the Newark (NJ) metropolitan area, J. Soil Mech. Found., ASCE, 93(2), Jumikis, A. R. (1958) Geology and soils of the Newark (NJ) metropolitan area, J. Soil Mech. Found. Div. 94(2). 12. Kaniraj, S. R., and Havanagi, V. G. (2001) Correlation analysis of laboratory compaction of fly ashes. J. Practice Periodical of Hazardous, Toxic and Radioactive Waste Management, ASCE, 5(1), Kumar, V. P. and Sudharani, C. H. (2001) Prediction of compression index of soils using artificial neural networks (anns), International Journal of Engineering Research and Applications, 1(4), Nakase, A., Kamei, T., and Kusakabe, O. (1988) Constitute parameters estimated by plasticity index, J. Geotech. Engg., ASCE, 114, Nath, A. and Dalal, S. S. (2004) The role of plasticity index in predicting compression behavior of clays, Electronic Journal of Geotechnical Engineering, vol. 9, 2004-Bundle E. 16. Pal, S.K and Ghosh, A (2011) Compaction and hydraulic conductivity characteristic of Indian fly ash, Indian geotechnical conference, December 2011, Kochi, P Ring, G.W., Sallberg, J. R. and Collins, W. H. (1962) Correlation of compaction and classification test data, HRB 325, Sridharan, A. and Nagaraj, H. B. (2000) Coefficient of consolidation and its correlation with index properties of remolded soils, Geotechnical Testing Journal, 27(5). 19. Terzaghi, K. and Peck R.B. (1967) Soil mechanics in engineering practice, 2nd edn. Wiley, New York 2012 ejge