SOIL MECHANICS - LABORATORY TESTING KH HEAD

Soil Mechanics Laboratory Testing

Soil Mechanics Laboratory Testing

The swell index which is the slope of the rebound curve of void ratio versus the logarithm of the effective pressure curve is used to estimate the consolidation settlement of over-consolidated fine grained soils. Because determination of swell index from oedometer tests takes a relatively long time, empirical equations involving index soil properties, are needed to estimate it for preliminary calculations and to control the validity of consolidation tests. Geotechnical engineering literature involves empirical equations for the estimation of compression and swell indexes. In this study the performance of widely used empirical equations were assessed using a database consisting of 42 test data.

In addition to this, new empirical relationships with single and multiple dependent variables were developed with better estimation capability. An artificial neural network (ANN) which has two input variables, one hidden layer and eight hidden layer nodes was also developed to estimate swell index. It was concluded that the performance of the ANN is better than empirical equations. The compression index (Cc) represents the slope of the curve of void ratio versus logarithm of effective pressure beyond maximum past effective stress and the swell index (Cs) represents the slope of the rebound curve of void ratio versus logarithm of effective pressure. Compression index and swell index are used for the calculation of consolidation settlement of overconsolidated fine grained soils and they are conventionally determined by laboratory odedometer tests.

However, the duration of conslidation tests is very long compared to standard index tests. For this reason, it is important to estimate compression and swell indexes with reasonable accuracy for preliminary calculations and to control the validity of consolidation tests. A large number of empirical equations are present in the geotechnical literature for the estimation of compression index (Skempton, 1944; Helenelund, 1951; Cozzolino, 1961; Sowers, 1970; Wroth and Wood, 1978; Carrier, 1985; Nagaraj and Murthy, 1986; Nakase et al., 1988; Bowles, 1989; Yin, 1999; Sridharan and Nagaraj, 2000; Giasi et al., 2003; Yoon et al., 2004; Ozer et al., 2008) however only two widely used equations are present for the estimation of swell index. The purpose of this study is to compare the performances of widely used empirical swell index equations and to develop new empirical equations and a neural network based estimation technique for swell index by using the results of conventional oedometer and index test results.

DATABASE COMPILATION

In order to build the database, conventional oedometer tests were performed according to ASTM 2435 (ASTM, 1996) on various undisturbed clay samples which were taken from various locations in Turkey. In addition to oedometer tests, index tests were performed on each sample according to relevant ASTM standards. Soil parameters used in the database were natural water content (wn), natural unit weight (gn), dry unit weight (gd), percent of soil passing from No. 200 sieve, percent of soil passing from No. 4 sieve, liquid limit (LL), plastic limit (PL), initial void ratio (e0), specific gravity of ...