Determining suction compression index of expansive soils based on non-linear suction-volumetric strain relationship

Expansive soils have always been problematic in many parts of the United States and the world. This is due to the stresses they exert on buildings' foundations, pavements, and other geotechnical structures. In the United States, volumetric changes due to shrinking and swelling soils cause extensive damage which costs billions of dollars annually. In the state of Oklahoma, expansive soil is widespread and the annual maintenance can cost millions of dollars statewide. The climatic conditions in the state easily allow for soil volume changes. This happens due to the wetting and drying cycles which affect the moisture active zone in unsaturated soils. Suction compression index (?h) is the key parameter that relates volumetric changes to soil suction changes in unsaturated soils. It is a soil property through which heave in expansive soils can be predicted due to the change in soil suction. It can be determined as the slope of the suction-volumetric strain relationship. Since this relationship is essentially nonlinear, the need for a precise ?h determination method has always been crucial. The more accurate ?h is determined, the more accurate soil movements can be predicted and taken care of early in the design stage. Accordingly, more money can be saved from either the repair costs or the initial costs by avoiding over-design. This study proposes an original ?h testing method. The testing method uniquely incorporates volumetric and suction measurements in a new and practical way utilizing simple digital imaging. This makes it convenient for geotechnical engineering practitioners and laboratories to adopt the testing method. The testing method unprecedentedly integrates statistical modeling for determination of incremental h in order to cover the entire nonlinearity of the suction-volumetric strain relationship. This is done by fitting the S-shaped relationship by a well-known class of statistical functions called Cumulative Distribution Functions (CDF). Incremental ?h is estimated by estimating the CDF at every suction value. The appropriateness of using these estimates to describe the suction-volumetric strain relationship is evaluated using the Kolmogorov-Smirnov (K-S) goodness of fit test. Furthermore, 95% confidence intervals of the superposed curves are also used to assess the appropriateness of the CDF estimates. Undisturbed soil specimens from three sites in Oklahoma have been tested. The new testing method is compared against other techniques in the literature and proven reliable results