Laboratory Resistivity Measurements for Soil Characterization

Field based electrical resistivity measurements, such as electrical resistivity tomography (ERT) and capacitively coupled resistivity (CCR), are geophysical methods that offer a non-destructive and rapid means to collect continuous data. As such, ERT and CCR are becoming increasingly popular tools for geotechnical engineers; however, it is challenging to derive geotechnical information such as soil type, density, and water content from the data. A laboratory geophysical investigation was carried out to gain a better understanding of the parameters that affect the electrical resistivity of soils and devise a relationship between resistivity and soil type or classification. In this study, a soil box attached to a resistance meter in a 4-electrode Wenner array was used for the resistivity measurements. Nine different benchmark soils were tested, representing most of the major soil groups according to the unified soil classification system. The effects of water quality, water content, degree of saturation, bulk density, dry density, Atterberg limits and temperature on the measured electrical resistivity of the soils were investigated. Although there is an apparent correlation between all of these parameters and the electrical resistivity of soils, the parameters that are most effective in the identification of soil type are bulk density and degree of saturation. The laboratory results indicate that if the soil is saturated, a reasonable estimate of the soil group classification can likely be made from resistivity alone. For unsaturated samples, the range of possible resistivity values is much larger; however, the estimate of soil group can be significantly narrowed down if an approximation of saturation or density can be made. To assess the feasibility of the developed approach, a series of verification studies using samples acquired from the field and other processed soils were also conducted

Evaluation of Seamless Bridges

0-7011The research study included experimental testing and numerical modeling to obtain and develop much needed experimental data and analytical tools to study the performance of seamless systems, identify design issues, and propose design guidelines for the U.S. practice