Date of Award


Degree Type


Degree Name

Master of Science in Ocean Engineering


Ocean Engineering

First Advisor

Christopher Baxter


Knowing the depth to bedrock is important in designing and constructing foundations for buildings and transportation infrastructure. Rock is typically a strong and competent foundation material, however if it is close to the ground surface it can be costly to remove. This is especially true if the presence of shallow rock is not known until construction. In many transportation projects where geotechnical borings are widely spaced along a road alignment, areas of shallow rock can be easily missed until construction of drainage structures beneath the road. More research is needed on the viability of cost effective tools to identify the presence of shallow rock before construction.

Non-destructive evaluation (NDE) techniques to characterize the stiffness of soils may be a good tool for this problem. Spectral Analysis of Surface Waves (SASW) is a wave propagation method in which vertical shear wave velocity profiles and elastic moduli of subsurface layers of soil and rock can be estimated. The profiles are obtained from the analysis of surface wave data, usually generated from a falling weight and measured by an array of two or more geophones.

The objective of this thesis is to evaluate the efficiency of the SASW system for use in transportation projects in Rhode Island. It will focus on the identification of shallow rock for aid in construction of drainage structures.

SASW tests were performed at five different locations. The resulting shear wave velocity profiles were analyzed and evaluated for the following: 1) identification of shallow rock, 2) global vs. array approach for modeling the dispersion curve and 3) influence of the initial layer thickness.

The results showed that it was possible to identify the presence of rock layers with the SASW system. However, the SASW system was not that accurate in identifying the depth to rock. A key lesson from this study is that the process to estimate the shear velocity requires considerable experience and personal judgment. There are many factors that affect the prediction of shear wave velocities, including the selection of data for analysis (masking), the type of approach for modeling the dispersion curve, and the steps used in the inversion.



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