Author ORCID Identifier

https://orcid.org/0009-0006-0211-0811

Date Available

5-11-2024

Year of Publication

2024

Document Type

Master's Thesis

Degree Name

Master of Science in Civil Engineering (MSCE)

College

Engineering

Department/School/Program

Civil Engineering

Advisor

Dr. L. Sebastian Bryson

Abstract

This paper presents the results of an effort to use geophysical measurements such as seismic wave velocities and electrical resistivities to calculate airfield design parameters. The study converts all geophysical measurements to equivalent California Bearing Ratio (CBR) values, comparing CBR values estimated from DCP penetration resistance with CBR values estimated from shear wave velocity and electrical resistivity values. Relationships linking the geophysical measurements to CBR estimates were established using laboratory data and applied to field in-situ measurements. The elastic modulus (E) is the stiffness parameter involved in predicting soil strength and stiffness. This research aims to relate electrical conductivity and modulus by using a box test. A sigmoidal model was proposed for the prediction of elastic modulus as a function of conductivity, which performed well with high-strength soil. Soil tests from two different source locations were considered at different moisture contents, with a total of eight tests analyzed. The results show that elastic modulus values estimated from both shear wave velocity and DCP measurements tend to perform better at low conductivity and higher stiffness soil types. However, the elastic modulus from the proposed model does not match well with the DCP or shear wave velocity data when applied a field site located in Rouen, France. Overall, this study demonstrates the viability of using geophysical methods to assess airfield suitability and improve the accuracy of soil assessment in airfield design.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2024.168

Funding Information

The material presented in this thesis is based upon work supported by the University of Dayton Research Institute under Subcontract # RSC19048, in support of the US Air Force under Prime Contract # FA8650-18-C-2808.

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