Ground penetrating radar attributes for nondestructive characterization of concrete

Abstract

Accurate estimates of in situ material properties are an essential component of effective decision making, conservation, and maintenance of civil infrastructure, historic buildings, and geotechnical projects. Standard in situ material characterization methods for soils and construction materials like concrete include reliable but invasive approaches like core sampling. Where invasive tests are not possible, alternatives such as ultrasonic pulse velocity or rebound hammer tests must be used; these tests can be difficult to interpret or perform reliably and only provide information about discrete points. Another technique, ground penetrating radar (GPR), is a versatile, efficient, and accessible method for feature detection that can provide continuous spatial information about a site. Those advantages support the prevalence of GPR in civil infrastructure and historic site management, precisely the fields that stand to benefit from a nondestructive in situ material characterization technique. Furthermore, GPR is often cited as being sensitive to mechanical properties, but the link between physical properties and electromagnetic properties as recorded by GPR signals is not fully characterized or understood. As such, this thesis explores the fundamental relationships between GPR attributes and potential predictions of material properties from those GPR attributes. Included first is an introduction to the GPR method and the limits of qualitative GPR data analysis through a survey performed at a medieval castle. Then, the technique of attribute analysis is introduced as a quantitative tool to interpret and analyze GPR data. The GPR attributes of the concrete from two different construction phases of Streicker Bridge are compared to determine if attributes are sensitive to relative differences in material properties. This chapter motivates an experiment to establish and characterize the relationship between GPR attributes and porosity, density, and compressive strength in concrete samples. Relationships between the GPR attributes and measured material properties are described by regression models trained and tested on the laboratory data. Those models can predict the porosity and density of lab samples and the compressive strength of the concrete in Streicker Bridge from the GPR attributes alone. Finally, the impact and future directions of this research are discussed.