Effectiveness of 2-D and 2.5-D FDTD Ground-Penetrating Radar Modeling for Bridge-Deck Deterioration Evaluated by 3-D FDTD

Computational modeling effectively analyzes the wave propagation and associated interaction within heterogeneous reinforced concrete bridge decks, providing valuable information for sensor selection and placement. It provides a good basis for the implementation of the inverse problem in defect detection and the reconstruction of subsurface properties, which is beneficial for defect diagnosis. The objective of this study is to evaluate the effectiveness of lower order models in the evaluation of bridge-deck subsurfaces modeled as layered media. The two lower order models considered are a 2-D model and a 2.5-D model that uses the 2-D geometry with a compressed coordinate system to capture wave behavior outside the cross-sectional plane. Both the 2- and 2.5-D models are compared to the results obtained from a full 3-D model. A filter that maps the 3-D excitation signal appropriately for 2- and 2.5-D simulations is presented. The 2.5-D model differs from the 2-D model in that it is capable of capturing 3-D wave behavior interacting with a 2-D geometry. The 2.5-D matches results from the corresponding 3-D model when there is no variation in the third dimension. Computational models for air-launched ground-penetrating radar with 1-GHz central frequency and bandwidth for the detection of bridge-deck delamination are implemented in 2-, 2.5-, and 3-D using FDTD simulations. In all cases, the defect is identifiable in the results. Thus, it is found that in layered media (such as bridge decks) 2- and 2.5-D models are good approximations for modeling bridge-deck deterioration, each with an order of magnitude reduction in computational time.

I. Introduction

The ground-penetrating radar (GPR) is a popular tool for rapid noninvasive geophysical sensing of reinforced concrete structures. In particular, road and bridge pavement diagnostics, including detecting media delamination and voids [1], are amenable to GPR probing. The severity of deterioration within the structure can be determined by means of the detection and localization of these subsurface pavement defects, thus allowing efficient allocation of limited funds for repair and maintenance. Recent work in the area of feature determination includes the improved determination of layer thicknesses [2], [3], more accurate prediction of the underground GPR wavefront and B-scan shape [4], determination of the time origin of the signals [5], and refined method of GPR bridge survey analysis by accounting for signal depth-amplitude effects [6].