Claudio Patriarca

GPR analysis of clayey soil behaviour in unsaturated conditions for pavement engineering and geoscience applications

Clay content is one of the primary causes of pavement damages, such as subgrade failures, cracks, and pavement rutting, thereby playing a crucial role in road safety issues as an indirect cause of accidents. In this paper, several ground-penetrating radar methods and analysis techniques were used to nondestructively investigate the electromagnetic behaviour of sub-asphalt compacted clayey layers and subgrade soils in unsaturated conditions. Typical road materials employed for load-bearing layers construction, classified as A1, A2, and A3 by the American Association of State Highway and Transportation Officials soil classification system, were used for the laboratory tests. Clay-free and clay-rich soil samples were manufactured and adequately compacted in electrically and hydraulically isolated formworks. The samples were tested at different moisture conditions from dry to saturated. Measurements were carried out for each water content using a vector network analyser spanning the 1 GHz–3 GHz frequency range, and a pulsed radar system with ground-coupled antennas, with 500-MHz centre frequency. Different theoretically based methods were used for data processing. Promising insights are shown to single out the influence of clay in load-bearing layers and subgrade soils, and its impact on their electromagnetic response at variable moisture conditions.

Uncertainty Quantification in Off-Ground Monostatic Ground Penetrating Radar

The characterization of the subsurface can be performed by full-waveform inversion of electromagnetic data. The modeling process relies on the ability to retrieve the scattered field Greens function from the measured data using sets of antenna characteristic global reflection and transmission coefficients. Crucial for a successful implementation of this technique is the understanding of uncertainties involved in the acquisition of the antenna calibration and survey measurements, and how these propagate in the parameter estimation results. We find that averaging a number of possible Greens functions obtained from one measurement with several antenna characteristic coefficients sets works remarkably well in reducing the uncertainties. The accuracy of the inversions improves using characteristic coefficients acquired as close as possible to the measurement conditions. A clear relation between dynamic range and system resolution is highlighted, based on the number of effective bits contained in the data.

Characterization of layered media using full-waveform inversion of proximal GPR data

Full-waveform inversion of proximal ground penetrating radar (GPR) data is used to determine the electromagnetic properties of layered media. The radar system consists of a vector network analyzer combined with an off-ground horn antenna operating at ultra wideband. The GPR wave propagation is modeled for a multilayered medium using a recursive Greens function computed in the frequency domain. The antenna and its interactions with the layered medium are modeled using a linear system of complex transfer functions. GPR signals were acquired in laboratory above a two-layered sand medium and two concrete slabs separated by a thin air layer (simulating a fracture). Subsequent inversions permit to retrieve the electromagnetic properties and the dimensions of these thin-layered media. For humid sand, GPR-derived dielectric permittivities showed a good agreement (RMSE = 1.65) with measured volumetric water contents. Dimensions of the three-layered concrete medium could be retrieved with a millimetric accuracy. The method is promising for the non-destructive characterization of multilayered media, including thin layers, owing to the full-waveform inversion of the radar data in a large frequency bandwidth.

Influence of acquisition related uncertainties on ground penetrating radar inversion results

Ground penetrating radar non-destructive testing requirements become more demanding. In that respect, it is essential to understand how antenna transfer functions and real system dynamic range affect the amount of retrievable information from measurements. This paper examines the confidence level of linear system transfer functions, and practical aspects of noise floor influence on stepped frequency ground penetrating radar. Small inaccuracies in antenna equations directly reflect in Greens function errors. Degradation of the numerical signal resolution was imposed by limiting the data resolution to two-bytes. The capability of the field system to detect thin layering in building materials using numerical modeling studies has been investigated. This would lead to the assumption that the radar model is correct and the only errors are due to inaccuracies in the data and the finite precision determination of the systems linear transfer functions. Systematic errors characterization is partially possible, limiting uncertainty in the data. A link seems to exist between the data precision and the possibility of information extrapolation for different settings.

Gradient based technique for electromagnetic layered earth model data inversion

Two methods for objective function minimization based on the idea of estimating the optimum gradient and on global search were compared in performing numerical and real data inversions. The required calculation of the gradient is based here on the numerical estimation of the reflection coefficient derivatives with respect to the model parameters. This results in a cheap computation method usable in specialized applications where quantitative EM analysis is required. It is shown that local optimization techniques allow for solving the inverse problem involving many layers that is intractable with global optimization techniques. It is remarkable that in the implemented smooth model, where the function Gxx↑(b, ω) and the reflection coefficients depend on smoothly varying model parameters, the gradient technique performs as well as the global minimization, with a considerable advantage in time inversion. The same advantage is observed in real data inversion.

Integrated full-waveform analysis of ground penetrating radar and electromagnetic induction data for non-invasive reconstruction of multilayered media

We present a new integrated method for full-waveform modeling of zero-offset, off-ground ground penetrating radar (GPR) and electromagnetic induction (EMI) in multilayered media. For both GPR and EMI systems, a vector network analyser (VNA) is used as transmitter and receiver. The antennas and their interactions with the investigated medium are modeled in the frequency domain by means of a linear system of complex transfer functions. The air-subsurface is represented by a 3-D multilayered medium, for which Maxwells equations are exactly solved. These approaches have been validated in laboratory conditions, demonstrating the high accuracy of the GPR and EMI models. The results show great promise for non-invasive reconstruction of multilayered media using GPR and EMI.