Maria Giulia Brancadoro

Bio: Maria Giulia Brancadoro is an academic researcher from Roma Tre University. The author has contributed to research in topics: Ground-penetrating radar & Ballast. The author has an hindex of 5, co-authored 9 publications receiving 81 citations.

A spectral analysis of ground-penetrating radar data for the assessment of the railway ballast geometric properties

Abstract: This paper presents a methodology for the assessment of railway ballast using ground-penetrating radar (GPR – 2 GHz horn antenna). The primary approach in this endeavour was the finite-difference time-domain (FDTD) simulations of ballast (a multi-stage process in terms of ballast size). To this effect, a combination of random sequential adsorption (RSA) and FDTD algorithms were applied. The results of the numerical simulation then were used to compare with the experimental investigations results using a container (methacrylate material) of the 1.5 × 1.5 × 0.5 m dimensions. Finally, the modelling of the frequency spectrum peak and the equivalent diameter of the ballast aggregates was developed.

GPR applications in mapping the subsurface root system of street trees with road safety-critical implications

Abstract: Street trees are an essential element of urban life. They contribute to the social, economic and environmental development of the community and they form an integral landscaping, cultural and functional element of the infrastructure asset. However, the increasing urbanisation and the lack of resources and methodologies for the sustainable management of road infrastructures are leading to an uncontrolled growth of roots. This occurrence can cause substantial and progressive pavement damage such as cracking and uplifting of pavement surfaces and kerbing, thereby creating potential hazards for drivers, cyclists and pedestrians. In addition, neglecting the decay of the principal roots may cause a tree to fall down with dramatic consequences. Within this context, the use of the ground-penetrating radar (GPR) non-destructive testing (NDT) method ensures a non-intrusive and cost-effective (low acquisition time and use of operators) assessment and monitoring of the subsurface anomalies and decays with minimum disturbance to traffic. This allows to plan strategic maintenance or repairing actions in order to prevent further worsening and, hence, road safety issues. This study reports a demonstration of the GPR potential in mapping the subsurface roots of street trees. To this purpose, the soil around a 70-year-old fir tree was investigated. A ground-coupled GPR system with central frequency antennas of 600 MHz and 1600 MHz was used for testing purposes. A pilot data processing methodology based on the conversion of the collected GPR data (600 MHz central frequency) from Cartesian to polar coordinates and the cross-match of information from several data visualisation modes have proven to identify effectively the three-dimensional path of tree roots.

A simulation-based approach for railway applications using GPR

Abstract: In this work a numerical model capable to predict the electromagnetic response of railway ballast aggregates under different physical conditions has been calibrated and validated by a simulation-based approach. The ballast model is based on the main physical and geometrical properties of its constituent material and it is generated by means of a random-sequential absorption (RSA) approach. A finite-difference time-domain (FDTD) simulator is then employed to calculate the ground-penetrating radar (GPR) signal response to the scenario. The calibration of the model has been performed by taking into account the main physical properties and the grain size characteristics of both the reference ballast material and a fine-grained pollutant material, namely, an A4 soil type material, according to the AASHTO soil classification. The synthetic GPR response has been generated by using the gprMax freeware simulator. Several scenarios have been considered, which in turn were reproduced in laboratory environment and used for the validation of the model. Promising results have demonstrated the high potential of such approach in characterizing the simulated response of complex coarse-grained heterogeneous materials.

How to create a full-wave GPR model of a 3D domain of railway track bed?

Abstract: Ground-penetrating radar (GPR) investigations of railway track beds are becoming more important nowadays in civil engineering. The manufacturing of representative full-scale scenarios in the laboratory environment for the creation of databases can be a critical issue. It is difficult to reproduce and monitor the effect of differing physical and performance parameters in the ballast layer as well as to evaluate the combination of these factors in more complex scenarios. In addition, reproducing full-scale tests of railway ballast implies to handle huge amounts of aggregates. To this effect, the use of the Finite-Difference Time-Domain (FDTD) simulation of the ground-penetrating radar signal can represent a powerful tool for creating, extending or validating databases difficult to build up and to monitor at the real scale of investigation. Nevertheless, a realistic three-dimensional simulation of a railway structure requires huge computational efforts. This work focuses on performing simula-tion of the ground-penetrating radar signal within a railway track bed by using a two-dimensional cross-section model of the ballast layer, generated by a Random Sequential Adsorption (RSA) paradigm. Attention was paid on the geometric reconstruction of the ballast system as well as on the content of voids between the aggregate particles, which complied with the real-world conditions of compaction for this material. The resulting synthetic GPR signal was subsequently compared with the real signal collected within a realistic track bed scenario of ballast aggregates recreated in the laboratory environment.

Signal processing of GPR data for road surveys

Abstract: Effective quality assurance and quality control inspections of new roads as well as assessment of remaining service-life of existing assets is taking priority nowadays. Within this context, use of ground penetrating radar (GPR) is well-established in the field, although standards for a correct management of datasets collected on roads are still missing. This paper reports a signal processing method for data acquired on flexible pavements using GPR. To demonstrate the viability of the method, a dataset collected on a real-life flexible pavement was used for processing purposes. An overview of the use of non-destructive testing (NDT) methods in the field, including GPR, is first given. A multi-stage method is then presented including: (i) raw signal correction; (ii) removal of lower frequency harmonics; (iii) removal of antenna ringing; (iv) signal gain; and (v) band-pass filtering. Use of special processing steps such as vertical resolution enhancement, migration and time-to-depth conversion are finally discussed. Key considerations about the effects of each step are given by way of comparison between processed and unprocessed radargrams. Results have proven the viability of the proposed method and provided recommendations on use of specific processing stages depending on survey requirements and quality of the raw dataset.

Automatic classification of ground-penetrating-radar signals for railway-ballast assessment

Abstract: The ground-penetrating radar (GPR) has been widely used in many applications However, the processing and interpretation of the acquired signals remain challenging tasks since an experienced user is required to manage the entire operation In this paper, we present an automatic classification system to assess railway-ballast conditions It is based on the extraction of magnitude spectra at salient frequencies and their classification using support vector machines The system is evaluated on real-world railway GPR data The experimental results show that the proposed method efficiently represents the GPR signal using a small number of coefficients and achieves a high classification rate when distinguishing GPR signals reflected by ballasts of different conditions

Transport Infrastructure Monitoring by InSAR and GPR Data Fusion

Abstract: This study reviews research developments in non-destructive assessment of linear transport infrastructures. The main focus will be on the integration between satellite remote sensing and ground-based techniques. Specifically, the potential of using interferometric synthetic aperture radar (InSAR) and high-frequency ground penetrating radar (GPR) techniques as self-standing and integrated survey methodologies will be discussed. To this effect, an overview on data fusion techniques will be given. The last section of the paper reports recent results achieved by using both GPR systems and the permanent scatterers InSAR technique on a real-life railway.

An investigation into the railway ballast dielectric properties using different GPR antennas and frequency systems

Abstract: This paper presents an investigation into the relative dielectric permittivity of railway ballast using ground-penetrating radar (GPR). To this effect, the experimental tests are carried out using a container (methacrylate material) of dimensions 1.5 × 1.5 × 0.5 m. GPR systems equipped with different ground-coupled and air-coupled antennas and central frequencies of 600 MH, 1000 MHz, 1600 MHz and 2000 MHz (standard and low-powered antenna systems) are used for testing purposes. Several processing methods are applied to assess and compare the dielectric permittivity of the ballast system under investigation. A comparison of the results identifies critical factors as well as antennas and central frequencies most suitable for the purpose.