GPR applied to mapping utilities along the route of the Line 4 (yellow) subway tunnel construction in São Paulo City, Brazil

Porsani, Jorge Luís; Ruy, Yang Boo; Ramos, Fernanda Pereira; Yamanouth, Gisele R.B.

doi:10.1016/j.jappgeo.2012.01.001

Cited by 53 publications

(18 citation statements)

References 14 publications

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“…It is well known that GPR has been extensively used for non-destructive testing problems [17], [18], [19] with mainstream civil engineering applications that include: mapping of utilities [20], [21], bridge evaluation [22], [23], road inspection [24], [25], [26], pipe location, [27], [28] and crack detection [29], [30]. The mapping of reinforcement in concrete using GPR [31] is particularly attractive due to the high contrast in dielectric properties between concrete and steel, combined with the fact that concrete is a relatively homogeneous medium which further increases the overall signal-to-clutter ratio.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning-Based Fast-Forward Solver for Ground Penetrating Radar With Application to Full-Waveform Inversion

Giannakis

Giannopoulos

Warren

2019

IEEE Trans. Geosci. Remote Sensing

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The simulation, or forward modeling, of Ground Penetrating Radar (GPR) is becoming a more frequently used approach to facilitate interpretation of complex real GPR data, and as an essential component of full-waveform inversion (FWI). However, general full-wave 3D electromagnetic (EM) solvers, such as ones based on the Finite-Difference Time-Domain (FDTD) method, are still computationally demanding for simulating realistic GPR problems. We have developed a novel near realtime, forward modeling approach for GPR that is based on a machine learning (ML) architecture. The ML framework uses an innovative training method which combines a predictive principal component analysis technique, a detailed model of the GPR transducer, and a large dataset of modeled GPR responses from our FDTD simulation software. The ML-based forward solver is parameterized for a specific GPR application, but the framework can be applied to many different classes of GPR problems. To demonstrate the novelty and computational efficiency of our ML-based GPR forward solver, we used it to carry out FWI for a common infrastructure assessment application-determining the location and diameter of reinforcement bars in concrete. We tested our FWI with synthetic and real data, and found a good level of accuracy in determining the rebar location, size, and surrounding material properties from both datasets. The combination of the near real-time computation, which is orders of magnitude less than what is achievable by traditional full-wave 3D EM solvers, and the accuracy of our ML-based forward model is a significant step towards commercially-viable applications of FWI of GPR.

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Section: Introductionmentioning

confidence: 99%

A Machine Learning-Based Fast-Forward Solver for Ground Penetrating Radar With Application to Full-Waveform Inversion

Giannakis

Giannopoulos

Warren

2019

IEEE Trans. Geosci. Remote Sensing

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“…The GPR technology is quite versatile and has been consolidated since the 1980s. Currently, geoscientists have applied the GPR method in a range of approaches, such as interference mapping [12][13][14][15][16][17][18][19][20][21][22][23], natural resources exploration [24][25][26][27], environmental contamination studies [28][29][30][31], archaeological studies [32][33][34][35][36][37][38], forensic studies [39][40][41], sedimentological studies [42][43][44][45], studies of rivers and lakes [46][47][48], and so forth.…”

Section: Gpr Methodsmentioning

confidence: 99%

GPR Survey on an Iron Mining Area after the Collapse of the Tailings Dam I at the Córrego do Feijão Mine in Brumadinho-MG, Brazil

2019

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This article shows the interesting results of a pioneer effort by IAG/USP researchers to use ground-penetrating radar (GPR) for humanitarian purposes, guiding the rescue of victims in the tragedy of Brumadinho. The tailings Dam I at the Córrego do Feijão iron ore mine, located in the Brumadinho complex, Minas Gerais State, Brazil, collapsed on 25 January 2019. About 11.7 million m3 of mining mud was spilled from the dam, burying bodies, equipment, structural buildings, buses, and cars along a length of 8.5 km up to the Paraopeba River. Additionally, the contaminated mud traveled more than 300 km along the bed of the Paraopeba River toward the São Francisco River. This work shows the results of a geophysical investigation using the GPR method 17 days after the event. To carry out the geophysical survey, an excavator was used for soil compaction. The data acquisition was performed on the tracks left by the excavator chain using SIR-4000 equipment and antennas of 200 and 270 MHz (GSSI). The GPR studies aimed to map bodies, structural buildings, and equipment buried in the mud. The location of the profiles followed preferably the edge of the slope due to the higher probability of finding buried bodies and objects. The GPR results allowed the detection of subsoil structures, such as concentrations of iron ore and accumulations of sand from the dam filter. The GPR was effective because the iron ore sludge in the mixing process became porous and the pores were filled with air, which provided penetration and reflection of the GPR electromagnetic waves up to a depth of 3.5 m. The results were surprising. Although no bodies or underground equipment were found, the results of this research served to eliminate the studied areas from future excavations, thus redirecting the rescue teams and optimizing the search process. These important results can serve as an additional motivation for the use of GPR in future humanitarian work in areas of tragedies.

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“…Por exemplo, obras urbanas como a construção de viadutos, instalação de redes hidráulicas e elétricas, a escavação de tuneis para veículos e metrô necessitam de estratégias para evitar estragos a construções já existentes, bem como acidentes no decorrer das obras (cf. PORSANI et al, 2012). Problemas ambientais urbanos, como o vazamento de óleo em cabos elétricos subterrâneos às margens do Rio Pinheiros, zona leste de São Paulo (OLIVEIRA, 2008), podem ser detectados de forma relativamente rápida, assim orientando estratégias de conserto e evitando maiores prejuízos ao ecossistema.…”

Section: Geofísica Arqueológicaunclassified

Geofísica arqueológica no ambiente da Arqueologia Urbana

Allen

Porsani

Poluha

2017

rsab

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A reforma e a requalificação de centros históricos -como construção, saneamento, pavimentação, entre outras -requerem que uma pesquisa arqueológica seja realizada antes de qualquer intervenção. Nesse contexto, busca-se um equilíbrio entre o que pode sofrer impactos negativos e o que deve ser estudado e preservado arqueologicamente, sempre buscando atender à necessidade do melhoramento dos locais públicos. O Largo da Igreja Nosso Senhor do Bonfim, Marechal Deodoro, Alagoas, ofereceu oportunidade de empregar o método geofísico GPR (Ground Penetrating Radar ou Georadar) para orientar escavações, identificar áreas para preservação e informar engenheiros civis sobre possíveis desafios para a execução do projeto civil. Os resultados foram interessantes, proporcionando um bom argumento para a incorporação de metodologias geofísicas em projetos de Arqueologia Urbana similares. Palavras-chave: GPR-Ground Penetrating Radar; Geofísica arqueológica; Arqueologia Urbana. ABSTRACTBrazilian urban renewal projects in historic districts require that archaeological research be conducted prior to any intervention, such as excavations for sanitation, construction, pavement, among others. In such a context, a balance must be struck between what might suffer impacts and what should be studied and preserved archaeologically, while attending the need to improve these public spaces. The Largo da Igreja Nosso Senhor do Bonfim, a public square dating to the early 17th century, offered the opportunity to use Ground Penetrating Radar to guide excavations, identify areas for preservation and to inform civil engineers of possible challenges for the project generally. The results were mixed, but provide a strong argument for the incorporation of geophysical methods in similar projects.

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GPR applied to mapping utilities along the route of the Line 4 (yellow) subway tunnel construction in São Paulo City, Brazil

Cited by 53 publications

References 14 publications

A Machine Learning-Based Fast-Forward Solver for Ground Penetrating Radar With Application to Full-Waveform Inversion

A Machine Learning-Based Fast-Forward Solver for Ground Penetrating Radar With Application to Full-Waveform Inversion

GPR Survey on an Iron Mining Area after the Collapse of the Tailings Dam I at the Córrego do Feijão Mine in Brumadinho-MG, Brazil

Geofísica arqueológica no ambiente da Arqueologia Urbana

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