• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.261-268
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• 2022

Purpose: In the case of cavity discovered by ground penetrating radar exploration, it is necessary to accurately predict the filling amount in the cavity in advance, fill the cavity sufficiently and exert strength to ensure stability and prevent ground subsidence. Method: The cavity waveform analysis method by GPR exploration and the method using the cavity shape imaging equipment were performed to measure the cavity shape with irregular size and shape of the actual cavity, and the amount of cavity filling of the injection material was calculated during rapid restoration. Results: The expected filling amount was presented by analyzing the correlation between the cavity size and the filling amount of injection material according to the cavity scale and soil depth through the method by GPR exploration and the cavity scale calculation using the cavity shaping equipment. Conclusion: The cavity scale measured by the cavity imaging equipment was found to be in the range of 20% to 40% of the cavity scale by GPR exploration. In addition, the filling amount of injection material compared to the cavity scale predicted by GPR exploration was in the range of about 60% to 140%, and the filling amount of the injection material compared to the cavity size by the cavity shaping equipment was confirmed to be about 260% to 320%.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.499-500
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• 2018

최근 지반이 가라앉아 지면에 구멍이 발생하는 싱크홀(Sink Hole)의 발생이 빈번하게 발생하고 있으며, 이에 대한 피해사례도 증가하고 있다. 이를 예방하고 대응하기 위하여 국가적으로 대대적인 지반조사를 하고 있으며 해당 지반을 탐사하기 위하여 지표투과레이더와 내시경 등을 활용한 방법을 사용하고 있다. 본 논문에서는 현재까지 가장 효율적인 방법으로 알려진 지표투과레이더의 데이터를 그래프 형태로 표현하고 분석하여 효과적으로 탐사를 할 수 있는 시스템을 제안한다.

• Journal of the Korean Geotechnical Society
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• v.39 no.7
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• pp.49-56
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• 2023

Gravel is commonly employed to enhance the bearing capacity of foundations and provide stable support for structures. However, effectively assessing the ground characteristics in the presence of gravel poses significant challenges. This study aims to compare the resolution of ground containing gravel using electrical resistivity, elastic wave surveys, and ground penetration radar (GPR). Nondestructive methods are applied at construction sites where soil improvement is carried out using gravel. The experiments focus on shallow depths, and the obtained results cover depths up to 2 m. Both the electrical resistivity and elastic wave techniques exhibit similar behavior in their findings, indicating comparable outcomes. However, GPR has limitations in observing the characteristics of ground with gravel. Dynamic cone-penetration tests were conducted to validate these findings. The electrical resistivity and elastic wave profiles exhibited similar behaviors in localized areas, further supporting their compatibility and reliability.

• Geophysics and Geophysical Exploration
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• v.19 no.1
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• pp.20-28
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• 2016

Recently many sinkholes have appeared in urban areas of Korea, threatening public safety. To predict the occurrence of sinkholes, it is necessary to investigate the existence of cavity under urban roads. Ground-penetrating radar (GPR) has been recognized as an effective means for detecting underground cavity in urban areas. In order to improve the understanding of the governing physical processes associated with GPR wave propagation, and interpret underground cavity effectively, a theoretical approach using numerical modeling is required. We have developed an algorithm employing a three-dimensional (3D) staggered-grid finite-difference time-domain (FDTD) method. This approach allows us to model the full electromagnetic wavefield associated with GPR surveys. We examined the GPR response for a simple cavity model, and the modeling results showed that our 3D FDTD modeling algorithm is useful to assess the underground cavity under urban roads.

• Journal of the Korean Geotechnical Society
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• v.40 no.2
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• pp.105-113
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• 2024

Underground buried cables can cause disconnections during the construction of roads and other subterranean structures due to uncertain designs. This paper describes experiments conducted to detect and verify the locations of these cables utilizing ground penetrating radar (GPR). The experiments were carried out at an active road construction site, where cable burial was anticipated. The GPR used operated within a frequency range of 400 MHz to 900 MHz to probe underground structures. The exploration methodology consisted of an initial GPR test to survey the entire area, followed by a secondary test informed by the results of the initial experiment, incorporating a diverse and increased number of lines. The findings confirmed the hyperbolic reflection patterns of cables at consistent locations along the same lines. These patterns were then compared to existing designs to corroborate the presence of cables at the identified locations. This research establishes an effective GPR methodology based on the electromagnetic wave reflection pattern, specifically the hyperbola, to detect difficult-to-locate underground buried cables.

• Journal of the Korean GEO-environmental Society
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• v.25 no.2
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• pp.5-14
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• 2024

Reinforced concrete bridge decks are the first to be damaged by vehicle loads and rain infiltration. Concrete deterioration primarily occurs owing to the corrosion of rebars and other metal components by chlorides used for snow and ice melting. The structural condition and concrete deterioration of the bridge decks within the pavement were evaluated using ground-penetrating radar (GPR) survey data. To evaluate concrete deterioration in bridges, it is necessary to develop GPR data analysis techniques to accurately identify deteriorated locations and rebar positions. GPR exploration involves the acquisition of reflection and diffraction wave signals due to differences in radar wave propagation velocity in geotechnical media. Therefore, a full-waveform inversion (FWI) method was developed to evaluate the deterioration of reinforced concrete bridge decks by estimating the radar wave propagation velocity in geotechnical media using GPR data. Numerical experiments using a GPR velocity model confirmed the deterioration phenomena of bridge decks, such as concrete delamination and rebar corrosion, verifying the applicability of the developed technology. Moreover, using the synthetic GPR data, FWI facilitates the determination of rebar positions and concrete deterioration locations using inverted velocity images.

• The Journal of Engineering Geology
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• v.17 no.4
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• pp.517-523
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• 2007

Geophysical surveys(seismic refraction, electrical resistivity, and ground penetrating radar) were performed to delineate the weathering zone associated with vadose water in Chojeong area and investigate the fault related fracture zones. On the basis of seismic velocity structures, weathering layer for the southwestern part is interpreted to be deeper than for the northeastern part. The depth to bedrock(i.e., thickness of weathered zone) from seismic refraction data attempted to be correlated with drill-core data and groundwater level. As for the investigation of geological discontinuities such as fault related fracture zone, seismic refraction, electrical resistivity, and ground penetrating data are compositely employed in terms of velocity and resistivity structures for mapping of surface boundary of the discontinuities up to shallow depth. Surface boundaries of fracture zone are well indicated in seismic velocity and electrical resistivity structures. Accurate estimation of weathered zone and fracture zone can be successfully available for mapping of attitude of vadose water layer.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.171-184
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• 2023

Machine learning (ML)-based cavity detection using a large amount of survey data obtained from vehicle-mounted ground penetrating radar (GPR) has been actively studied to identify underground cavities. However, only simple image processing techniques have been used for preprocessing the ML input, and many conventional seismic and GPR data processing techniques, which have been used for decades, have not been fully exploited. In this study, based on the idea that a cavity can be identified using diffraction, we applied ML-based diffraction separation to GPR data to increase the accuracy of cavity detection using the YOLO v5 model. The original ML-based seismic diffraction separation technique was modified, and the separated diffraction image was used as the input to train the cavity detection model. The performance of the proposed method was verified using public GPR data released by the Seoul Metropolitan Government. Underground cavities and objects were more accurately detected using separated diffraction images. In the future, the proposed method can be useful in various fields in which GPR surveys are used.

• Geophysics and Geophysical Exploration
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• v.24 no.3
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• pp.113-130
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• 2021

Recently, ground-penetrating radar (GPR) surveys have been actively employed to obtain a large amount of data on occurrences such as ground subsidence and road safety. However, considering the cost and time efficiency, more intuitive and accurate interpretation methods are required, as interpreting a whole survey data set is a cost-intensive process. For this purpose, GPR data can be subjected to attribute analysis, which allows quantitative interpretation. Among the seismic attributes that have been widely used in the field of exploration, complex trace analysis and similarity are the most suitable methods for analyzing GPR data. Further, recently proposed attributes such as edge detecting and texture attributes are also effective for GPR data analysis because of the advances in image processing. In this paper, as a reference for research on the attribute analysis of GPR data, we introduce the useful attributes for GPR data and describe their concepts. Further, we present an analysis of the interpretation methods based on the attribute analysis and past cases.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.