• Geophysics and Geophysical Exploration
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• v.9 no.3
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• pp.225-230
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• 2006

Fluid replacement and conductivity logging have been applied to three boreholes in coastal aquifer in order to identify permeable fractures and to estimate the origin of saline groundwater. Fluid replacement technique measures and monitors the change of borehole fluid conductivity with depth under ambient or pumping condition after replacing the original borehole fluid with different one (by pumping out original one and injecting simultaneously new one at the hole bottom). After the replacement of borehole fluid, the change of fluid conductivity can be the direct indicator of the intake flow of formation water through aquifer such as permeable fractures or porous formations. The conductivity profiles measured with times therefore indicate the locations of permeable zone or fractures within the open hole or the fully slotted casing hole. As a result of fluid conductivity logging for three boreholes at coastal area in Yeonggwang, Jeonam Province, it is interpreted that the seawater intrusion in this area is not by remnant saline groundwater after land reclamation but mainly by intrusion of saline water through fractured rock. This approach might be useful for assessing the characteristics of seawater intrusion, the design of optimal pumping, the mitigation of seawater intrusion using freshwater injection, and estimating the hydraulic characteristics in coastal aquifer.

• The Journal of Engineering Geology
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• v.6 no.3
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• pp.137-153
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• 1996

The purpose of this study is to investigate the possibilities of identifying and detecting underground cavities using seismic waves recorded by the fixed and mobile stations. During 18 months of field work we recorded chemical explosions near the Bongdarn station. Seismic Stations were installed on the free surface and underground inside the Samba mine. The seismograms at the fixed(lorg-term) seismic station show abrupt change of polarization characteristics which can he associated with the appearance of P-to-S converted phase(PS) at 150 ~ 200 msec after the first P arrival. This result indicates that converted phases are generated very near to the Bongdarn station at a depth of 190m. Shear-wave splitting phenomena have also been observeci The time delay between fast shear(fS) and slow shear(sS) waves ranges between 30 and 60 msec(average is 42 msec). However, exact time delay between the fast and the slow shear waves can not be accurately measured because of the very short time delay and limitation of sampling rate. Chemical explosion experiments were recorded at stations along various paths to contrast the seismic response of areas with and without cavities. The seismograms recorded at the stations installed at cavity areas show an abrupt change of polarization characteristics but not on the other stations. Seismic waves propagating through the cavity are characterized by the attenuation of high frequency waves and predominantly low frequency seismic waves after the S wave arrivals.

• Tunnel and Underground Space
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• v.10 no.1
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• pp.59-69
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• 2000

Acoustic emission is n burst of microseismic waves generated by microscopic failure due to deformation in materials. The study on the detection of initiation and propagation of microcracks from acoustic emission measurement is very important for the evaluation of the stability of underground rock structures by the nondestructive letting method. In this study, acoustic emission was measured under uniaxial stiffness loading test used to obtain the complete stress-strain curves of marble and concrete used as reinforced materials of rock structures. The analysis of acoustic emission parameters and source location were performed to discuss the characteristics of the deformation and failure behavior of rock and concrete. And acoustic emission was measured under cyclic loading test to verify the Kaiser effect associated with the damage of materials, in situ stress of rock, and stress history of concrete structure.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.65-70
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• 2005

A low resistivity zone is found in many places such as a fractured fault zone, weathered zone and aquifer. The electrical resistivity is influenced mainly by pore fluid as well as the clay mineral types and contents, Hence, it is very important to understand the relationship between the electrical resistivity and clay contents associated with the low resistivity zone for geotechnical applications such as civil engineering. This study examines the characteristics of clay mineral types and contents to electrical resistivity through sample measurements, and proposes an expression relating the resistivity and clay content. The electrical resistivity is measured for an artificial agar specimen with clay minerals instead of a natural rock. The clay minerals used are Kaolinite and Montmorillonite. Montmorillonite shows remarkably lower resistivity than Kaolinite, although its clay content is fewer than that of Kaolinite. Also, the proposed expression shows a good correlation coefficient as high as 0.89 or more in all clay minerals.

• Journal of the Korean Society of Safety
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• v.34 no.6
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• pp.50-57
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• 2019

In this study, various types of deep learning models that have been proposed recently are classified according to data input / output types and analyzed to find the deep learning model suitable for constructing a crack detection model. First the deep learning models are classified into image classification model, object segmentation model, object detection model, and instance segmentation model. ResNet-101, DeepLab V2, Faster R-CNN, and Mask R-CNN were selected as representative deep learning model of each type. For the comparison, ResNet-101 was implemented for all the types of deep learning model as a backbone network which serves as a main feature extractor. The four types of deep learning models were trained with 500 crack images taken from real concrete structures and collected from the Internet. The four types of deep learning models showed high accuracy above 94% during the training. Comparative evaluation was conducted using 40 images taken from real concrete structures. The performance of each type of deep learning model was measured using precision and recall. In the experimental result, Mask R-CNN, an instance segmentation deep learning model showed the highest precision and recall on crack detection. Qualitative analysis also shows that Mask R-CNN could detect crack shapes most similarly to the real crack shapes.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.18-25
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• 2021

In many developed countries, such as South Korea, efficiently maintaining the aging infrastructures is an important issue. Currently, inspectors visually inspect the infrastructure for maintenance needs, but this method is inefficient due to its high costs, long logistic times, and hazards to the inspectors. Thus, in this paper, a novel crack inspection approach for concrete bridges is proposed using integrated image processing techniques. The proposed approach consists of four steps: (1) training a deep learning model to automatically detect cracks on concrete bridges, (2) acquiring in-situ images using a drone, (3) generating orthomosaic images based on 3D modeling, and (4) detecting cracks on the orthmosaic image using the trained deep learning model. Cascade Mask R-CNN, a state-of-the-art instance segmentation deep learning model, was trained with 3235 crack images that included 2415 hard negative images. We selected the Tancheon overpass, located in Seoul, South Korea, as a testbed for the proposed approach, and we captured images of pier 34-37 and slab 34-36 using a commercial drone. Agisoft Metashape was utilized as a 3D model generation program to generate an orthomosaic of the captured images. We applied the proposed approach to four orthomosaic images that displayed the front, back, left, and right sides of pier 37. Using pixel-level precision referencing visual inspection of the captured images, we evaluated the trained Cascade Mask R-CNN's crack detection performance. At the coping of the front side of pier 37, the model obtained its best precision: 94.34%. It achieved an average precision of 72.93% for the orthomosaics of the four sides of the pier. The test results show that this proposed approach for crack detection can be a suitable alternative to the conventional visual inspection method.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.245-253
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• 2021

RC slab bridges account for the largest portion of deteriorated bridges in Korea. However, most RC slabs are not included in the first and second classes of bridges, which are subject to bridge safety management and maintenance. The highest damaged components in highway bridges are the subsidiary facilities including expansion joints and bearings. In particular, leakage through expansion joints causes deterioration and cracks of concrete and exposure of reinforced bars. Therefore, this study analyzed the effect of adhesion damage at expansion joints on the response of the deck in RC slab bridges. When the spacing between the expansion joints at both ends was closely adhered, cracks occurred in the concrete at both ends of the deck due to the resistance rigidity at the expansion joints. Based on the response results, the correlation analysis between displacements in the longitudinal direction of the expansion joint and concrete stress at both ends of the deck for each damage scenario was performed to investigate the effect of the occurrence of damage on the bridge behavior. When expansion joint devices at both sides were damaged, the correlation between displacement and stress showed a low correlation of 0.18 when the vehicles proceeded along all the lanes. Compared with those in the intact state, the deflections of the deck in the damaged case at both sides showed a low correlation of 0.34 to 0.53 while the vehicle passed and 0.17 to 0.43 after the vehicle passed. This means that the occurrence of cracks in the ends of concrete changed the behavior of the deck. Therefore, data-deriven damage detection could be developed to manage the damage to expansion joints that cause damage and deterioration of the deck.

• Journal of the Microelectronics and Packaging Society
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• v.16 no.2
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• pp.33-42
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• 2009

A polymer-based flexible neural probe was fabricated for monitoring of neural activities from a brain. To improve the insertion stiffness, a 5 ${\mu}m$ thick biocompatible Au layer was electroplated between the top and bottom polymer layers. The developed neural probe penetrated a gel whose elastic modulus is similar to that of a live brain tissue without any fracture, To minimize mechanical residual stress and bending from the probe, two new methods were employed: (1) use of a thermal annealing process after completing the device and (2) incorporation of multiple different layers to compensate the residual stress between top and bottom layers. Mechanical bending around the probe tip was clearly removed after employing the two processes. In electrical test, the developed probe showed a proper impedance value to record neural signals from a brain and the result remained the same for 72 hours. In simple in-vitro probe characterization, the probe showed a great removal of residual stress and an excellent recording performance. The in-vitro recording results did not change even after 1 week, suggesting that this electrode has the potential for great recording from neuron firing and long-term implant performance.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.78-85
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• 2005

This study, combining geophysical and environmental approaches, was undertaken to investigate the causes of secondary salinity in the Goondoola basin, in southwestern Queensland. Airborne radiometric, electromagnetic and ground electromagnetic datasets were acquired, along with data on soils and subsurface materials and groundwater. Relationships established between radiometric, elevation data, and measured material properties allowed us to generate predictive maps of surface materials and recharge potential. Greatest recharge to the groundwater is predicted to occur on the weathered bedrock rises surrounding the basin. Electromagnetic data (airborne, ground, and downhote), used in conjunction with soil and drillhole measurements, were used to quantify regolith salt store and to define the subsurface architecture. Conductivity measurements reflect soil salt distribution. However, deeper in the regolith, where the salt content is relatively constant, the AEM signal is influenced by changes in porosity or material type. This allowed the lateral distribution of bedrock weathering zones to be mapped. Salinisation in this area occurs because of local-andintermediate-scale processes, controlled strongly by regolith architecture. The present surface outbreak is the result of evaporative concentration above shallow saline groundwater, discharging at break of slope. The integration of surficial and subsurface datasets allowed the identification of similar landscape settings that are most at risk of developing salinity with groundwater rise. This information is now being used by local land managers to refine management choices that prevent excess recharge and further salt mobilisation.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.509-523
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• 2023

The high-level nuclear waste (HLW) repository is exposed to complex environmental conditions consisting of high temperature, high humidity, and radiation, resulting in structural deterioration. Therefore, structural health monitoring is essential, and piezo sensors are used to detect cracks and estimate strength. However, since the monitoring sensors installed in the disposal tunnel and disposal container cannot be replaced or removed, the quantitative life of the monitoring sensor and its suitability must be assessed. In this study, the life of a piezo sensor for monitoring was assessed using an accelerated life test (ALT). The failure mode and mechanism of the piezo sensor under high temperature conditions were determined, and temperature stress's influence on the piezo sensor's life was analyzed. ALT was conducted on temperature stress and the relationship between temperature stress and piezo sensor life was suggested. The life of the piezo sensor was assessed using the Weibull probability distribution and the Arrhenius acceleration model. The suggested relationship can be used in multiple stress ALT designs for more precise life assessment.