• Ecology and Resilient Infrastructure
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• v.7 no.2
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• pp.90-96
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• 2020

Recently, a method that applies laser scanning (LS) that acquires vegetation information such as the vegetation habitat area and the size of vegetation in a point cloud format has been proposed. When LS is used to investigate the physical shape of vegetation, it has the advantage of more accurate and rapid information acquisition. However, to examine uncertainties that may arise during measurement or post-processing, the process of adjusting the data by the actual data is necessary. Therefore, in this study, the physical structure of stems, branches, and leaves of woody vegetation in an artificially formed river channel was manually investigated. The obtained results then compared with the information acquired using the three-dimensional terrestrial laser scanning (3D TLS) method, which repeatedly scanned the target vegetation in various directions to obtain relevant information with improved precision. The analysis demonstrated a negligible difference between the measurements for the diameters of vegetation and the length of stems; however, in the case of branch length measurement, a relatively more significant difference was observed. It is because the implementation of point cloud information limits the precise differentiation between branches and leaves in the canopy area.

• Ecology and Resilient Infrastructure
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• v.1 no.2
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• pp.68-81
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• 2014

In this study, the numerical simulation regarding the process and characteristics of topography change due to the vegetation recruitment and growth was carried out by adding the vegetation growth model to two-dimensional flow and sediment transport models. The vegetation introduction and recruitment on the condition for developing an alternate bar reduced the bar migration. The vegetated area and channel width changes were more significantly influenced by changes in upstream discharge rather than the duration of low flow. When the upstream discharge decreased, the vegetation area increased and the channel width decreased. The vegetation introduction and recruitment on the condition for developing a braided channel significantly influenced the characteristics of topography changes. In the braided channel, vegetation reduced the braided index, and when the upstream discharge decreased significantly, the channel topography was changed from the braided channel to the single channel. The vegetation area decreased as the upstream discharge increased. The channel width decreased significantly after the vegetation was introduced and it also decreased as the upstream discharge decreased. It was confirmed through the numerical simulation that a decrease in flood discharge accelerated the vegetation introduction and recruitment in the channel and this allowed to confirm its influence on the characteristics of topography changes qualitatively.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.212-222
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• 2021

In this study, the flow resistance coefficient was calculated considering the physical properties and distribution characteristics of floodplain vegetation, and the effect of floodplain vegetation distribution on flow characteristics was analyzed by reflecting it in a two-dimensional numerical simulation. The three-dimensional point clouds of vegetation acquired using ground lidar were analyzed to apply floodplain vegetation's physical properties to the existing formula for vegetation flow resistance calculation. The floodplain vegetation distribution in the modeling was divided into locally distributed and fully distributed conditions in the floodplain. As a result of the simulation of the study site, the flow resistance coefficient of floodplain vegetation was found to have a value of about five times or more compared to the flow resistance coefficient of the main channel bed when the design flood occurs based on Manning's n coefficient. Also, it affected the hydraulic characteristics in the main channel and floodplain.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.107-118
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• 2022

The social need for stable hydrogen storage technologies that respond to the increasing demand for hydrogen energy is increasing. Among them, underground hydrogen storage is recognized as the most economical and reasonable storage method because of its vast hydrogen storage capacity. In Korea, low-depth hydrogen storage using artificial protective structures is being considered. Further, establishing corresponding safety standards and ground stability evaluation is becoming essential. This study evaluated the hydro-mechanical behavior of the ground during a hydrogen gas leak from a low-depth underground hydrogen storage facility through the HM coupled analysis model. The predictive reliability of the simulation model was verified through benchmark experiments. A parameter study was performed using a metamodel to analyze the sensitivity of factors affecting the surface uplift caused by the upward infiltration of high-pressure hydrogen gas. Accordingly, it was confirmed that the elastic modulus of the ground was the largest. The simulation results are considered to be valuable primary data for evaluating the complex analysis of hydrogen gas explosions as well as hydrogen gas leaks in the future.

• Ecology and Resilient Infrastructure
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• v.9 no.3
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• pp.131-140
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• 2022

The magnitude and frequency of extreme floods are increasing owing to the effects of climate change. Therefore, multipurpose flood management techniques incorporating nature-based solutions have been introduced to mitigate the limitations of flood management and river design methods relying on existing observation data. Nature-based solutions to prepare for such extreme flooding events include ways to retreat the embankment, expand the floodplain, and reduce flood damage. To apply these technologies, adopting appropriate location selection methods based on various evaluation factors, such as flood damage reduction effects, sustainable ecological environments, river connectivity, and physical channel structure enhancements, should be prioritized. Therefore, in this study, the optimal location for implementing the multipurpose floodplain construction project was determined by selecting the location of the floodplain expansion with objectivity in the river waterfront area upstream of Daecheong Dam to downstream of Yongdam Dam. Through the final location determination, the Dongdaeje and Jeogokje sections were included in the optimal location considering both flood damage reduction and water environment improvement.

• Journal of the Korean Geotechnical Society
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• v.39 no.7
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• pp.69-76
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• 2023

Cavity causes settlement and its remediation after an accident results in significant time and economic losses. This study aims to experimentally evaluate the prospect of using infrared camera to detect and measure underground subsidence. Emissivity is necessary to detect the energy emitted from an object and accurately assess temperature using an infrared camera. The emissivity in laboratory tests is fixed to evaluate a reasonable distance between the infrared camera and the object, and temperature values are assessed at various distances. In field experiments, the cavity of the field experiment is simulated using a PVC pipe with a diameter of 5 cm, artificially buried at depths of 5 and 25 cm from the surface. The infrared camera measurements are taken from 4 PM to 3 PM of the next day (a total of 23 h). The analysis included the time-series temperature distribution and the cooling rate index assessment, which represents the temperature change rate per unit of time. The results showed that various temperature trends are observed depending on the location of the subsidence. This study demonstrates that the infrared camera can be used to assess the condition of the subsurface.

• Journal of the Korean Geotechnical Society
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• v.39 no.10
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• pp.41-48
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• 2023

The presence of abnormalities in the subgrade of roads poses safety risks to users and results in significant maintenance costs. In this study, we aimed to experimentally evaluate the temperature distributions in abnormal areas of subgrade materials using infrared cameras and analyze the data with machine learning techniques. The experimental site was configured as a cubic shape measuring 50 cm in width, length, and depth, with abnormal areas designated for water and air. Concrete blocks covered the upper part of the site to simulate the pavement layer. Temperature distribution was monitored over 23 h, from 4 PM to 3 PM the following day, resulting in image data and numerical temperature values extracted from the middle of the abnormal area. The temperature difference between the maximum and minimum values measured 34.8℃ for water, 34.2℃ for air, and 28.6℃ for the original subgrade. To classify conditions in the measured images, we employed the image analysis method of a convolutional neural network (CNN), utilizing ResNet-101 and SqueezeNet networks. The classification accuracies of ResNet-101 for water, air, and the original subgrade were 70%, 50%, and 80%, respectively. SqueezeNet achieved classification accuracies of 60% for water, 30% for air, and 70% for the original subgrade. This study highlights the effectiveness of CNN algorithms in analyzing subgrade properties and predicting subsurface conditions.

• Journal of the Korean Geotechnical Society
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• v.39 no.12
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• pp.115-125
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• 2023

In this study, we evaluated the behavior of frozen soil using an electrical resistivity survey method-a nondestructive technique-and examined its characteristics through field experiments. Frozen soil was artificially prepared by injecting fluid to accelerate the freezing process, and naturally frozen soil was selected in a nearby area for comparison. A dynamic cone penetration test (DCPT) was performed to compare the reliability of the electrical resistivity survey, and time-domain reflectometry surveys were performed to assess the moisture content of the ground. Field experiments were conducted in February-when the atmosphere temperature was below freezing-and May-when the temperature was above freezing. This temperature-compensated method was used to determine reliability because the behavior of frozen soil depends on the underlying temperature. In the resistivity survey method, a section of high electrical resistivity was observed under freezing conditions due to the frozen water and converted into porosity. The converted porosity was compared with the porosity inferred from the DCPT, and the results showed that the measured electrical resistivity was valid.

• Journal of the Korean Geotechnical Society
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• v.39 no.12
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• pp.37-46
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• 2023

Dynamic soil properties are essential factors for predicting the detailed behavior of the ground. However, there are limitations to gathering soil samples and performing additional experiments. In this study, we used an artificial neural network (ANN) to predict dynamic soil properties based on static soil properties. The selected static soil properties were soil cohesion, internal friction angle, porosity, specific gravity, and uniaxial compressive strength, whereas the compressional and shear wave velocities were determined for the dynamic soil properties. The Levenberg-Marquardt and Bayesian regularization methods were used to enhance the reliability of the ANN results, and the reliability associated with each optimization method was compared. The accuracy of the ANN model was represented by the coefficient of determination, which was greater than 0.9 in the training and testing phases, indicating that the proposed ANN model exhibits high reliability. Further, the reliability of the output values was verified with new input data, and the results showed high accuracy.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.77-84
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• 2024

Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.