• Journal of the Korean GEO-environmental Society
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• v.12 no.10
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• pp.83-90
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• 2011

A series of centrifugal model test was conducted to investigate the distribution of vertical earth pressure on circular ductile underground corrugated steel plate waterway culvert with considering the compaction degree of the backfill in the high landfilled embankment section. The compaction degree of backfill was varied to 80, 85, 90, and 95% at the 53g-level gravity considering the similarity of the site. As a result of this test, the load reduction factor by the arching effect of the top of corrugated steel plate showing ductile behavior nearly agreed with the load reduction factor according to the compaction degree of backfill specified in the AISI(2002) design method. The vertical earth pressure measured at the top of the corrugated steel plate was linearly decreased as the compaction degree increased. The greater the compaction degree of backfill was, the greater the reduction of surface loading on the top of the corrugated steel plate by arching effect. The load decreased by arching effect on top of the corrugated steel plate was transferred to the side backfill of the corrugated steel plate(EP 1) and the outside of backfill(EP 3).

• Journal of Korean Society on Water Environment
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• v.27 no.2
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• pp.200-209
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• 2011

The purpose of the study is to optimally manage sewage treatment plant with analysis of phosphorus contribution and improvement of water quality contributing rate in the effect of inflowing point of effluent and Pal-Dang lake after reducing T-P discharge from large scale public sewage treatment plant at upstream of Pal-Dang lake. Also, this study, for enforcement of T-P in effluent, plans optimal management of effluent T-P through examining propriety of environmental, technological, and economical aspect such as water quality standard of domestic and foreign T-P and related policy. In regarding optimal management of T-P discharged from public sewage treatment plant located in upstream of Pal-Dang lake, the study drew following conclusions. With the optimal management of public sewage treatment plant, it showed that a pollution level became higher in the order of Sumgang E in South-Han river, C in Dalcheon, B1 B2, A in North-Han river, and J in Kyungancheon, and it is required reduction of T-P first. The highest value in analysis of benefit-costs from sewage treatment plant in the selected research area was Kyungan B, and the others are with the order of Jojong A, Bokha A, Kyungan A, and Yanghwa A. With result of this study, all 14 areas are required more enforced phosphorus treatment. The study resulted that the most top priority areas were Hangang F, Sumgang B, and Gyungan A, top priority areas were Bokha A, Dalcheon B, and Cheongmi A, priority areas were Hangang E, Heukcheon A, Gyungan B, and Jojong A, and potential areas were Sumgang A, Yanghwa A, Dalcheon A, and Hangang D. It seems to be appropriate to apply 0.2 mg/L of T-P treatment for water supply source reservation, 0.5 mg/L for the other areas by locally, and 0.2~0.5 mg/L for biological nitrogen phosphorus treatment method and 0.5~1 mg/L for Conventional Activated Sludge by technologically. Also, it may be appropriate to apply 0.2 mg/L for the most top priority area(I), 0.3 mg/L for the top priority area(II), 0.4 mg/L for priority area(III), and 0.5 mg/L for potential area(IV) by the separation of priority area.

• Journal of the Korean Geotechnical Society
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• v.38 no.4
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• pp.59-70
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• 2022

There is a growing interest in evaluating earthquake damage and determining disaster prevention measures due to the magnitude 5.8 earthquake in Pohang, Korea. Since the liquefaction phenomena occurred extensively in the residential area as a result of the earthquake, there was a demand for research on liquefaction phenomenon evaluation and liquefaction disaster prediction. Liquefaction is defined as a phenomenon where the strength of the ground is completely lost due to a sudden increase in excess pore water pressure caused due to large dynamic stress, such as an earthquake, acting on loose sand particles in a short period of time. The liquefaction potential index, which can identify the occurrence of liquefaction and predict the risk of liquefaction in a targeted area, can be used to create a liquefaction hazard map. However, since liquefaction assessment using existing field testing is predicated on a single borehole liquefaction assessment, there has been a representative issue for the whole targeted area. Spatial interpolation and geographic information systems can help to solve this issue to some extent. Therefore, in order to solve the representative problem of geotechnical information, this research uses the kriging method, one of the geostatistical spatial interpolation techniques, and constructs a geotechnical information database for liquefaction and spatial interpolation. Additionally, the liquefaction hazard map was created for each return period using the constructed geotechnical information database. Cross validation was used to confirm the accuracy of this liquefaction hazard map.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.515-529
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• 2022

Identifying the available water resources amount is an essential process in establishing a sustainable water resources management plan. Dam facility is a major infrastructure storing and supplying water during the dry season, and the water supply yield of the dam varies depending on dam inflow conditions or operation rule. In South Korea, water supply yield of dam is calculated by reservoir simulation based on observed historical dam inflow data. However, the water supply capacity of a dam can be underestimated or overestimated depending on the existence of historical drought events during the simulation period. In this study, probabilistic inflow data was generated and used to estimate the appropriate range of the water supply yield of hydropower dams. That is, a method for estimating the probabilistic dam inflow that fluctuates according to climatic and socio-economic conditions and the range of water supply yield for hydropower dams was presented, and applied to hydropower dams located in the Han river in South Korea. It is expected that the understanding water supply yield of the hydropower dams will become more important to respond to climate change in the future, and this study will contribute to national water resources management planning by providing potential range of water supply yield of hydropower dams.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.617-626
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• 2022

In Korea, annual precipitation and its variability have gradually increased since modern meteorological observations began, and the risk of disasters has also been increasing due to significant regional variations and recent abnormal climate conditions. Given that damage from storms and floods mainly occurs around rivers, it is crucial to determine the appropriate design frequency for river-related projects. This study examined existing design practices used to determine hydrological design frequencies and suggested a new method to determine appropriate design frequencies. The study collected available data pertaining to seven evaluation factors, specifically the basin areas, shape parameters, channel slopes, stream orders, backwater effect reaches, extreme rainfall frequencies, and urbanized flood inundation areasfor 413 local rivers in Chungcheongnam-do in Korea. The estimated weights for areas of extreme rainfall frequencies and urbanized flood inundation were found to be 18, having a great effect on determining the design frequency. Compared with the established design frequency in previous government reports, the estimated design frequency increased for 255 rivers and decreased for 158 rivers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.117-126
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• 2022

Currently, the number of bridge structures in Korea is continuously increasing and enlarged, and the number of old bridges that have been in service for more than 30 years is also steadily increasing. Bridge aging is being treated as a serious social problem not only in Korea but also around the world, and the existing manpower-centered inspection method is revealing its limitations. Recently, various bridge damage detection studies using deep learning-based image processing algorithms have been conducted, but due to the limitations of the bridge damage data set, most of the bridge damage detection studies are mainly limited to one type of crack, which is also based on a close set classification model. As a detection method, when applied to an actual bridge image, a serious misrecognition problem may occur due to input images of an unknown class such as a background or other objects. In this study, five types of bridge damage including crack were defined and a data set was built, trained as a deep learning model, and an open set recognition-based bridge multiple damage recognition model applied with OpenMax algorithm was constructed. And after performing classification and recognition performance evaluation on the open set including untrained images, the results were analyzed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.127-134
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• 2022

Recently, policies and research to prevent increasing construction accidents have been actively conducted in the domestic construction industry. In previous studies, the prediction model developed to prevent construction accidents mainly used only structured data, so various characteristics of construction sites are not sufficiently considered. Therefore, in this study, we developed a machine learning-based construction accident prediction model that enables the characteristics of construction sites to be considered sufficiently by using both structured and text-type unstructured data. In this study, 6,826 cases of construction accident data were collected from the Construction Safety Management Integrated Information (CSI) for machine learning. The Decision forest algorithm and the BERT language model were used to train structured and unstructured data respectively. As a result of analysis using both types of data, it was confirmed that the prediction accuracy was 95.41 %, which is improved by about 20 % compared to the case of using only structured data. Conclusively, the performance of the predictive model was effectively improved by using the unstructured data together, and construction accidents can be expected to be reduced through more accurate prediction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.427-438
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• 2022

With the recent growing importance over safety management the need for advanced and technical approaches for on-site safety inspection methods has increased. Railway construction is subject to its own particular set of temporal and spatial challenges due to its unique facilities and equipment. This study aimed to investigate the field characteristics of railway infrastructure and improve the conventional field safety management methods by identifying the most appropriate features of AR technology. Group interviews and surveys were conducted with field safety experts to derive the major problems and inspection needs. Subsequently, various features of AR, such as BIM model projection, and remote conferencing, were investigated to determine their applicability to address safety issues. As a result, four problems in the current safety management process, such as 'lack of time due to the conventional inspection method and inspection of areas that are difficult to access', and three major inspection types, such as 'observance of work procedures, status of installation, adequate dimensional spacing', were identified to be improved when adopting AR based techniques. Furthermore, AR technology utilizing plans to solve safety inspection problems and effectively manage major inspection types were proposed, and a follow up survey was conducted with the same field safety experts to derive the priority of technology development.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.869-877
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• 2022

This study aims to analyze the factors affecting the re-subscription period upon initial termination of the reverse mortgage subscription. The study utilized the Korea Housing Finance Corporation's database to extract the information regarding re-subscribers of the reverse mortgage from July 2007 to June 2021. The ordered logit model was employed and found that a set of user (subscriber) characteristics are influential towards the re-subscription period. Among the individual characteristics, changes in age group, marital status from married to single-living, maintaining single-living, and the initial subscription period were found statistically significant, highlighting that the increase in the initial subscription period decreased the re-subscription period. Among the housing (home equity) characteristics, changes in housing price and ownership type (single and partial ownership) were statistically significant, indicating that the change in ownership type decreases the re-subscription period. Lastly, the variables related to loan terms were found significant, revealing that changes in payout method and schedule were both increasing factors of the re-subscription period. Based on the findings, necessary policy implications can be considered to secure the returning subscribers of the reverse mortgage effectively.