• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.772-781
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• 2020

A direct shear member resists external forces through the shear transfer of reinforcing bars placed at the concrete interface. The current concrete structural design code uses empirical formulas based on the shear friction analogy, which is applied to the horizontal shear of concrete composite beams. However, in the case of a member with a large amount of reinforcing bars, the shear strength obtained through the empirical formula is lower than the measured value. In this paper, the limit state of newly constructed composite beams on an existing concrete girder is defined using stress field theory, and material constitutive laws are applied to gain horizontal shear strength while considering the tension-stiffening and softening effects of concrete struts. A simplified method of calculating the shear strength is proposed, which was validated by comparing it with the related design code provisions. As a result, it was confirmed that the method generally shows a similar tendency to the experimental results when the shear reinforcing bar yields, unlike the regulations of the design code, where differences in the predicted value of shear strength occur according to the shear reinforcement ratio.

• Journal of the Korean Geotechnical Society
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• v.22 no.11
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• pp.55-64
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• 2006

It is very Important to predict the damage zone of a rock mass induced by blasting for the excavation of an underground cavity such as a tunnel, as the damage zones incur mechanical and hydraulic instability of the rock mass potentially. Complicated blasting processes that can hinder the proper characterization of the damage zone can be effectively represented by two loading mechanisms. The first mechanism is the dynamic impulsive load-generating stress waves that radiate outwards immediately after detonation. This load creates a crushed annulus along with cracks around the blasthole. The second is the gas pressure that remains for an extended time after detonation. As the gas pressure reopens some arrested cracks and extends these, it contributes to the final structure of the damage zone induced by the blasting. This paper presents a simple method to evaluate the damage zone induced by gas pressure during rock blasting. The damage zone is characterized by analyzing crack propagations from the blasthole. To do this, a model of a blasthole with a number of radial cracks that are equal in length in a homogeneous infinite elastic plane is considered. In this model, crack propagation is simulated through the use of only two conditions: a crack propagation criterion and the mass conservation of the gas. The results show that the stress intensity factor of a crack decreases as the crack propagates from the blasthole, which determines the crack length. In addition, it was found that the blasthole pressure continues to decrease during crack propagation.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.261-272
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• 2023

In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.1-8
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• 2024

Persistent droughts due to climate change will intensify water shortage problems in Korea. According to the 1st National Water Management Plan, the shortage of domestic and industrial waters is projected to be 0.07 billion m³/year under a 50-year drought event. A long-term prediction of water demand is essential for effectively responding to water shortage problems. Unlike industrial water, which has a relatively constant monthly usage, domestic water is analyzed on monthly basis due to apparent monthly usage patterns. We analyzed monthly water usage patterns using water usage data from 2017 to 2021 in Chungcheong, South Korea. The monthly water usage rate was calculated by dividing monthly water usage by annual water usage. We also calculated the water distribution rate considering correlations between water usage rate and climate variables. The division method that divided the monthly water usage rate by monthly average temperature resulted in the smallest absolute error. Using the division method with average temperature, we calculated the water distribution rates for the Chungcheong region. Then we predicted future water usage rates in the Chungcheong region by multiplying the average temperature of the SSP5-8.5 scenario and the water distribution rate. As a result, the average of the maximum water usage rate increased from 1.16 to 1.29 and the average of the minimum water usage rate decreased from 0.86 to 0.84, and the first quartile decreased from 0.95 to 0.93 and the third quartile increased from 1.04 to 1.06. Therefore, it is expected that the variability in monthly water usage rates will increase in the future.

• Land and Housing Review
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• v.10 no.3
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• pp.43-55
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• 2019

The purpose of this study is to derive indicators and development directions to be considered when planning new towns in the Seoul metropolitan area as new towns are planned to be built. To this end, the following implications were derived after analyzing the survey data of experts in each field using Frequency Analysis and Analysis of Variance(ANOVA) technique. First, the assessment results of the existing first and second phase new towns showed that there were many negative assessments of citizen participation and information sharing, smart technologies and services, social and cultural diversity and inclusion. Regarding the third phase new town, experts said that the most important indicators are accessibility and convenience of transportation, environmental comfort, quality and service of residence. In addition, experts cited the superiority of landscape/design, jobs/self-sufficiency and social/cultural diversity as important indicators. Second, after examining whether the perceptions and assessments of experts differ depending on individual characteristics such as gender, age, occupation, and professional field, the first and second phase new towns showed significant differences only in "gender", and the third phase new town had significant differences in "gender" and "professional field". Third, experts thought that changes in population structure, industry and jobs, quality of life and diversity, environment and climate change, and social and residential welfare should be considered important in the planning of third phase new town. In addition, experts considered expanding park and self-sufficient land as important in the land use plan, and ranked eco-city as a desirable type of the city, and public transportation facilities, park areas and education facilities as the most important living infrastructure.

• Journal of the Korea Organic Resources Recycling Association
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• v.29 no.3
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• pp.5-16
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• 2021

In this study, the applicability of the MBR(Membrane Bio Reactor) process of oxygen dissolve was evaluated through comparison and evaluation of the efficiency of oxygen dissolve device and conventional aeration device in the explosive tank within the MBR process. The organic matter and ammonia oxidation by oxygen dissolve device were evaluated, and the efficiency of persaturation was evaluated by applying real waste water (anaerobic digester effluent treatement from food waste). SCOD and ammonia removal rates for oxygen dissolve device and conventional aeration device methods were similar. However, it was determined that the excess sludge treatment cost could be reduced as the yield of microorganisms by oxygen dissolve device is about 0.03 g MLSS-produced/g SCOD-removed lower than that of microorganisms by conventional aeration device. The removal rates of high concentrations of organic matter (4,000 mg/L) and ammonia (1,400 mg/L) in anaerobic digester effluent treatment from food waste were compared to the conventional aeration device and the oxygen dissolve device organic matter removal rate was approximately 13% higher than that of the conventional aeration device. In addition, for MLSS, the conventional aeration device was 0.3 times higher than for oxygen dissolve device. This is believed to be due to the high progress of sludge autooxidation because the dissolved oxygen is sufficiently maintained and supplied in the explosive tank for oxygen dissolve device. Therefore, it was determined that the use of oxygen dissolve device will be more economical than conventional aeration device as a way to treat wastewater containing high concentrations of organic matter.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.1-12
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• 2018

Heat waves during summer cause a qualitative degradation in urban environments and increases the number of patients who suffer from heat-related illnesses, and the urbanization deepens these problems. It is a prerequisite to analyze the current status accurately in order to assess the urban heat island phenomenon. Thus, this study aims to collect weather measurements information at the occurrence of a severe heat wave in Seoul, thereby allowing analysis of information, which will also consider the land use type. The weather measurement information used in the analysis had an advantage, as the gap between measured locations is considerably shorter than before due to the miniaturization of the automatic weather systems (AWS), which are connected through the communication network. Based on the above collected information, a temporal change in the data due to land use type was analyzed. As a result, the difference in temperature change in response to the land use type could be compared, as could the occurrence pattern of the tropical night phenomenon, and the effect on temperature reduction in green belt areas could be identified through the comparison of the intensity of heat island by time and land use. The methods and results derived in this study through the comparative analysis in terms of time and land use, weather information measurements, and mapping can be utilized as foundational data that can be referred to in urban planning to reduce the heat island phenomenon in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.577-584
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• 2021

Electrical energy is an essential component in present societies, which is an important basis for our technological society. In the design of new power infrastructure, it is important to consider the psychological aspects of how our culture considers and aspects its development as an integral component of the community environment. The construction of new high voltage overhead transmission lines has become a controversial issue for public policy of government due to social opposition. The members of community are concerned about how these power lines may have an impact on their lives, basically caused by their effects on health and safety. The landscape and visual impact is one of the most impact that can be easily perceived for local community. The computer 3D simulation of new landscape is illustrated by a real life use corresponding to the selection of the power line route with least observability for local community. This paper used ArcGIS(geographic information system tool) for planning, survey, basic route and detailed route, route for implementation of transmission line corridor. Also, the paper showed the map of natural environment, living environment, safety and altitude using database of power line corridor, and transmission siting model was developed by this study. The suggested landscape of computer simulation with lowest visibility on a power line zone can contribute to reducing oppositions of local community and accelerating the construction of new power lines.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.315-324
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• 2022

The experimental data obtained in a wave flume were analyzed using machine learning techniques to establish a model that predicts the input wave height of the wavemaker based on the waves that have experienced wave shoaling and to verify the performance of the established model. For this purpose, artificial neural network (NN), the most representative machine learning technique, and Gaussian process regression (GPR), one of the non-parametric regression analysis methods, were applied respectively. Then, the predictive performance of the two models was compared. The analysis was performed independently for the case of using all the data at once and for the case by classifying the data with a criterion related to the occurrence of wave breaking. When the data were not classified, the error between the input wave height at the wavemaker and the measured value was relatively large for both the NN and GPR models. On the other hand, if the data were divided into non-breaking and breaking conditions, the accuracy of predicting the input wave height was greatly improved. Among the two models, the overall performance of the GPR model was better than that of the NN model.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.391-393
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• 2022

In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.