• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.4
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• pp.389-394
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• 2019

In this study, a functional inorganic insulation as TiO₂ and inorganic wet fly ash were used to evaluate the physical performance and thermal environment of an exterior finish that can improve the thermal environment of a building. The performance evaluation of the finish was based on the KS F 4715 thin coating material and the thermal environment. When TiO₂ was added, the physical performance was lowered at 10% or more, and the inorganic wet-treated fly ash increased the physical performance by 10%. In the thermal environmental evaluation, the surface temperature reduction effect of the inorganic wet-treated fly ash was low, but when used in combination with TiO₂, it was effective to reduce the surface temperature and the internal temperature. As a result, the optimum combination of TiO₂ and inorganic wet-treated fly ash for thermal environment control was found to be optimal when 5% of each mixture was used.

• Journal of Christian Education in Korea
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• v.71
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• pp.155-179
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• 2022

This study aims to apply Hannah Arendt's concept of 'collective responsibility' to the Christian education on environmental issues around the world, focusing on climate change. This study prepares the concept of 'collective responsibility' and the concept of 'collective guilt' and emphasizes the fact that the current climate change problem should be seen as a political task rather than a task of personal ethics. According to Arendt's theory, Christian education activities applying 'collective responsibility' for climate change can become action. This study has four suggestions for Christian learning to understand and recognize climate change. First, presenting and justifying the anxiety and anger toward climate change in the classroom. Second, transcending self-interest (egocentrism) through "Common Sense (enlarged mentality)" in Kantian terms. Third, building education communities through 'citizen participatory education,' running communication, and conversation. Fourth, encouraging experience and practice in every education community with "faith expressing itself through love (Gal 5:6)." Then, to be sure, this refers to not only love of neighbor in Christianity but also political friendship (philia politikē). The academic significance of this study is that it is the first interdisciplinary research paper in Korea which dealt with Arendt's political theory in relation to Christian education. Although it claims to be a theoretical work that applies Arendt's political theory from a systematic theological perspective to Christian education, the author is proud that it is accompanied by practical elements that can be actualized in the education field.

• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.24-35
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• 2022

For water quality management, it is necessary to continuously improve the forecasting by analyzing the past water quality, and a Data-driven model is emerging as an alternative. Because the Data-driven model is built based on a wide range of data, it is essential to apply the correlation analysis method for the combination of input variables to obtain more reliable results. In this study, the Gamma Test was applied as a preceding step to build a faster and more accurate data-driven water quality prediction model. First, a physical-based model (HSPF, EFDC) was operated to produce daily water quality reflecting the complexity of the watershed according to various hydrological conditions for Paldang Dam. The Gamma Test was performed on the water quality at the water quality prediction site (Paldangdam2) and major rivers flowing into the Paldang Dam, and the method of selecting the optimal input data combination was presented through the analysis results (Gamma, Gradient, Standar Error, V-Ratio). As a result of the study, the selection criteria for a more efficient combination of input data that can save time by omitting trial and error when building a data-driven model are presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.255-258
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• 2022

As environmental pollution continues, attention on renewable energy is on the constant rise in recent days. Although various kinds of renewable energy such as solar, wind power and biomass energy have been generated in Jeju, opening and analyzing cases on related data seem insufficient. Therefore, this study is being conducted to deduce the variables which have high relation with solar panel&s output and to understand machine learning methods that can be applied to solar power generation data by utilizing Kaggle platform, which is actively used by a number of scientists. Then, it is planned to propose a form of solar power generation dataset by researching machine learning methods that could be applied to the data. To be specific, analyzing solar power generation data with the Kaggle platform, this study will provide complements on gathering solar power data in Jeju. This study is anticipated to be utilized on data analysis for developing the solar power industry in Jeju. That is, this study is expected to reveal the room for improvement inherent in existing open datasets in Jeju, so that they could be constructed in a suitable form for machine learning for AI analytics. Through this process, a method to increase efficiency of solar power generation is anticipated to be prepared.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.5
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• pp.1025-1037
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• 2015

Flexible base isolation bearings that separate superstructure from ground have been widely used in the construction field because they make a significant contribution to increasing the fundamental period of the structure, thereby decreasing response acceleration transmitted into the superstructure. However, the established bearing devices installed to uphold the whole building give rise to some problems involved with failure and collapse due to lack of the capacity as modern structures are getting more massive and higher. Therefore, this study suggests new isolation bearings assembled with additional restrainers enabled to reinforcing and recentering, and then evaluates their performance to withstand the seismic load. The superelastic shape memory alloy (SMA) bars are installed into the conventional lead-rubber bearing (LRB) devices in order to provide recentering forces. These new systems are modeled as component spring models for the purpose of conducting nonlinear dynamic analyses with near fault ground motion data. The LRB devices with steel bars are also designed and analyzed to compare their responses with those of new systems. After numerical analyses, ultimate strength, maximum displacement, permanent deformation, and recentering ratio are compared to each model with an aim to investigate which base isolation models are superior. It can be shown that LRB models with superelastic SMA bars are superior to other models compared to each other in terms of seismic resistance and recentering effect.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.545-556
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• 2015

This study is to project the future snowfall and to assess heavy snowfall vulnerable area in South Korea using ground measured snowfall data and RCP climate change scenarios. To identify the present spatio-temporal heavy snowfall distribution pattern of South Korea, the 40 years (1971~2010) snowfall data from 92 weather stations were used. The heavy snowfall days above 20 cm and areas has increased especially since 2000. The future snowfall was projected by HadGEM3-RA RCP 4.5 and 8.5 scenarios using the bias-corrected temperature and snow-water equivalent precipitation of each weather station. The maximum snowfall in baseline period (1984~2013) was 122 cm and the future maximum snow depth was projected 186.1 cm, 172.5 mm and 172.5 cm in 2020s (2011~2040), 2050s (2041~2070) and 2080s (2071~2099) for RCP 4.5 scenario, and 254.4 cm, 161.6 cm and 194.8 cm for RCP 8.5 scenario respectively. To analyze the future heavy snowfall vulnerable area, the present snow load design criteria for greenhouse (cm), cattleshed ($kg/m^2$), and building structure ($kN/m^2$) of each administrative district was applied. The 3 facilities located in present heavy snowfall areas were about two times vulnerable in the future and the areas were also extended.

• Journal of the Korean Regional Science Association
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• v.40 no.2
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• pp.107-130
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• 2024

Urban land surface temperature (LST) change is a major environmental factor that affects the thermal comfort, energy consumption, and health of urban residents. Most studies that explored the relationship between LST and urban built-environment form analyzed only midday LST. This study explores the diurnal variation of summertime LST in Seoul using ECOSTRESS data, which observes LST at various times of the day and analyzes whether the LST variation differs by built environment type. Launched in 2018, ECOSTRESS operates in a non-sun-synchronous orbit, observing LST with a high resolution of 70 meters. This study collected data from early morning (6:25) to evening (17:26) from 2019 to 2022 to build time-series LST. Based on greenery, water bodies, and building form data, eight types of Seoul's built environment were derived by hierarchical clustering, and the LST fluctuation characteristics of each cluster were compared. The results showed that the spatial disparity in LST increased after dawn, peaked at noon, and decreased again, highlighting areas with rapid versus stable LST changes. Low-rise and high-rise compact districts experienced fast, high temperature increases and high variability, while low-density apartments experienced moderate LST increases and low variability. These results suggest urban forms that can mitigate rapid daytime heating.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.5
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• pp.45-55
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• 2015

Currently, extreme weather events such as super typhoon, extreme snowfall, and heat wave are frequently occurring all over the world by natural and human caused factors. After industrial growth in the 1970s, earth's temperature has risen sharply. due to greenhouse effect. Global warming can be attributed to gases emitted from using fossil fuel such as average carbon dioxide, perfluorocarbons, nitrous oxide, and methane. Especially, carbon dioxide has the highest composition of about 90%. in the fossile fuel usage emitted gas. Concrete has excellent durability as a building material climate change. However, due to various of physical and chemical environmental effect such as conditions during its curing process, the performance degradation may occur. Carbon dioxide in the atmosphere causes steel corrosion and durability decreases by lowering the alkalinity of concrete. Therefore, in this study, concrete durability performance with respect to carbonation from curing conditions change due to wind speed and sunshine exposure time. Concrete carbonation experiment are performed. using wind speed (0, 2, 4, 6) m/s and sunlight exposure time (2, 4, 6, 8) hrs. Also, performance based evaluation through the satisfaction curve based on the carbonation depth and carbonation rate test results are performed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.751-760
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• 2021

Most bridges in Korea are over 20 years old, and many problems linked to their deterioration are being reported. The current practice for bridge inspection mainly depends on expert evaluation, which can be subjective. Recent studies have introduced data-driven methods using building information modeling, which can be more efficient and objective, but these methods require manual procedures that consume time and money. To overcome this, this study developed an image-based automaticbridge component classification network to reduce the time and cost required for converting the visual information of bridges to a digital model. The proposed method comprises two convolutional neural networks. The first network estimates the type of the bridge based on the superstructure, and the second network classifies the bridge components. In avalidation test, the proposed system automatically classified the components of 461 bridge images with 96.6 % of accuracy. The proposed approach is expected to contribute toward current bridge maintenance practice.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.611-617
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• 2009

With advanced technologies applied to transportation, realtime traffic information has been necessary for not only drivers but also agencies. In normal, traffic conditions have been represented to three levels according to congestion: "free", "slow", and "jammed". Those categories and criteria are set up for traffic management even though traffic information is provided for drivers. This study examines how drivers feel current congestion levels and delves into traffic categories and criteria which they recognize. To collect data for drivers' recognition, a survey of freeway travellers is conducted answering the question about traffic flow speed from video image on a freeway section. In the result of the survey, the surveyee preferred a 4-level traffic condition including "delayed" to 3-level traffic condition. As its criteria, 20 km/h, 50 km/h, and 75 km/h were obtained. These results are expected to contribute to building more appropriate traffic information for drivers and providing an operational guideline for Traffic Monitering Centers.