• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.434-434
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• 2023

다양한 지면 모형은 대기 강제력 데이터 세트에 의해 구동되며 육지의 물, 에너지 및 생지화학적 순환의 해석에 활용된다. 그 중 에너지 플럭스 교환을 추정하는 것은 극심한 가뭄, 폭염, 물 부족 등 극한 기후 현상에서 중요한 역할을 한다. 에너지 플럭스는 기상기후조건과 토지피복의 변화에 따른 영향을 받고 있는데 그 영향을 구체적으로 조사하는 것은 생태계 프로세스의 매커니즘을 구성하는 데 필수적이다. 본 연구에서는 최신버전인 Community Land Model 버전 5.0 (CLM5)를 이용하여 동북아시아 지역의 에너지 플럭스의 시공간분포를 분석하였다. CLM5의 시뮬레이션은 1991년부터 2010년까지 2.5° × 2.5° 그리드에서 실행되었고 주요 에너지 인자인 순복사량, 현열, 잠열을 모의하였으며, 실행결과는 FLUXNET의 동북아시아 사이트의 관측자료를 이용하여 모델을 검증 및 평가하였다. 대기 강제력 변수의 차이는 모의 결과에 영향을 미치기 때문에 수문인자와 토지피복유형에 따른 에너지 플럭스의 변동성을 분석하였고 잠열을 식생 증발산열과 지면 증발열로 파티션하여 연구지역에 따른 각 구성요소의 비율을 산정하였다. 20년간의 순복사열, 잠열과 온도의 시공간적 변동성의 연 추세를 분석한 결과 동북아시아의 대부분 지역에서 잠열과 온도는 소폭 증가되였고 순복사열은 중국 내륙과 몽골지역에서 감소되였다. 본 연구는 지표와 대기 사이의 에너지 교환에 대해 분석하였으며 이후 증발산 및 물 플럭스와의 연동성과 관계성 분석에 활용하여 기후변화를 이해하는 데 기여할수 있을 것으로 사료된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.91-98
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• 2023

Since risks occurring in construction projects can have a significant impact on schedules and costs, there have been many studies on this topic. However, risk analysis is often limited to only certain construction situations,and experience-dependent decision-making is therefore mainly performed. Data-based analyses have only been partially applied to safety and contract documents. Therefore, in this study, cluster analysis and a Word2Vec algorithm were applied to formal documents that contain important elements for contractors or clients. An initial classification of document content into six types was performed through cluster analysis, and 157 occurrence types were subdivided through application of the Word2Vec algorithm. The derived terms were re-classified into five categories and reviewed as to whether the terms could develop into potential construction risk factors. Identifying potential construction risk factors will be helpful as basic data for process management in the construction industry.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.4
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• pp.568-575
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• 2023

This paper aims to evaluate the quality characteristics and healing performance of precast concrete incorporating self-healing technology as a key technique for the construction of smart cities. The study found that precast concrete mixed with hybrid capsules exhibited a tendency of reduced slump and air content, impacting the quality characteristics. Specifically, the slump decreased by up to 14 %, and the air content by up to 9 %. Moreover, the inclusion of hybrid capsules in the concrete resulted in a maximum decrease of 16 % in compressive strength and 18 % in flexural strength. However, the introduction of hybrid capsules significantly enhanced the crack healing performance. The assessment through water permeability tests showed that the healing rate of 0.3 mm crack width after a 28-day healing period improved as the mixing ratio increased, with the healing rates at 1 %, 3 %, and 5 % hybrid capsule mixtures observed to increase by approximately 16 %, 25 %, and 32 %, respectively.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.130-138
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• 2023

In this study, experimental and analytical studies were conducted on the structural performance of permanent steel formed wide beams in construction stage. Four specimens were fabricated with different rib spacings of the side steel formwork and fixing plate depths, and experimental tests were performed to investigate the effects of variables on the structural performance. Also, an finite element analysis model of the steel permanent formwork wide beam was proposed based on the test results. Using the proposed model, parametric studies were performed with variables including rib spacing of the bottom and side steel formwork, spacing, depth, and thickness of the fixing plate to derive optimized details. Furthermore, an artificial neural network model was developed to easily estimate the deformation of the steel permanent formwork wide beam with various details.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.105-112
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• 2023

Steel fiber reinforced concrete (SFRC) exhibits enhanced strength and superior energy dissipation capacity compared to normal concrete, and it can also reduce crack propagation and fragmentation of concrete even when subjected to blast loads. In this study, the parameters defining failure surface and damage function of the K&C concrete nonlinear model were proposed to be applied for the properties of SFRC in LS-DYNA. Single element analysis has been conducted to validate the proposed parameters in the K&C model, which provided very close simulations on the compressive behavior of SFRC. In addition, blast analysis was performed on SFRC columns with different volume fractions of steel fibers, and the blast resistance of SFRC columns was quantitatively analyzed with Korea Occupational Safety & Health Agency (KOSHA) guidelines.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.109-110
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• 2022

Currently, interest in the quality of concrete is increasing. Among the important factors for evaluating the quality of concrete, interest in unit-water content is also increasing. Currently, the air-meter method, the microwave oven drying method, the capacitance method, and the microwave penetration method are used to measure the unit-water content of concrete.. Among the above methods, except for the microwave method, the measurement method is complicated, portability is reduced, and economic efficiency is reduced. This research aims to measure a unit-water content by using a Frequency Domain Reflectometry(FDR) sensor that is economical, simple to measure, and portable among microwave methods. In addition, it is an experimental study to determine the accuracy of unit-water content using a single input residual model during deep learning to solve the limitations of the FDR sensor.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.29-30
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• 2022

The unit-water content has a very significant effect on the durability of the construction structure and the quality of concrete. Although there are various methods for measuring the unit-water content, there are problems of time required for measurement, precision, and reproducibility. Recently, there is an FDR sensor capable of measuring moisture content in real time through an apparent dielectric constant change of electromagnetic waves. In addition, various artificial intelligence techniques that can non-linearly supplement the accuracy of FDR sensors are being studied. In this study, the accuracy of unit-water content measurement was compared and evaluated using machine learning and deep learning techniques after normalizing the data secured in concrete using frequency domain reflectometry (FDR) sensors used to measure soil moisture at home and abroad. The result of comparing the accuracy of machine learning and deep learning is judged to be excellent in the accuracy of deep learning, which can well express the nonlinear relationship between FDR sensor data and concrete unit-water content.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.201-202
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• 2023

Recently, interest in concrete quality has been increasing. It is important to manage these factors due to unit-water content and aggregate quality that affect concrete quality. In this study, the unit-water content of concrete was measured through an economical, easy-to-measure, and portable Frequency Domain Reflecmetry sensor among micro-methods that compensated for the shortcomings of existing concrete unit-water content measurement methods. As a result of predicting the unit-water content, the accuracy within the ± 10 kg/m³ error range was confirmed to be more than 72% of all factors. In order to ensure high accuracy, it is considered necessary to conduct an experiment to evaluate the unit-water content by conducting additional experiments according to other variables and factors.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.51-52
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• 2023

Recently, heat island and dry island phenomena occur frequently due to land surface development and excessive energy consumption in urban areas. As a result, the surface temperature of the building and the entire temperature of its surroundings are increased, and as a result, the durability of the building is rapidly deteriorated. In order to suppress these causes, a method of maintaining the temperature of road heating wires was implemented as a temporary measure, but this did not predict climate change. Therefore, this study is a method to measure the compressive strength, density, and thermal conductivity of light weight concrete using waste glass foam beads. After fabricating a simple chamber, the temperature and humidity of the inside and outside were measured with an Arduino device in consideration of external factors. Therefore, if waste glass foam beads made through proper mixing are constructed in the urban center, the quality of the urban can be improved.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.173-174
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• 2023

In this study, unit-water content was measured using a frequency domain reflecometry(FDR) sensor that complements the problems of the existing unit-water content measurement method to evaluate the unit-water content affecting the workability, durability, and quality of high strength concrete. The experiment used the unit-water content of high strength concrete as a variable, and the accuracy and probability distribution of the unit-water content measured through deep learning were analyzed for the output value output through the FDR sensor. In the case of the unit-water content predicted by deep learning analysis, a high accuracy and high distribution of more than 93% were found within the error range of ± 10 kg/m³. In the future, research is needed to secure high reliability by utilizing data obtained through experiments with various variables.