• Journal of the Korean Institute of Gas
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• v.14 no.6
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• pp.15-20
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• 2010

Compressed Natural Gas (CNG) buses have been supplied since the year 2000 in order to resolve severe atmospheric pollution in metropolitan area and contributed on the improvement of urban atmospheric environment. However, it is indispensible to take an adequate measure to guarantee the safety of CNG vehicles because of the possibility of huge fire accident. A receptacle, connecting device between high pressure fuel supply tank and fuel line, plays an important role in CNG supply system. In recent, leakage of CNG from receptacles has been reported. So, the concern about the security and reliability of receptacles has been arisen. Therefore, a lot of efforts to prevent leakage are invested among researchers and the durability of this component should be guaranteed despite repeated operation. This research has performed durability tests of a CNG receptacle regarding the repeated usage, extreme chattering, and continuous full flow test. Although a receptacle used for CNG vehicle satisfies validation requirements in the test results, it has been found that failure in the function of leakage prevention in a receptacle could take place in the case of prolonged exposure to high supply pressure in common quick charging environment on site.

• Convergence Security Journal
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• v.21 no.1
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• pp.191-200
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• 2021

Artificial intelligence technology is developing in an environment where a lot of data is produced due to the development of computing technology, a cloud environment that can store data, and the spread of personal mobile phones. Among these artificial intelligence technologies, the deep neural network provides excellent performance in image recognition and image classification. There have been many studies on image detection for forest fires and fire prevention using such a deep neural network, but studies on detection of cigarette smoking were insufficient. Meanwhile, military units are establishing surveillance systems for various facilities through CCTV, and it is necessary to detect smoking near ammunition stores or non-smoking areas to prevent fires and explosions. In this paper, by reflecting experimentally optimized numerical values such as activation function and learning rate, we did the detection of smoking pictures and non-smoking pictures in two cases. As experimental data, data was constructed by crawling using pictures of smoking and non-smoking published on the Internet, and a machine learning library was used. As a result of the experiment, when the learning rate is 0.004 and the optimization algorithm Adam is used, it can be seen that the accuracy of 93% and F1-score of 94% are obtained.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.76-83
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• 2021

This study examines the bending behavior of lap-spliced ultra-high-strength fiber-reinforced concrete members and evaluates the safety of the design codes for ultra-high-strength fiber-reinforced concrete structures. An experiment on a total of six beams was performed. The main variables were the fiber-inclusion and the lap-spliced length at the center of the beams. The steel fibers in a volume fraction of 2% were used, and the lap-splice lengths were determined to be 8db and 16db. As a result of the test, the specimens not reinforced with fiber lost abrupt load-bearing capacity at the lap region and did not experience yielding of the reinforcing bar. In the case of fiber-reinforced concrete, if a lap-splice length of 16db is secured, the yielding of the main reinforcing bar can be experienced, and appropriate flexural strength can be expressed. Based on the experimental results of this study, as a result of reviewing the lap-splice length calculation formulas of the current design standards and the ultra-high-strength concrete structural design recommendations, it was found that all of them were evaluated conservatively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.520-528
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• 2021

In this study, we attempted to derive major management factors related to the quality control of formwork and identified differences in the perceptions of construction engineers, construction managers, and field workers about the importance and performance of the derived factors. As a result of the study, 18 management factors related to the formwork were derived. Among the derived factors, the field workers placed importance on the factors that influence the detailed process of the formwork, while construction engineers placed importance on the factors related to the judgment of the progress and completion of the construction. The construction managers placed importance on the factors that affect the quality of the building frame. Based on the results of this study, it is expected that a plan to improve the quality of formwork that accepts the various opinions of each participant will be established.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.1161-1175
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• 2018

An unexpected event could be easily followed by a large secondary accident due to the limitation in sight of drivers in road tunnels. Therefore, a series of automated incident detection systems have been under operation, which, however, appear in very low detection rates due to very low image qualities on CCTVs in tunnels. In order to overcome that limit, deep learning based tunnel incident detection system was developed, which already showed high detection rates in November of 2017. However, since the object detection process could deal with only still images, moving direction and speed of moving vehicles could not be identified. Furthermore it was hard to detect stopping and reverse the status of moving vehicles. Therefore, apart from the object detection, an object tracking method has been introduced and combined with the detection algorithm to track the moving vehicles. Also, stopping-reverse discrimination algorithm was proposed, thereby implementing into the combined incident detection processes. Each performance on detection of stopping, reverse driving and fire incident state were evaluated with showing 100% detection rate. But the detection for 'person' object appears relatively low success rate to 78.5%. Nevertheless, it is believed that the enlarged richness of image big-data could dramatically enhance the detection capacity of the automatic incident detection system.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.184-193
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• 2021

Purpose: In this study, since the operation principle of the CCFL Exit light is the same as that of general lighting equipment, the characteristics of the CCFL Exit light were analyzed by deriving test items that can affect the characteristics of the light source from the KS standard, which is the standard for lamp ballast performance certification of general lighting equipment. Method: The samples used in the experiment were performed on products of two manufacturers for each size, such as large, medium, and small, and the test items were power factor, crest factor, and current harmonic distortion. Result: As a result of the experiment, the power factor showed a value between 0.4 and 0.6 in all samples, which was smaller than the 0.9 value set by KS. The crest factor ranged from 3.6 to 3.7 for large, 4.4 to 4.7 for medium, and 3.5 to 3.7 for small. It showed a value more than two times higher than the KS standard of 1.7. Current total harmonic distortion ranged from 81% to 110%, and considering that the KS standard was less than 20%, it could be confirmed that all samples had a value significantly exceeding the KS standard. Conclusion: The crest factor and current total harmonic distortion may affect the temperature rise of the light source and the burnout of the device. When developing an exit light, if this item is developed within the scope of the KS standard, the quality improvement and maintenance of the exit light will be greatly improved.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.1-6
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• 2021

Mercury, once released, is not destroyed but accumulates and circulates in the natural environment, causing serious harm to ecosystems and human health. In the United States, sulfur-impregnated activated carbon is being considered for the removal of vapor mercury from the flue gas of coal-fired power plants, which accounts for about 32 % of the anthropogenic emissions of mercury. In this study, a high-efficiency porous mercury adsorption material was developed to reduce the mercury vapor in the exhaust gas of coal combustion facilities, and the mercury adsorption characteristics of the material were investigated. As a result of the investigation of the vapor mercury adsorption capacity at 30℃, the silica nanotube MCM-41 was only about 35 % compared to the activated carbon Darco FGD commercially used for mercury adsorption, but it increased to 133 % when impregnated with 1.5 % sulfur. In addition, the furnace fly ash recovered from the waste copper regeneration process showed an efficiency of 523 %. Furthermore, the adsorption capacity was investigated at temperatures of 30 ℃, 80 ℃, and 120 ℃, and the best adsorption performance was found to be 80 ℃. MCM-41 is a silica nanotube that can be reused many times due to its rigid structure and has additional advantages, including no possibility of fire due to the formation of hot spots, which is a concern when using activated carbon.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1249-1249
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• 2022

The facade, an exterior material of a building, is one of the crucial factors that determine its morphological identity and its functional levels, such as energy performance, earthquake and fire resistance. However, regardless of the type of exterior materials, huge property and human casualties are continuing due to frequent exterior materials dropout accidents. The quality of the building envelope depends on the detailed design and is closely related to the back frames that support the exterior material. Detailed design means the creation of a shop drawing, which is the stage of developing the basic design to a level where construction is possible by specifying the exact necessary details. However, due to chronic problems in the construction industry, such as reducing working hours and the lack of design personnel, detailed design is not being appropriately implemented. Considering these characteristics, it is necessary to develop the detailed design process of exterior materials and works based on the domain-expert knowledge of the construction industry using artificial intelligence (AI). Therefore, this study aims to establish a detailed design automation algorithm for AI-based condition-responsive exterior wall panels and their back frames. The scope of the study is limited to "detailed design" performed based on the working drawings during the exterior work process and "stone panels" among exterior materials. First, working-level data on stone works is collected to analyze the existing detailed design process. After that, design parameters are derived by analyzing factors that affect the design of the building's exterior wall and back frames, such as structure, floor height, wind load, lift limit, and transportation elements. The relational expression between the derived parameters is derived, and it is algorithmized to implement a rule-based AI design. These algorithms can be applied to detailed designs based on 3D BIM to automatically calculate quantity and unit price. The next goal is to derive the iterative elements that occur in the process and implement a robotic process automation (RPA)-based system to link the entire "Detailed design-Quality calculation-Order process." This study is significant because it expands the design automation research, which has been rather limited to basic and implemented design, to the detailed design area at the beginning of the construction execution and increases the productivity by using AI. In addition, it can help fundamentally improve the working environment of the construction industry through the development of direct and applicable technologies to practice.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.2
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• pp.104-108
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• 2023

Because of recent expansion of the electric car market. it is highly growing that should be supplemented its performance and safely issue. The EMI problem due to the interlocking of electrical components that causes various safety problems such as fire in electric vehicles is emerging every time. We strive to achieve optimal charging efficiency by combining various technologies and reduce radioactive noise among the EMI noise of a weirless charging control module, one of the important parts of an electric vehicle was designed and tested. In order to analyze the EMI problems occurring in the wireless charging control module, the optimized wireless charging control module by applying the optimization design technology by learning the accumulated test data for critical factors by utilizing the Python-based script function in the Ansys simulation tool. It showed an EMI noise improvement effect of 25 dBu V/m compared to the charge control module. These results not only contribute to the development of a more stable and reliable weirless charging function in electric vehicles, but also increase the usability and efficiency of electric vehicles. This allows electric vehicles to be more usable and efficient, making them an environmentally friendly alternative.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.2
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• pp.97-104
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• 2023

In order to maximize the utilization of recycled fine aggregate, high strength mortar made of 100 % recycled fine aggregate was prepared, and its physical properties were evaluated to determine the possibility of using recycled fine aggregate as structural aggregate. The effect caused by the amount of nanosilica on the physical properties of w/b 0.2 recycled fine aggregate mortar consisting of cement, silica fume, and blast furnace slag. To improve the dispersion of nanosilica inside mortar, an aqueously dispersed nanosilica solution by ultrasonic tip sonication was prepared, and incorporated into the mortar to evaluate changes in mortar flow, porosity and compressive strength depending on nanosilica content. According to the experimental results, mortar flow decreased as the replacement ratio of nano-silica increased. As the replacement ratio of nanosilica increased up to 0.75 %, the porosity decreased and the compressive strength increased, but, at a replacement ratio of 1 %, the porosity increased and the compressive strength decreased. It was confirmed that the nano-silica replacement ratio of 0.75 % was optimum proportion to maximize the mechanical performance of high-strength recycled fine aggregate mortar.