• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.1-8
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• 2022

The corrosion of reinforcement is the main reason for the performance degradation of concrete structures. The pre-rusted parts of rebar in concrete structures are vulnerable to the corrosion, especially if the structure is exposed to wet or chlorinated environments. In this study, effects of different curing solution on corrosion behavior of the pre-rusted rebars in the cement composites were investigated. HCl(3%) and CaCl₂(10%) solution were utilized to accelerate the pre-rust of the rebar, and each pre-rust condition rebar including reference (RE) were placed in mortar cylinder. Three kinds of samples then were cured in CaCl₂ (3%) solution and tap water respectively for 120 days. Electrochemical polarization and half-cell potential measurement were used to monitor the influence of curing water on the corrosion behavior of pre-rusted steel bar in cement composite. The surface morphology and composition of corroded steel bar were analyzed by scanning electron microscope and energy dispersive X-ray diffraction. The results show that the corrosion rates of pre-rusted samples in both curing water are higher than that of non-pre-rusted samples. The corrosion rates of RE, CaCl₂ and HCl pre-rusted samples in salt water were 8.14, 4.48, 13.81 times higher than those in tap water respectively, on the 120th day.

• 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.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.542-549
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• 2022

Purpose: Pipes are widely used as applied devices in many industrial fields such as machinery, electronics, electricity, and plants, and are also widely used in safety-related fields such as firefighting and chemistry. With the diversification of products, the importance of technology in the piping field is also increasing. In particular, when changing the existing copper pipe to stainless steel, it is necessary to evaluate safety and flow characteristics through structural analysis or flow analysis. Method: This study investigated the structural stability of the 6.35 and 15.88 socket models, which are integrated insert type connectors developed by a company, using FEM. For structural analysis, HyperMesh as pre-processor, HYPER VIEW as post-processor, and LS-DYNA as solver were used. Result: In the case of 6.35 socket, the maximum stresses at hook, holder and hinge were 95.02MPa, 19.59MPa and 44.01MPa, respectively, and in case of 15.88 socket, it was 127.7 MPa, 40.09MPa and 45.23MPa, respectively. Conclusion: Comparing the stress distribution of the two socket models, the stress in the 15.88 socket, which has a relatively large outer diameter, appears to be large overall, but it is significantly lower than the yield stress of each material, indicating that there is no problem in structural safety in both models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.310-316
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• 2021

Conventional satellites are generally large satellites that are multi-functional and have high performance. However, small satellites have been gradually drawing attention since the recent development of lightweight and integrated electric, electronic, and optical technologies. As the size and weight of a satellite decrease, the barrier to satellite development is becoming lower due to the cost of manufacture and cheaper launch. However, solar panels are essential for the power supply of satellites but have limitations in miniaturization and weight reduction because they require a large surface area to be efficiently exposed to sunlight. Space solar cells must be manufactured in consideration of various space environments such as spacecraft and environments with solar thermal temperatures. It is necessary to study structural materials for lightweight and high-efficiency solar cells by applying an unfolding mechanism that optimizes the surface-to-volume ratio. Currently, most products are developed and operated as solar cell panels for space applications with a triple-junction structure of InGaP/GaAs/Ge materials for high efficiency. Furthermore, multi-layered junctions have been studied for ultra-high-efficiency solar cells. Flexible thin-film solar cells and organic-inorganic hybrid solar cells are advantageous for material weight reduction and are attracting attention as next-generation solar cells for small satellites.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.4
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• pp.492-498
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• 2021

In this paper, the electromagnetic wave transmittance of the reinforced concrete structure wall was analyzed using the performance measurement system of electromagnetic wave shielding. Recently, electromagnetic wave shielding technologies on the reinforced concrete wall conditions have been studied, and the shielding effectiveness have been tested on unit cell size. However, the unit cell size tests have problems on that the measurement range for shielding performance is insufficient and it is difficult to reflect the real conditions of the concrete wall. Therefore, we constructed a shielding performance measurement system using a large sample of 2.2m × 2.2m like a real wall. To verify the measurement system, general reinforced concrete test samples were selected, and real shielding performance measurements and numerical analysis were proceeded. Test and numerical analysis results showed similar tendencies in the evaluation frequency range of 75MHz to 2GHz. Thus we validated the effectiveness of this shielding performance measurement system.

• Resources Recycling
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• v.31 no.1
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• pp.37-45
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• 2022

The development of the electrical, electronic, and telecommunication industries has increased the share of electricity in total energy consumption. With the enforcement of the Act on the Promotion of the Development, Use, and Diffusion of New and Renewable Energy in 2021, the mandatory supply ratio of new and renewable energy is expected to expand, and the amount of waste cables generated in the stage of replacing and discarding cables used in the industry is also expected to increase. The purpose of this study was to quantify the environmental burden of waste cable recycling through the life cycle assessment (LCA) method. The results showed that the higher the amount of glue contained in the waste cable, the greater was the amount of fine dust and greenhouse gases generated. In addition, by assigning weights to 10 environmental burden items, it was confirmed that the marine aquatic eco-toxicity potential (MAETP) and human toxicity potential (HTP) had the greatest environmental burden. The main causes were identified as heptane and ethanol, which were the glue contained in the waste cable and the cleaning solutions used to remove them. Therefore, it is necessary to refrain from using glue in the cable production process and reduce the environmental burden by reducing the use of waste cable cleaning solutions used in the recycling process or using alternative materials.

• Environmental and Resource Economics Review
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• v.31 no.3
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• pp.419-449
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• 2022

This paper aims to quantify the potential economic burdens of EU's carbon border adjustment mechanisms faced by Korean domestic industries. In addition, this study tries to compare and analyzes changes in the burden of each industry resulted from the implementation of the domestic low-carbon policy. Based on the quantitative findings, we intend to suggest policy implications for establishing mid- to long-term strategies in response to climate change risks. Based on the environmentally extended input-output analysis, the total economic burdens of the domestic industries due to the EU's carbon border adjustment mechanisms are estimated to be approximately KRW 8,245.6 billion in 2030. Looking at the impacts by industry, it is found that major industries such as petrochemicals, petroleum refining, transportation equipment, steel, automobiles, and electric/electronic equipment industries are expected to account for 84.3% of the total potential burdens. In addition, in multiple policy scenarios assuming technological developments and energy transition following the implementation of domestic low-carbon policies, the total economic burden of carbon border adjustment is expected to decrease by about 11.7% to 15.0%. The main result of this study suggests that we should not view EU EU's carbon border adjustment mechanism as a trade regulation, but to use it as a momentum for more effective implementation of the low-carbon and energy transition strategies in the global carbon neural era.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.550-559
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• 2022

Purpose: Pipes are widely used as applied devices in many industrial fields such as machinery, electronics, electricity, and plants, and are also widely used in safety-related fields such as firefighting and chemistry. With the diversification of products, the importance of technology in the piping field is also increasing. In particular, when changing the existing copper pipe to stainless steel, it is necessary to evaluate safety and flow characteristics through structural analysis or flow analysis. Method: This study investigated the safety by flow analysis of the 6.35 inch socket model, which are integrated insert type connectors developed by a company, using CFD analysis technique. For CDF analysis, RAN model and LES model are used. Result: As results of the analysis, amplitude of the pressure fluctuation acting on the wall of the piping system is formed at a level of 3,780 Pa or less, which is a very small level of pressure compared with the operating pressure or design stress of the refrigerant piping. Conclusion: These results mean that the effect of vibration caused by turbulence on the structural safety of the pipe is negligible.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.61-74
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• 2022

Recently, youth unemployment, especially the unemployment problem of university graduates, has emerged as a social problem. Unemployment of university graduates is both a pan-national issue and a university-level issue, and each university is making many efforts to increase the employment rate of graduates. In this study, we present a model that predicts employment availability of D-university graduates by utilizing Machine Learning. The variables used were analyzed using up to 138 personal information, admission information, bachelor's information, etc., but in order to reflect them in the future curriculum, only the data after admission works effectively, so by department / student. The proposal was limited to the recommended ability to improve the separate employment rate. In other words, since admission grades are indicators that cannot be improved due to individual efforts after enrollment, they were used to improve the degree of prediction of employment rate. In this research, we implemented a employment prediction model through analysis of the core ability of D-University, which reflects the university's philosophy, goals, human resources awards, etc., and machined the impact of the introduction of a new core ability prediction model on actual employment. Use learning to evaluate. Carried out. It is significant to establish a basis for improving the employment rate by applying the results of future research to the establishment of curriculums by department and guidance for student careers.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.267-277
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• 2022

Achievement at university is recognized in a comprehensive sense as the level of qualitative change and development that students have embodied as a result of their experience in university education. Therefore, the academic achievement of university students will be given meaning in cooperation with the historical and social demands for diverse human resources such as creativity, leadership, and global ability, but it is practically an indicator of the outcome of university education. Measurement of academic achievement by such credits involves many problems, but in particular, standardization of academic achievement by credits based on evaluation methods, contents, and university rankings is a very difficult problem. In this study, we present a model that uses machine learning techniques to predict whether or not academic achievement is excellent for D-University graduates. The variables used were analyzed using up to 96 personal information and bachelor's information such as graduation year, department number, department name, etc., but when establishing a future education course, only the data after enrollment works effectively. Therefore, the items to be analyzed are limited to the recommended ability to improve the academic achievement of the department/student. In this research, we implemented an academic achievement prediction model through analysis of core abilities that reflect the philosophy, goals, human resources image, and utilized machine learning to affect the impact of the introduction of the prediction model on academic achievement. We plan to apply the results of future research to the establishment of curriculum and student guidance conducted in the department to establish a basis for improving academic achievement.