• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.471-478
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• 2022

This paper is about research and development of Korea Aerospace University's Solar-Powered UAV System that named of KAU-SPUAV, and describes the design process of the 4.2 m solar UAV that succeeded in a long flight of 32 hours and 19 minutes at June 2020. In order to improve the long-term flight performance of the KAU-SPUAV, For reduce drag, a circular cross-section of the fuselage was designed, and manufactured light and sturdy fuselage by applying a monocoque structure using a glass fiber composite material. In addition, a solar module optimized for the wing shape of a 4.2 m solar drone was constructed and arranged, and a propulsion system applied with the 23[in] × 23[in] propeller was constructed to improve charging and flight efficiency. The developed KAU-SPUAV consumes an average of 55W when cruising and can receive up to 165W of energy during the day, and its Long-term Endurance was verified through flight tests.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.394-401
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• 2021

The construction of new renewable energy facilities is steadily increasing every year. In particular, the offshore wind farm market, which has abundant development scalability and a high production coefficient, is growing rapidly. The southwest sea has the highest possible offshore wind power potential, and related projects are to be promoted. This study presents a basic design procedure by the EUROCODE and considers structural safety in the development of an effective of shore wind foundation in the clay layer. In a previous study, the wind power generator of 5MW class was the main target, but the 8MW of wind turbine generator, which meets the technical trend of the wind turbine market in the Southwest sea, was selected as the standard model. Furthermore, a foundation that fulfills the geological conditions of the Southwest sea was developed. The structural safety of this foundation was verified using finite element method. Moreover, structural safety was secured by proper reinforcement from the initial design. Based on the results of this study, structural safety check for various types of foundations is possible in the future. Additionally, specialized structural design and evaluation guidance were also established.

• Journal of the Korean Institute of Gas
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• v.26 no.6
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• pp.9-15
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• 2022

In order to verify the durability of the high-pressure hydrogen tank in the operating pressure range, a hydraulic rupture test should be performed. However, if the bubbles generated by the initial injection process of water are attached to the inner wall of the tank and remain, a sudden pressure change of the bubbles during the rupture of the pressurized tank may cause shock and noise. Therefore, in this study, the flow velocity required to remove the bubbles remaining on the inner wall of the tank was predicted through simplified formulas, and the shape of the injection nozzle to maintain the flow velocity was determined based on the shape of the hydrogen tank for the hydrogen bus. In addition, a numerical model was developed to predict the change in flow velocity according to the inlet pressure, and an experiment was performed through a model tank to prove the validity of the prediction result. As a result of the experiment, the flow velocity near the tank wall was similar to the predicted value of the analysis model, and when the inlet pressure was 1.5 to 5.5 bar, the minimum size of the removable bubble was predicted to be about 2.2 to 4.6 mm.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.63-80
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• 2022

As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.107-118
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• 2022

The social need for stable hydrogen storage technologies that respond to the increasing demand for hydrogen energy is increasing. Among them, underground hydrogen storage is recognized as the most economical and reasonable storage method because of its vast hydrogen storage capacity. In Korea, low-depth hydrogen storage using artificial protective structures is being considered. Further, establishing corresponding safety standards and ground stability evaluation is becoming essential. This study evaluated the hydro-mechanical behavior of the ground during a hydrogen gas leak from a low-depth underground hydrogen storage facility through the HM coupled analysis model. The predictive reliability of the simulation model was verified through benchmark experiments. A parameter study was performed using a metamodel to analyze the sensitivity of factors affecting the surface uplift caused by the upward infiltration of high-pressure hydrogen gas. Accordingly, it was confirmed that the elastic modulus of the ground was the largest. The simulation results are considered to be valuable primary data for evaluating the complex analysis of hydrogen gas explosions as well as hydrogen gas leaks in the future.

• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.58-63
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• 2022

With the emergence of environmental problems caused by fine dust worldwide, LNG, which is cheaper and less pollution than diesel, is attracting attention as the next generation energy of automobiles and is expanding its supply. However, it is difficult to operate smoothly due to the lack of infrastructure for LNG charging stations in Korea and the limited size of containers that can be installed according to regulations. In Korea, research and development on the contents of containers for the smooth operation of natural gas vehicles are underway, but there is a problem that the container directly receives the impact of the vehicle collision and explodes, causing a major disaster. Therefore, in this study, the safety of the container was verified by deriving the strain and stress values through ANSYS Explicit Dynamics analysis. As a result, a maximum stress of 565.37MPa occurred in the container, and it is expected that plastic deformation will occur as it exceeds the yield stress of STS304 used as a material for the container, which is beyond 505MPa. When an impact caused by a collision between a vehicle and a container is applied, it is considered necessary to design a support or reinforcement because the container may be damaged or defective.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.697-703
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• 2022

Due to the recent economic downturn caused by Covid-19 and the unstable international situation, many investors are choosing the derivatives market as a means of investment. However, the derivatives market has a greater risk than the stock market, and research on the market of market participants is insufficient. Recently, with the development of artificial intelligence, machine learning has been widely used in the derivatives market. In this paper, reinforcement learning, one of the machine learning techniques, is applied to analyze the scalping technique that trades futures in minutes. The data set consists of 21 attributes using the closing price, moving average line, and Bollinger band indicators of 1 minute and 3 minute data for 6 months by selecting 4 products among futures products traded at trading firm. In the experiment, DNN artificial neural network model and three reinforcement learning algorithms, namely, DQN (Deep Q-Network), A2C (Advantage Actor Critic), and A3C (Asynchronous A2C) were used, and they were trained and verified through learning data set and test data set. For scalping, the agent chooses one of the actions of buying and selling, and the ratio of the portfolio value according to the action result is rewarded. Experiment results show that the energy sector products such as Heating Oil and Crude Oil yield relatively high cumulative returns compared to the index sector products such as Mini Russell 2000 and Hang Seng Index.

• Journal of the Korean Geosynthetics Society
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• v.21 no.2
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• pp.57-65
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• 2022

This study simulated the shock wave propagation through the tamping material between explosives and hole wall at blasting works and verified the effect of tamping materials. The Arbitrary Lagrangian-Eulerian(ALE) method was selected to model the mixture of solid (Lagrangian) and fluid (Eulerian). The time series analysis was carried out during blasting process time. Explosives and tamping materials (air or water) were modeled with finite element mesh and the hole wall was assumed as a rigid body that can determine the propagation velocity and shock force hitting the hole wall from starting point (explosives). The numerical simulation results show that the propagation velocity and shock force in case of water were larger than those in case of air. In addition, the real site at blasting work was modeled and simulated. The rock was treated as elasto-plastic material. The results demonstrate that the instantaneous shock force was larger and the demolished block size was smaller in water than in air. On the contrary, the impact in the back side of explosives hole was smaller in water, because considerable amount of shock energy was used to demolish the rock, but the propagation of compression through solid becomes smaller due to the damping effect by rock demolition. Therefore, It can be proven that the water as the tamping media was more profitable than air.

• Korean Journal of Ecology and Environment
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• v.55 no.4
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• pp.330-340
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• 2022

We deduced the proper estimation methodology for the amount of carbon sequestration by damaged trees for Environmental Impact Assessment (EIA). The nine development projects related to renewable energy, damaged trees occur, assessment status and used method of evaluating the carbon storage of damaged trees were summarized. And after re-calculating the carbon storage of damaged trees through allometric equations, the difference between the two groups, re-calculated the damaged trees carbon storage and the damaged trees carbon storage in the report, was validated. As a result, damaged trees carbon storage in words was more than the re-calculated damaged trees carbon storage, and it was statistically significant (p<0.005). This result means that the existing method for calculating damaged tree carbon storage is overcalculated. It was judged that it was necessary to improve the calculation method. Therefore, allometric equations suitable for each dominated-tree species should be used when calculating the damaged tree carbon storage. Furthermore, we propose to establish a carbon storage calculation system based on actual data from the ecosystem so that researchers can efficiently and accurately the damaged trees carbon storage.

• Composites Research
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• v.36 no.1
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• pp.53-58
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• 2023

The PIC design method is assigning different stacking sequences for each shell element through the preliminary FE analysis. In previous study, machine learning was applied to the PIC design method in order to assign the region efficiently, and the training data is labeled by dividing each region into tension, compression, and shear through the preliminary FE analysis results value. However, since buckling is not considered, when buckling occurs, it can't be divided into appropriate loading type. In the present study, it was proposed PIC-NTL (PIC design using novel technique for analyzing load type) which is method for applying a novel technique for analyzing load type considering buckling to the conventional PIC design. The stress triaxiality for each ply were analyzed for buckling analysis, and the representative loading type was designated through the determined loading type within decision area divided into two regions of the same size in the thickness direction of the elements. The input value of the training data and label consisted in coordination of element and representative loading type of each decision area, respectively. A machine learning model was trained through the training data, and the hyperparameters that affect the performance of the machine learning model were tuned to optimal values through Bayesian algorithm. Among the tuned machine learning models, the SVM model showed the highest performance. Most effective stacking sequence were mapped into PIC tube based on trained SVM model. FE analysis results show the design method proposed in this study has superior external loading resistance and energy absorption compared to previous study.