• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.409-418
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• 2021

Conformal coating is a technology that protects PCB(Printed Circuit Board) and minimizes PCB failures. Since the defects in the coating are linked to failure of the PCB, the coating surface is examined for air bubbles to satisfy the successful conditions of the conformal coating. In this paper, we propose an algorithm for detecting problematic bubbles in high-risk groups by applying image signal processing. The algorithm consists of finding candidates for problematic bubbles and verifying candidates. Bubbles do not appear in visible light images, but can be visually distinguished from UV(Ultra Violet) light sources. In particular the center of the problematic bubble is dark in brightness and the border is high in brightness. In the paper, these brightness characteristics are called valley and mountain features, and the areas where both characteristics appear at the same time are candidates for problematic bubbles. However, it is necessary to verify candidates because there may be candidates who are not bubbles. In the candidate verification phase, we used convolutional neural network models, and ResNet performed best compared to other models. The algorithms presented in this paper showed the performance of precision 0.805, recall 0.763, and f1-score 0.767, and these results show sufficient potential for bubble test automation.

• Explosives and Blasting
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• v.37 no.3
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• pp.13-24
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• 2019

This paper was prepared to investigate the behavior of fragments in underwater torpedo explosion beneath a frigate or surface ship by using an explicit finite element analysis. In this study, a fluid-structure interaction (FSI) methodology, called the multi-material arbitrary Lagrangian-Eulerian (MM-ALE) approach in LS-DYNA, was employed to obtain the responses of the torpedo fragments and frigate hull to the explosion. The Euler models for the analysis were comprised of air, water, and explosive, while the Lagrange models consisted of the fragment and the hull. The focus of this modeling was to examine whether a worst-case fragment could penetrate the frigate hull located close (4.5 m) to the exploding torpedo. The simulation was performed in two separate steps. At first, with the assumption that the expanding skin of the torpedo had been torn apart by consuming 30% of the explosive energy, the initial velocity of the worst-case fragment was sought based on a well-known experimental result concerning the fragment velocity in underwater bomb explosion. Then, the terminal velocity of the worst-case fragment that is expected to occur before the fragment hit the frigate hull was sought in the second step. Under the given conditions, the possible initial velocities of the worst-case fragment were found to be very fast (400 and 1000 m/s). But, the velocity difference between the fragment and the hull was merely 4 m/s at the instant of collision. This result was likely to be due to both the tremendous drag force exerted by the water and the non-failure condition given to the frigate hull. Anyway, at least under the given conditions, it is thought that the worst-case fragment seldom penetrate the frigate hull because there is no significant velocity difference between them.

• Journal of The Korean Society For Urban Railway
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• v.6 no.4
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• pp.319-326
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• 2018

The safety interval to prevent collision between trains in a train control system is based on the braking distance according to the emergency braking of the train. The evaluation of the braking performance is based on the longitudinal train dynamics or the commissioning test in the test track, but since the conditions such as the weakening of the adhesion coefficient between the wheel and rail can not all be considered, these conventional methods are not sufficient to design of the train control systems. Therefore, in this study, the Monte Carlo Method (MCM) which can consider various environments is used to analyze braking performance and limitations. The braking model is based on the air braking used in the emergency braking and is modeled to take into account the braking pressure, efficiency, friction coefficient, adhesion condition, and vehicle mass distribution. It is confirmed that braking performance can be improved by controlling the quality of braking device. In addition, the change of the braking performance was confirmed according to the vehicle constituting the train. The results of this study are expected to be used as basic information for designing safety clearance for the train control systems and as a basis for improving the braking performance of railway vehicles.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.445-454
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• 2022

Ice accretion on the aircraft components, such as wings, fuselage, and empennage, can occur when the aircraft encounters a cloud zone with high humidity and low temperature. The prevention of ice accretion is important because it causes a decrease in the aerodynamic performance and flight stability, thus leading to fatal safety problems. In this study, a shape design optimization of a multi-element airfoil is performed to minimize the amount of ice accretion on the high-lift device including leading-edge slat, main element, and trailing-edge flap. The design optimization framework proposed in this paper consists of four major parts: air flow, droplet impingement and ice accretion simulations and gradient-free optimization algorithm. Reynolds-averaged Navier-Stokes (RANS) simulation is used to predict the aerodynamic performance and flow field around the multi-element airfoil at the angle of attack 8°. Droplet impingement and ice accretion simulations are conducted using the multi-physics computational analysis tool. The objective function is to minimize the total mass of ice accretion and the design variables are the deflection angle, gap, and overhang of the flap and slat. Kriging surrogate model is used to construct the response surface, providing rapid approximations of time-consuming function evaluation, and genetic algorithm is employed to find the optimal solution. As a result of optimization, the total mass of ice accretion on the optimized multielement airfoil is reduced by about 8% compared to the baseline configuration.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1069-1080
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• 2022

The tropospheric ozone is a pollutant that causes a great deal of damage to humans and ecosystems worldwide. In the event that ozone moves downwind from its source, a localized problem becomes a regional and global problem. To enhance ozone monitoring efficiency, geostationary satellites with continuous diurnal observations have been developed. The objective of this study is to derive the Tropospheric Ozone Movement Vector (TOMV) by employing continuous observations of tropospheric ozone from geostationary satellites for the first time in the world. In the absence of Geostationary Environmental Monitoring Satellite (GEMS) tropospheric ozone observation data, the GEOS-Chem model calculated values were used as synthetic data. Comparing TOMV with GEOS-Chem, the TOMV algorithm overestimated wind speed, but it correctly calculated wind direction represented by pollution movement. The ozone influx can also be calculated using the calculated ozone movement speed and direction multiplied by the observed ozone concentration. As an alternative to a backward trajectory method, this approach will provide better forecasting and analysis by monitoring tropospheric ozone inflow characteristics on a continuous basis. However, if the boundary of the ozone distribution is unclear, motion detection may not be accurate. In spite of this, the TOMV method may prove useful for monitoring and forecasting pollution based on geostationary environmental satellites in the future.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• Explosives and Blasting
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• v.40 no.3
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• pp.19-32
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• 2022

Hydrogen is a fuel having the highest energy compared with other common fuels. This means hydrogen is a clean energy source for the future. However, using hydrogen as a fuel has implication regarding carrier and storage issues, as hydrogen is highly inflammable and unstable gas susceptible to explosion. Explosions resulting from hydrogen-air mixtures have already been encountered and well documented in research experiments. However, there are still large gaps in this research field as the use of numerical tools and field experiments are required to fully understand the safety measures necessary to prevent hydrogen explosions. The purpose of this present study is to develop and simulate 3D numerical modelling of an existing hydrogen gas station in Jeonju by using handheld LiDAR and Ansys AUTODYN, as well as the processing of point cloud scans and use of cloud dataset to develop FEM 3D meshed model for the numerical simulation to predict peak-over pressures. The results show that the Lidar scanning technique combined with the ANSYS AUTODYN can help to determine the safety distance and as well as construct, simulate and predict the peak over-pressures for hydrogen refueling station explosions.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.4
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• pp.222-230
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• 2023

In the present work, the scale effect on the Boil-Off Rate (BOR) was investigated based on an analytical method to systematically evaluate the thermal performance of a Liquefied Natural Gas (LNG) Cargo Containment System (CCS). A two-dimensional thermal resistance network model was developed to accurately estimate the heat ingress into the CCS from the outside. The analysis was performed for the KC-1 LNG membrane tank under the IGC and USCG design conditions. The ballast compartment of both the LNG tank and cofferdam was divided into six sections and a thermal resistance network model was made for each section. To check the validity of the developed model, the analysis results were compared with those from existing literature. It was shown that the BOR values under the IGC and USCG design conditions were agreed well with previous numerical results with a maximum error of 1.03% and 0.60%, respectively. A SDR, the scale factor of the LNG CCS was introduced and the BOR, air temperature of the ballast compartment, and the surface temperature of the inner hull were obtained to examine the influence of the SDR on the thermal performance. Finally, a correlation for the BOR was proposed, which could be expressed as a simple formula inversely proportional to the SDR. The proposed correlation could be utilized for predicting the BOR of a full-scale LNG tank based on the BOR measurement data of lab-scale model tanks.

• Land and Housing Review
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• v.15 no.1
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• pp.167-177
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• 2024

This study aimed to assess the efficacy of an adsorption process in removing organic matter and micropollutant residuals. After a full-scale water circulation system, the adsorption process was considered a post-treatment step. The system, treating anthropogenically impacted surface waters, comprises a hydro-cyclone, coagulation, flocculation, and dissolved air flotation unit. While the system generally maintained stable and satisfactory effluent quality standards over months, it did not meet the highest standard for organic matter (as determined by chemical oxygen demands). Adsorption experiments utilized two granular activated carbon types, GAC 830 and GCN 830, derived from coal and coconut-shell feedstocks, respectively. The assessment encompassed organic materials along with two notable micropollutants: acetaminophen (APAP) and acid orange 7 (AO7). Adsorption kinetics and isotherm experiments were conducted to determine adsorption rates and maximum adsorption amounts. The quantitative findings derived from pseudo-second-order kinetics and Langmuir isotherm models suggest the effectiveness of the adsorption process. The findings of this study propose the potential of employing the adsorption process as a post-treatment to enhance the treatment of contaminants that are not satisfactorily treated by conventional water circulation systems. This enhancement is crucial for ensuring the sustainability of urban water cycles.

• Journal of the Korea Organic Resources Recycling Association
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• v.18 no.3
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• pp.77-86
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• 2010

In this study, the model of the indirect wind suction waste sorting machine for characteristics of the screening of waste was studied using computational fluid dynamics and the drag coefficient for the model and the suction wind speed were obtained. The wind separator are developing by installing a cyclone air outlet to the suction blower impeller waste is selective in a way that does not pass the features and characteristics of the inlet pipe of the pressure loss and separation efficiency can have a significant impact on. Using Wind separator for selection of waste in the waste prior research on the aerodynamic properties are essential. For plastic cases, it is reasonable to take the drag coefficient between 0.8 and 1.0, and for cans, compression depending on whether the cans, the drag coefficient is in the range from 0.2 to 0.7. The separation efficiency of waste as change suction speed was the highest efficiency when the suction speed was 25~26 m/s. Shape of the inlet, depending on how the transfer pipe of the duct pressure loss occurs because the inlet velocity changes through the appropriate design standards to allow for continued research is needed.