• Journal of Powder Materials
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• v.18 no.3
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• pp.226-237
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• 2011

W-ZrC and W-HfC composite powders were fabricated by the Plasma Alloying & Spheroidization (PAS) method and the powders were sprayed into hybrid coating layers by using Low Vacuum Plasma Spray (LVPS) process, respectively. Microstructure, mechanical properties, and ablation characteristics of the fabricated coating layers were investigated. The LVPS process led to successful production of W-Carbide hybrid coatings, approximately 400 ${\mu}M$ or above in thickness. As the substrate preheating temperature increased from $870^{\circ}C$ to $917^{\circ}C$, the hardness of the W-ZrC coating layer increased due to decreased porosity. Vickers hardness showed higher value (about 108.4 HV) in W-ZrC hybrid coating material compared to that of W-HfC while adhesive strength was found to be similar in both coating layers. The plasma torch test revealed good ablation resistance of the W-Carbide hybrid coating layers. The relatively high performance W-ZrC coating layer at the elevated temperature is thought to be attributed to both the strengthening effect of ZrC particle remained in the layer and the formation of ZrO2 phase with high temperature stability.

• Journal of the Korean Society of Hazard Mitigation
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• v.1 no.1 s.1
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• pp.127-138
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• 2001

Although Carbon/Carbon Composites(CFRCs) have excellent mechanical properties at high temperature, the disadvantage of combustion in air restricts their applications. Thus a lot of investments have been studied to improve the drawback of CFRCs. In this study, SiC used as a thermal protective coating material possesses almost the same expansion coefficient compared to that of carbon, so SiC was coated on 4D (directional) CFRCs by Pack-Cementation process. For the 4D CFRCs coated with SiC, optical microscopy observations were performed to estimate the coating mechanism involved and TGA tests were also performed to evaluate the improvement of combustion resistance. And their high temperature combustion properties were investigated by the arc torch plasma test. From the results, it is found that the mechanical properties and high temperature combustion properties of the 4D(directional) CFRCs coated with SiC were much better than bare 4D CFRCs.

• Journal of Welding and Joining
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• v.31 no.1
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• pp.65-70
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• 2013

Finite element analysis and welding experiments were performed to evaluate deformation aspect for Flux Cored Arc Welding(FCAW) and Electro Gas Welding(EGW). Numerical researches of FCAW and EGW were performed considering the difference of number of welding pass and welding direction to arc flow. To perform the numerical study of FCAW and EGW, number of welding pass and welding direction to arc flow were considered in the finite element model. FCAW process requires multi pass and its welding direction is vertical to welding torch. On the other hand, EGW process requires single pass and its welding direction is parallel to welding torch. The difference of welding direction and heat input was considered in the finite element analysis. In FCAW process, Goldak's double ellipsoidal heat input model was adopted. In the EGW process, Hemi-spherical power density distribution was adopted. In the results of experiment and finite element analysis, angular deformation of FCAW process is larger than that of EGW process.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.11
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• pp.1491-1497
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• 2011

One of the primary concerns in the design of welding devices is how to reduce the distance error between the welding path and the torch, especially when the path has a combination of circular and linear parts. This study investigated a mechanism for reducing the tracking error in the tangent area of a circular and linear path. A portable welding device, called a carriage, has been designed for a specific welding path by considering the distance error deviation. This welding carriage for vertical cover plate welding consists of a rail, a welding torch and the carriage body itself.

• Elastomers and Composites
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• v.45 no.2
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• pp.87-93
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• 2010

The fire resistive materials are used to resist from fire accidents in the building. In this study silicone rubber/inorganic flame retardant composites were prepared by mechanical stirring method, using aluminium trihydroxide(ATH, $Al(OH)_3$) and magnesium dihydroxide(MDH, $Mg(OH)_2$) as synergistic fire-resistant additives. The thermal properties of the fire resistant composites were characterized by thermogravimetric analysis(TGA). In addition, rheological properties were observed by rheometer and fire-resistant properties were tested by gas torch. Through this study, we realized that the silicone rubber containing ATH, MDH increased the performance of fire-resistance.

• Applied Chemistry for Engineering
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• v.9 no.5
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• pp.667-673
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• 1998

Rebar corrosion in a simulated pore solution (SPS) with chloride ion was analyzed by Tafel and AC impedance method and corrosion effects of surface roughness and iron oxide layer were also investigated. Corrosion estimation of rebar by electrochemical impedance spectroscopy is very useful, and the measured value can be adapted to proposed electrochemical equivalent circuit model. Corrosion potential increased to the cathodic direction as the concentration of chloride ions increased and corrosion current had the same tendency as above. Surface films were analyzed with scanning electron microscope and Auger electron spectroscopy. Thermally oxidized layer by torch flame for 15 sec was very poor at anti-corrosive property. The corrosion rate of rebar increased as the surface roughness increased. Also, higher temperatures above RT of SPS in initial stage caused a rebar to be corroded faster.

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.3
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• pp.88-95
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• 2019

The hydrogen torch ignition system has been widely used to ignite a pure aluminum for aluminum powder combustion system because of its simple ignition method. However, the conventional hydrogen torch ignition system has a disadvantage that requires a high-pressure tank to supply hydrogen, which leads to the increase of the weight. In order to solve this problem, a hydrogen ignition system using $NaBH_4$, a solid chemical hydride, was designed in this study. The thermal decomposition of $NaBH_4$ was initiated approximately at $500^{\circ}C$ and hydrogen was generated. The parameters affecting the thermal decomposition characteristics of $NaBH_4$ were analyzed and the aluminum combustion test was carried out using $NaBH_4$-based hydrogen ignition system to study the applicability to a practical aluminum-combustion propulsion system.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.6
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• pp.359-366
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• 2020

In this study, a simulation-based damage estimation method for helidecks is proposed using an artificial neural network. The structural members that share a connecting node in the helideck are regarded as a damage group, and a total of 37,400 damage scenarios are numerically generated by applying randomly assigned damage to up to three damage groups. Modal analysis is then performed for all the damage scenarios, which are selectively used as either training or validation or verification sets based on the purpose of use. An artificial neural network with three hidden layers is constructed using a PyTorch program to recognize the patterns of the modal responses of the helideck model under both damaged and undamaged states, and the network is successively trained to minimize the loss function. Finally, the estimated damage rate from the proposed artificial neural network is compared to the actual assigned damage rate using 400 verification scenarios to show that the neural network is able to estimate the location and amount of structural damage precisely.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.2
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• pp.34-41
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• 2021

A commercial HVOF torch (originally designed for coating applications) has been modified as a high temperature flow source for material testing. In this study, a water cooled commercial Gardon gauge was used to measure heat fluxes at four locations away from the nozzle exit. The cooling water temperature data were used to calculate calorimetric heat fluxes at the same locations. The heat fluxes from both methods were compared and the calorimetric heat fluxes were found to be many times higher than the Gardon gauge heat fluxes. A hypothesis is applied to the calorimetric method to understand the discrepancy seen between the methods. The Gardon gauge heat fluxes are seen to be in the range of the hypothesized calorimetric calculations. This can be considered as a considerable validation for the hypothesis, but further refinement needed using appropriate numerical models.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.2
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• pp.67-72
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• 2022

Ecological research relies on the interpretation of large amounts of visual data obtained from extensive wildlife surveys, but such large-scale image interpretation is costly and time-consuming. Using an artificial intelligence (AI) machine learning model, especially convolution neural networks (CNN), it is possible to streamline these manual tasks on image information and to protect wildlife and record and predict behavior. Ecological research using deep-learning-based object recognition technology includes various research purposes such as identifying, detecting, and identifying species of wild animals, and identification of the location of poachers in real-time. These advances in the application of AI technology can enable efficient management of endangered wildlife, animal detection in various environments, and real-time analysis of image information collected by unmanned aerial vehicles. Furthermore, the need for school education and social use on biodiversity and environmental issues using AI is raised. School education and citizen science related to ecological activities using AI technology can enhance environmental awareness, and strengthen more knowledge and problem-solving skills in science and research processes. Under these prospects, in this paper, we compare the results of our early 2013 study, which automatically identified African cichlid fish species using photographic data of them, with the results of reanalysis by CNN deep learning method. By using PyTorch and PyTorch Lightning frameworks, we achieve an accuracy of 82.54% and an F1-score of 0.77 with minimal programming and data preprocessing effort. This is a significant improvement over the previous our machine learning methods, which required heavy feature engineering costs and had 78% accuracy.