• Applied Chemistry for Engineering
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• v.22 no.2
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• pp.167-172
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• 2011

In this work, the effect of surface treatment on mesoporous carbons (MCs) supports was investigated by analyzing surface functional groups. MCs were prepared by a conventional templating method using mesoporous silica (SBA-15) for using catalyst supports in direct methanol fuel cells (DMFCs). The MCs were treated with different phosphoric acid ($H_3PO_4$) concentrations i.e., 0, 1, 3, 4, and 5 M at 343 K for 6 h. And then Pt-Ru was deposited onto surface treated MCs (H-MCs) by chemical reduction method. The characteristics of Pt-Ru catalysts deposited onto H-MCs were determined by specific surface area and pore size analyzer, X-ray diffraction, X-ray photoelectron, transmission electron microscopy, and inductive coupled plasma-mass spectrometer. The electrochemical properties of Pt-Ru/H-MCs catalysts were also analyzed by cyclic voltammetry experiments. From the results of surface analysis, an oxygen functional group was introduced to the surface of carbon supports. From the results, the H4M-MCs carbon supports surface treated with 4 M $H_3PO_4$ led to uniform dispersion of Pt-Ru onto H4M-MCs, resulting in enhancing the electro-catalytic activity of Pt-Ru catalysts.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.590-596
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• 2020

In the island areas where system connection with the commercial power grid is difficult, it is quite important to find a method to efficiently manage energy produced with independent microgrids. In this paper, a prosumer management system for P2P power transaction was realized through the testing the power meter and the response rate of the collected data for the power produced in the small-scale microgrids in which hybrid models of solar power and wind power were implemented. The power network of the microgrid prosumer was composed of mesh structure and the P2P power transaction was tested through the power meter and DC power transmitter in the off-grid sites which were independently constructed in three places. The measurement values of the power meter showed significant results of voltage (average): 380V + 0.9V, current (average): + 0.01A, power: 1000W (-1W) with an error range within ±1%. Stabilization of the server was also confirmed with the response rate of 0.32 sec. for the main screen, 2.61 sec. for the cumulative power generation, and 0.11 sec for the power transaction through the transmission of 50 data in real time. Therefore, the proposed system was validated as a P2P power transaction system that can be used as an independent network without transmitted by Korea Electric Power Corporation (KEPCO).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.587-596
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• 2021

Naval battleships have systems to perform special purposes, such as the Command and Fire Control System (CFCS). Some of the this equipment should be equipped with an Uninterruptible Power System (UPS ) to ensure operational continuity and the backup of important data, even during unexpected power outages caused by problems with the ship's power generator. Heavy combat losses can occur if the equipment cannot satisfy the function. Therefore, it is important to design a stable UPS. The battery and Battery Management System (BMS) are two of the most important factors for designing a stable UPS. A power outage will be encountered if the battery and BMS are not stable. The customer will be exposed to abnormal situations, loss of important tactical data, and inability to operate some of the CFCS. As a result, an enhanced safety system should be designed. Thus, this study implemented and verified the improved system in terms of three methods, such as comparative analysis of the batteries, improvement about leakage current of the circuit, and tests of the aggressive environmental resistance to improve the UPS for CFCS.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.67-76
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• 2020

This paper reports an experimental study to evaluate the flexural behavior of concrete beams reinforced using Fe based shape memory alloy (Fe-SMA) bars. For the experiment, a concrete beam of 200mm×300mm×2,200mm was produced, and a 4% pre-strained Fe-SMA bar was used as a tensile reinforcement. As experimental variables, type of tensile reinforcement (SD400, Fe-SMA), reinforcement ratio (0.2, 0.39, 0.59, 0.78), activation of Fe-SMA (activation, non-activation), and joint method of Fe-SMA bar (Continuous, welding, coupler) were considered. The electric resistance heating method was used to activate the Fe-SMA bar, and a current of 5A/㎟ was supplied until the specimen reached 160℃. After the upward displacement of the specimen due to the camber effect was stabilized, a three-point flexural loading experiment was performed using an actuator of 2,000 kN capacity. As a result of the experiment, it was found that the upward displacement occurred due to the camber effect as the Fe-SMA bar was activated. The specimen that activated the Fe-SMA bar had an initial crack at a higher load than the specimen that did not activate it. However, as with general prestressed concrete, the effect of the prestress by Fe-SMA activation on the ultimate state of the beam was insignificant.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.7-15
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• 2022

Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.32 no.2
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• pp.77-82
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• 2022

Recently, research on the development of low-cost/high-efficiency water electrolysis catalysts to replace noble metal catalysts is being actively conducted. Since overvoltage reduces the overall efficiency of the water splitting device, lowering the overvoltage of the oxygen evolution reaction (OER) is the most important task in order to generate hydrogen more efficiently. Currently, noble metal catalysts show excellent characteristics in OER performance, but they are experiencing great difficulties in commercialization due to their high price and efficiency limitations due to low reactivity. In this study, a water electrolysis catalyst Ni-MWCNT was prepared by successfully doping Ni into the MWCNTs structure through the pulsed laser ablation in liquid (PLAL) process. High resolution-transmission electron microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS) were performed for the structure and chemical composition of the synthesized Ni-MWCNT. Catalytic oxygen evolution reaction evaluation was performed by linear sweep voltammetry (LSV) overvoltage characteristics, Tafel slope, electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and Chronoamperometry (CA) was used for measurement.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.99-108
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• 2022

Among induced polarization (IP) methods, spectral IP (SIP) uses alternating current as a transmission source to measure amplitudes and phase of complex electrical resistivity at each source frequency, which disperse with respect to source frequencies. The frequency dependence, which can be explained by a relaxation model such as Cole-Cole model or equivalent models, is analyzed to estimate SIP parameters from dispersion curves of complex resistivity employing multi-objective optimization (MOO). The estimation uses a generic algorithm to optimize two objective functions minimizing data misfits of amplitude and phase based on Cole-Cole model, which is most widely used to explain IP relaxation effects. The MOO-based estimation properly recovered Cole-Cole model parameters for synthetic examples but hardly fitted for the real laboratory measures ones, which have relatively smaller values of phases (less than about 10 mrad). Discrepancies between scales for data misfits of amplitude and phase, used as parameters of MOO method, and it is in necessity to employ other methods such as machine learning, which can deal with the discrepancies, to estimate SIP parameters from dispersion curves of complex resistivity.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.93-98
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• 2023

In this paper, an artificial neural network based on simulated annealing was constructed. The mapping relationship between the parameters of micro-scaled flow channels electrochemical machining and the channel shape was established by training the samples. The depth and width of micro-scaled flow channels electrochemical machining on stainless steel surface were predicted, and the flow channels experiment was carried out with pulse power supply in NaNO3 solution to verify the established network model. The results show that the depth and width of the channel predicted by the simulated annealing artificial neural network with "4-7-2" structure are very close to the experimental values, and the error is less than 5.3%. The predicted and experimental data show that the etching degree in the process of channels electrochemical machining is closely related to voltage and current density. When the voltage is less than 5V, a "small island" is formed in the channel; When the voltage is greater than 40V, the lateral etching of the channel is relatively large, and the "dam" between the channels disappears. When the voltage is 25V, the machining morphology of the channel is the best.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.11
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• pp.215-222
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• 2018

In this paper, the research on the energy storage system adapting super-capacitor has been performed. The most advanced features compared to the conventional lead-acid battery systems is that it can obtain high power capability due to the super capacitor power characteristics. The suggested system can attain high power in short times and achieve high power quality improvements. The application areas are power quality improvement system, motor start power which requires high power during transient times. The energy conversion system consists of bi-directional converter and inverter and advantages of high speed, high power charging and discharging performances. The design steps for the two loop controller of the bi-directional inverter are suggested and verified by the experiment and manufacturing. The two loop controller design starts from linearized transfer function which is calculated from the state averaging model including state decoupling method. The current controller requirements are 20% overshoot and settling time and voltage controller are no overshoot and settling time which is 10 times longer than current controller. The design is verified from the step input response. The designed controllers have unity power factor characteristics and thus can improve the power quality of the grid. It also has fast response time and zero steady state error.