• Transactions of the Korean hydrogen and new energy society
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• v.31 no.2
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• pp.184-193
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• 2020

One of the technical methods to increase the volumetric energy density of hydrogen is to pressurize the gaseous hydrogen and then contain it in a rigid vessel. Especially for automotive systems, the compressed hydrogen storage can be found in cars as well as at refueling stations. During the charging the pressurized hydrogen into a vessel, the temperature increases with the amount of stored hydrogen in the vessel. The temperature of the vessel should be controlled to be less than a limitation for ensure stability of material. Therefore, the accurate estimation of temperature is of significance for safely storing the hydrogen. In this work, three well-known cubic equations of state (EOSs) were adopted to examine the accuracy in regenerating thermodynamic properties of hydrogen within the temperature and pressure ranges for the compressed hydrogen storage. The formulations representing molar volume, internal energy, enthalpy, and entropy were derived for Redlich-Kwong (RK), Soave-Redlioch-Kwong (SRK), and Peng-Robinson (PR) EOSs. The calculated results using the EOSs were compared with literature data given by NIST. It was revealed that the accuracies of RK and SRK EOSs were satisfactorily compatible and better than the results by PR EOS.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.3
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• pp.233-239
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• 2014

This paper proposes that each converter supplies the power using the proposed droop control for the parallel operation of the converters. The proposed method is easy to increase the power as parallel system in DC distribution. By improving conventional droop-control method used in AC grid newly, a droop controller is designed to apply droop control in DC grid. And the control method of the proposed droop controller is explained particularly. In this paper, by applying the proposed control method to DC distribution system, propriety is verified through the simulation and the experiment.

• Environmental Engineering Research
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• v.23 no.3
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• pp.309-315
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• 2018

Chlortetracycline (CTC) is one of the most important compounds in antibiotic production, and its distribution has been widely investigated due to health and ecological concerns. This study presents systematic approach to optimize the high-performance liquid chromatography-tandem mass spectrometry for analyzing CTC in a multiple reaction monitoring mode ($479{\rightarrow}462m/z$). One-factor-at-a-time (OFAT) test with response surface analysis (RSA) was used as optimization strategy. In OFAT tests, the fragmentor voltage, collision energy, and ratio of acetonitrile in the mobile phase were selected as major factors for RSA. The experimental conditions were determined using a composite in cube design (CCD) to maximize the peak area. As a result, the partial cubic model precisely predicted the peak area response with high statistical significance. In the model, the (solvent composition) and (collision $energy^2$) terms were statistically significant at the 0.1 ${\alpha}$-level, while the two-way interactions of the independent variables were negligible. By analyzing the model equation, the optimum conditions were derived as 114.9 V, 15.7 eV, and 70.9% for the fragmentor voltage, collision energy, and solvent composition, respectively. The RSA, coupled with the CCD, offered a comprehensive understanding of the peak area that responds to changes in experimental conditions.

• Journal of Applied Biological Chemistry
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• v.43 no.1
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• pp.18-24
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• 2000

A one-dimensional transport of displacing monovalent ion, $A^+$, and a trivalent ion being displaced, $B^{3+}^ in a porous exchange system such as soil was approximated using the Crank-Nicolson implicit finite difference technique and the Thomas algorithm in tandem. The variations in the concentration profile were investigated by varying the ion-exchange equilibrium constant (k) of ion-exchange reactions, the influent concentrations, and the cation exchange capacity (CEC) of the exchanger, under constant flux condition of pore water and dispersion coefficient. A higher value of k resulted in a greater removal of the native ion, behind the sharper advancing front of displacing ion, while the magnitude of the penetration distance of $A^+$ was not great. As the CEC increased, the equivalent fraction of $B^{3+}^ initially in the soil was greater, thus indicating that a higher CEC adsorbed trivalent cations preferentially over monovalent ions. Mass balance error from simulation results was less than 1%, indicating this model accounted for instantaneous charge balance fairly well.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1016-1021
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• 2013

While using the hydrogen mixture gas torch, the glass edge sealing and the shape of the edge sealing parts is affected by many parameters such as flow rate of gas, traveling speed of torch, distance between glass and torch. As the glass edge sealing shape have effects on the insulation and airtightness and strength of the glass panel; the sealing shapes are predicted according to the process parameters. The paper highlight the nonlinear regression equations of the cross-sectional shape of the sealing shape according to the parameters, that is experimentally predicted later compared and verified the equation with the experimental result.

• Korean Journal of Materials Research
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• v.19 no.6
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• pp.330-336
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• 2009

The size of crystallites in mono-dispersed cubic silver bromide grains was measured by applying a powder X-ray diffraction method and Scherrer's equation to grains that were suspended in swollen gelatin layers. In order to evaluate the existence of defects, the measured crystallite size was compared to those measured by using a scanning electron microscope. In the case of the grains prepared by the controlled double jet method, the size of crystallites was equal to the edge length of the grains that had edge lengths smaller than 400 nm. This result proved the usefulness of the above-stated method for measuring the size of crystallites and also evaluating the presence of any crystal defect in each grain. In the case of the grains, which were precipitated in the presence of a sensitizing dye and potassium iodide, the size of crystallites was smaller than the edge's length, indicating the discontinuities in the grains introduced during the precipitation process.

• Journal of Environmental Science International
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• v.27 no.11
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• pp.975-982
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• 2018

In this study, zeolite (Z-C1) was synthesized using a fusion/hydrothermal method from coal fly ash. The morphological structures of Z-C1 were confirmed to be highly crystalline with a cubic crystal structure. Exchange capacities of $Ca^{2+}$ and $Mg^{2+}$ ions in a single and a mixed solution reached equilibrium within 120 min. The exchange kinetics of these ions were well predicted by the pseudo-second-order rate equation. The exchange isotherms of the $Ca^{2+}$ and $Mg^{2+}$ ions matched the Langmuir isotherm better than the Freundlich isotherm. The maximum cation exchange capacities ($q_m$) obtained by the Langmuir isotherm model were 2.11 mmol/g (84.52 mg/L) and 1.13 mmol/g (27.39 mg/L) for the $Ca^{2+}$ and $Mg^{2+}$ ions, respectively.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.52.1-52.1
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• 2019

The Helioseismic and Magnetic Imager (HMI) is the instrument of Solar Dynamics Observatory (SDO) to study the magnetic field and oscillation at the solar surface. The HMI image is not enough to analyze very small magnetic features on solar surface since it has a spatial resolution of one arcsec. Super resolution is a technique that enhances the resolution of a low resolution image. In this study, we use a method for enhancing the solar image resolution using a Deep-learning model which generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained a model based on a very deep residual channel attention networks (RCAN) with HMI images in 2014 and test it with HMI images in 2015. We find that the model achieves high quality results in view of both visual and measures: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is much better than the conventional bi-cubic interpolation. We will apply this model to full-resolution SDO/HMI and GST magnetograms.

• Steel and Composite Structures
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• v.48 no.3
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• pp.335-351
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• 2023

This research studies the primary resonance and nonlinear vibratory responses of multilayer functionally graded shallow (MFGS) shells under external excitations. The shells considered with functionally graded porous (FGP) core and resting on two types of nonlinear viscoelastic foundations (NVEF) governed by either a linear model with two parameters of Winkler and Pasternak foundations or a nonlinear model of hardening/softening cubic stiffness augmented by a Kelvin-Voigt viscoelastic model. The shells considered have three layers, sandwiched by functionally graded (FG), FGP, and FG materials. To investigate the influence of various porosity distributions, two types of FGP middle layer cores are considered. With the first-order shear deformation theory (FSDT), Hooke's law, and von-Kármán equation, the stress-strain relations for the MFGS shells with FGP core are developed. The governing equations of the shells are consequently derived. For the sake of higher accuracy and reliability, the P-T method is implemented in numerically analyzing the vibration, and the method of multiple scales (MMS) as one of the perturbation methods is used to investigate the primary resonance. The results of the present research are verified with the results available in the literature. The analytical results are compared with the P-T method. The influences of material, geometry, and nonlinear viscoelastic foundation parameters on the responses of the shells are illustrated.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.70.4-70.4
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• 2019

Image super-resolution (SR) is a technique that enhances the resolution of a low resolution image. In this study, we use three SR models (RCAN, ProSRGAN and Bicubic) for enhancing solar SDO/HMI magnetograms using deep learning. Each model generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). The pixel resolution of HMI is about 0.504 arcsec. Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained three models with HMI images in 2014 and test them with HMI images in 2015. We find that the RCAN model achieves higher quality results than the other two methods in view of both visual aspects and metrics: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is also much better than the conventional bi-cubic interpolation. We apply this model to a full-resolution SDO/HMI image and compare the generated image with the corresponding Hinode NFI magnetogram. As a result, we get a very high correlation (0.92) between the generated SR magnetogram and the Hinode one.