• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.12
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• pp.769-776
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• 2016

In this study, a numerical simulation of a vanadium redox flow battery was investigated for reactions involving an electrochemical species using comprehensive conservation laws and a kinetic model. For a 3-D geometry of the cell, the distributions of electric potential, vanadium concentration, overpotential, and ohmic loss were calculated. The cell temperature and initial vanadium ion concentration were set as variables. The voltage and electrochemical loss were calculated for each variable. The effects of each variable's impact on the electrochemical performance of a vanadium redox flow battery was numerically analyzed using the calculated overpotential in the electrode and the ohmic loss in the electrolyte phase. The cell temperature increased from $20^{\circ}C$ to $80^{\circ}C$ when the voltage efficiency decreased from 89.34% to 87.29%. The voltage efficiency increased from 88.65% to 89.25% when the vanadium concentration was changed from $1500mol/m^3$ to $3000mol/m^3$.

• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.408-415
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• 2020

In this study, the AE-SOM method, which combines auto-encoder and self-organizing map, is used to detect and diagnose faults in EVA production process. Then, the fault propagation pathways are identified using Granger causality test. One year and seven months of operation data were obtained to detect faults of the process, and the process variables of the autoclave reactor are mainly analyzed. In the data pretreatment process, the data are standardized and 200 samples of each grade are randomly chosen to obtain a fault detection model. After that, the best matching unit (BMU) of each grade is confirmed by applying AE-SOM. The faults are determined based on each BMU. When a fault is found, the most causative variable of the fault is identified by using a contribution plot, and the fault propagation pathway is identified by Granger causality test. The prognostic of the two shutdowns is detected, and the fault propagation pathway caused by the faulty variable was analyzed.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.08a
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• pp.136-136
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• 2011

AlSb는 광전자 소자응용에 매우 유용한 재료이며 이를 이용한 반도체소자 설계 및 밴드갭 엔지니어링을 위해서는 화합물 반도체의 전자밴드구조를 포함한 광학적 특성이 반드시 요구된다. 본 연구는 이러한 요구의 해결방안으로서 AlSb 화합물의 유전함수 온도의존성을 0.7~5.0 eV의 에너지 영역에서 타원편광분석법을 이용하여 분석하였다. AlSb는 산소와 급격히 반응하기 때문에, 대기 중에서 물질 고유의 광특성이 유지되기 어려울 뿐만 아니라, 박막 위에 생성되는 산화막 때문에 순수한 AlSb의 유전함수 측정이 불가능하다. 따라서 박막의 산화 효과를 최소화하기 위하여 초고진공 상태의 molecular beam epitaxy 챔버 안에서 800 K의 온도로 성장한 1.5 ${\mu}m$ 두께의 AlSb 박막을 상온 300 K 까지 온도를 단계적으로 변화시켜가며 타원편광분석기를 이용하여 실시간으로 측정하였다. 각 온도에서 측정된 AlSb의 유전함수를 2차 미분하여 전이점(critical point)을 분석한 결과 $E_0$, $E_0+{\Delta}_0$, $E_1$, $E_1+{\Delta}_1$, $E_0'$, $E_0'+{\Delta}_0'$, $E_2$, $E_2+{\Delta}_2$에 해당하는 각 전이점들의 온도 의존성을 확인할 수 있었다. 실험에서 측정된 특정 온도를 포함하여 임의의 온도에서의 AlSb의 유전함수를 유도하기 위하여 변수화모델을 사용하였고 이를 통하여 각 변수들의 온도 의존 궤적을 분석하였다. 2차 미분법을 이용한 전이점들의 온도의존성 분석결과를 기준으로 변수화 모델링을 진행하였으며 그 결과 각 온도에서 실제 유전함수와 근소한 차이를 갖는 AlSb의 유전함수 모델을 만들 수 있었다. 따라서 본 연구결과는 반도체 물성에 대한 학술적 측면뿐 아니라 고온에서의 소자공정 실시간 모니터링 및 반도체 소자 설계 등의 산업적 측면에서 매우 유용하게 사용될 것으로 기대된다.

• Applied Chemistry for Engineering
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• v.32 no.6
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• pp.659-663
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• 2021

10 m³/min (CMM) multi-pollutants abatement system was successfully developed by effectively integrating ozone oxidation, wet scrubbing, and wet electrostatic precipitation for the simultaneous removal of particulate matters (PMs) and NOx in a semiconductor fabrication process. The sophisticated control and optimization of operating parameters were conducted to maximize the destruction and removal efficiency of NOx. In particular, the stability test of a wet electrostatic precipitator was carried out in parallel for 30 days to validate the reliability of core parts including a power supply. An O₃/NO ratio, which is the most important operating parameter, was optimized to be about 1.5 and the optimization of wet scrubbing with a reducing agent made it possible to analyze the contribution of neutralization reaction.

• The Journal of Bigdata
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• v.6 no.2
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• pp.39-49
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• 2021

Recently, large and diverse weather data are being collected by sensors from various sources. Efforts to predict the concentration of fine dust through machine learning are being made everywhere, and this study intends to compare PM10 and PM2.5 prediction models using data from 840 outdoor air meters installed throughout the city. Information can be provided in real time by predicting the concentration of fine dust after 5 minutes, and can be the basis for model development after 10 minutes, 30 minutes, and 1 hour. Data preprocessing was performed, such as noise removal and missing value replacement, and a derived variable that considers temporal and spatial variables was created. The parameters of the model were selected through the response surface method. XGBoost, Random Forest, and Deep Learning (Multilayer Perceptron) are used as predictive models to check the difference between fine dust concentration and predicted values, and to compare the performance between models.

• The Korean Journal of Applied Statistics
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• v.37 no.4
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• pp.467-484
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• 2024

Longitudinal data are measured repeatedly over time from the same subject, so there is a correlation from the repeated outcomes. Therefore, when analyzing this correlation, both serial correlation and between-subject variation must be considered in longitudinal data analysis. In this paper, we will focus on the marginalized models to estimate the population average effect of covariates among models for analyzing longitudinal binary data. Marginalized models for longitudinal binary data include marginalized random effects models, marginalized transition models, and marginalized transition random effect models, and in this paper, these models are first reviewed, and simulations are conducted using complete data and missing data to compare the performance of the models. When there were missing values in the data, there is a difference in performance depending on the model in which the data was generated. We analyze Korea Health Panel data using marginalized models. The Korean Medical Panel data considers subjective unhealthy responses as response variables as binary variables, compares models with several explanatory variables, and presents the most suitable model.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.6
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• pp.1034-1042
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• 2004

This study was carried out to investigate preparation of reconstructed red peppers, effects of pungency and redness of red peppers on the Kimchi quality using central composite design and response surfaces methodology. Capsaicinoids and ASTA (American Spice Trading Association) value put in X$_1$, X$_2$ of independent variable. The result of response surface regression analysis of reconstructed red peppers, correlation coefficient ($R^2$) of overall pungency intensity, persistence and degree of redness was 0.935, 0.935 and 0.821, respectively. After it was made Kimchi samples with reconstructed red peppers, it was examined pH, titratable acidity and lactic acid bacteria of its during fermentation. In the initial fermentation period of Kimchi, it showed pH of 5.46∼5.78, titratable acidity of 0.27∼0.31%, salt content of 2.26∼2.48% and lactic acid bacteria of 4.05${\times}$10$^{5}$ ∼6.23${\times}$10$^{5}$ , respectively. And it showed traditional fermentation pattern in the pH, titratable acidity and microbes of the middle (appropriate fermentation) and last (excessive) fermentation period. While capsaicinoids content in the Kimchi decreased a little according to extend fermentation period, ASTA value showed low correlation reconstructed red pepper and fermentation period. Also, it was analyzed correlation coefficient ($R^2$) of independent variables (capsaicinoids, X$_1$; ASTA value, X$_2$) between sensory attribute in the Kimchi during fermentation. The result of regression analysis, $R^2$ in the overall pungency intensity, persistence and degree of redness showed 0.515, 0.675, 0.784, respectively.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.11a
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• pp.17-22
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• 2007

차량에서 전조등의 밝기 변화가 운전자의 장애물 인식능력을 저하시키고, 운전자에게 불쾌감과 스트레스를 제공한다면 운전자 및 보행자의 안전에 위협이 될 수 있다. 그러므로 차량 전조등의 밝기변화 패턴에 영향을 미치는 전조등의 전압과 시간을 변수로 하여, 순간적으로 밝기변동이 발생하였을 경우, 연령대별(20/60대)로 운전자가 느끼는 심리적인 반응(불쾌감)이 어떠한 경향을 갖는지를 파악하는 것이 중요하다. 따라서 본 논문에서는 운전자의 야간 주행시 전조등의 밝기변동에 대한 경향을 파악하기 위해 전조등의 밝기변동 영상을 제작한 다양한 전조등의 밝기패턴(전압패턴 A/B)을 제공하여 본 시험을 위한 1차 예비 시험을 실시하였다. 예비시험 결과, 전압패턴 A에 대해서는 전압과 시간변이 대해서 모두 영향을 받는 것으로 나타났으며, 반면, 전압패턴 B의 경우에 있어서는 시간변이 보다 전압변이가 더 큰 요소로 작용하는 것으로 나타났다. 또한 불쾌감을 느끼는 것을 수치적으로 표현하였을 경우에, 전압패턴 A보다 B패턴에서 더 많은 불쾌감을 느끼는 것으로 파악되었다. 현재, 본 연구는 진행중에 있으며, 앞으로, 2차/3차 예비시험을 통해, 연령대별 시인능력평가 및 심리적 반응 평가, 도로조명의 유무에 따른 운전자의 시인능력 평가, 그리고 전조등의 밝기변동 빈도 수에 대한 심리적 반응을 모의시험하고 경향을 파악하고 있으며, 이를 통해서 본 시험을 준비중에 있다.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.16 no.3
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• pp.291-299
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• 2018

Under a pyro-processing concept, an electrolytic reduction process has been developed to reduce uranium oxide in molten salt by electrochemical means as a part of spent fuel treatment process development. Accordingly, a model based on electrochemical theory is required to design a reactor for the electrolytic reduction process. In this study, a 1D model based on the phase-field theory, which explains phase separation behaviors was developed to simulate electrolytic reduction of uranium oxide. By adopting parameters for diffusion of oxygen elements in a pellet and electrochemical reaction rate at the surface of the pellet, the model described the behavior of inward reduction well and revealed that the current depends on the internal diffusion of the oxygen element. The model for the electrolytic reduction is expected to be used to determine the optimum conditions for large scale reactor design. It is also expected that the model will be applied to simulate the integration of pyro-processing.

• Korean Chemical Engineering Research
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• v.53 no.3
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• pp.309-314
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• 2015

Adsorption of brilliant blue FCF dye from aqueous solution using coconut shell based activated carbon was investigated. Batch experiments were carried out as function of adsorbent dose, initial concentration, contact time and temperature. The equilibrium adsorption data were analyzed by Langmuir and Freundlich model. The results indicate that Freundlich model provides the best correlation of the experimental data. Base on the estimated Freundlich constant (1/n=0.129~0.212), this process could be employed as effective treatment method. Adsorption kinetics experimental data were modeled using the pseudo-first-order and pseudo-second-order kinetic equation. It was shown that pseudo-second-order kinetic equation could best describe the adsorption kinetics. Base on the negative Gibbs free energy value (-4.81~-10.33 kJ/mol) and positive enthalpy value (+78.59 kJ/mol) indicate that the adsorption is spontaneous and endothermic process.