• Journal of Industrial Technology
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• v.27 no.B
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• pp.245-253
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• 2007

Failure rate serves as a pivotal role in reliability study. Of all, the constant failure rate is the most popularly used in field exercises. In reality, however, the electrical and electronic parts' life is represented by not only the constant failure rate but the decreasing and/or increasing failure rates. Explicit consideration and incorporation of them into the model development may yield more desirable results. In this study, we built a reliability model for failure rates varying over time intervals and derived well known measures such as probability density function, reliability function, mean life, moments, and mission time. We then evaluated mean life with consideration of the first-year multiplier and compared the results those with constant failure rate. The results given in the study may provide a reference applying for practical decision making.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.106-111
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• 1994

We proposed a new variable sampling rate model which expresses the phenomena with both rapid and slow components. A method for determining the variable sampling rate and the older of the time series model was explained. The proposed variable sampling rate model was evaluated based oil an information criterion(AIC). Tile variable sampling rate model brought smaller an information criterion than one of a constant sampling rate model of conventional type, and was proved to be effective as a prediction model of the system with both rapid and slow components.

• Journal of Environmental Science International
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• v.2 no.4
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• pp.331-336
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• 1993

A mathematical model for organic removal efficiency was investigated in a fluidized bed biofilm reactor by changing the feed flow rate, the residence time and the recycle flow rate. In batch experiment, organic removal could be assumed as first order and an intrinsic first order rate constant(k1) was found $6.4{\times}^{-6}cm^3/mg{\cdot}sec$ at influent COD range of 3040 - 6620 mg/L. In continuous experiment, at the condition of the influent COD, 3040 mg/L, the superficial upflow velocity, 0.47 cm/sec, the biofilm thickness 336 ${\mu}m$ and the biofilm dry density 0.091 g/mL, the calculated COD removal efficiency from the mathematical model gave 60% which was very close to the observed value of 66 %. As the feed flow rate was increased, the COD removal efficiency was sharply decreased and at constant feed flow rate, the COD removal efficiency was decreased also as the residence time being decreased.

• 한국연소학회:학술대회논문집
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• 2014.11a
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• pp.59-62
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• 2014

Predicting coal combustion by computational fluid dynamics (CFD) requires a combination of complicated flow and reaction models for turbulence, radiation, particle flows, heterogeneous combustion, and gaseous reactions. There are various levels of models available for each of the phenomena, but the use of advanced models are significantly restricted in a large-scale boiler due to the computational costs and the balance of accuracy between adopted models. In this study, the influence of coal devolatilization model and turbulent mixing rate was assessed in CFD for a commercial boiler at 500 MWe capacity. For coal devolatilization, two models were compared: i) a simple model assuming single volatile compound based on proximate analysis and ii) advanced model of FLASHCHAIN with multiple volatile species. It was found out that the influence of the model was observed near the flames but the overall gas temperature and heat transfer rate to the boiler were very similar. The devolatilization rate was found not significant since the difference in near-flame temperature became noticeable when it was multiplied by 10 or 0.1. In contrast, the influence of turbulent mixing rate (constant A in the Magnussen model) was found very large. Considering the heat transfer rate and flame temperature, a value of 1.0 was recommended for the rate constant.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.1046-1053
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• 1999

The musculotendon model is presented to show the declines in muscle force and shortening velocity during muscle fatigue due to the repeated functional electrical stimulation (FES). It consists of the nonlinear activation and contraction dynamics including physiological concepts of muscle fatigue. The activation dynamics represents $Ca^{2+}$ binding and unbinding mechanism with troponins of cross-bridges in sarcoplasm. It has the constant binding rate or activation time constant and two step nonlinear unbinding rate or inactivation time constant. The contraction dynamics is the modified Hill type model to represent muscle force - length and muscle force - velocity relations. A muscle fatigue profile as a function of the intracellular acidification, pH is applied into the contraction dynamics to represent the force decline. The computer simulation shows that muscle force and shortening velocity decline in stimulation time. And we validate the model. The model can predicts the proper muscle force without changing its parameters even when existing the estimation errors of the optimal fiber length. The change in the estimate of the optimal fiber length has an effect only on muscle time constant in transient period not on the tetanic force in the steady-state and relaxation periods.

• Journal of Environmental Science International
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• v.9 no.1
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• pp.75-80
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• 2000

Kinetic data for the acid phase anaerobic digestion were presented in this study and the constants were determined with acid production rate and gas production rate. Process models based on continuous culture theory were used to describe the characteristics of the acid forming microorganisms and to enable further development toward utilization of the process in a more rational manner. Acid phase digestion can be separated with appropriate manipulation of hydraulic retention time in anaerobic digestion. Kinetic analysis of data from the various hydraulic retention times using a phase specific model obtained form the acid phase indicated maximum specific growth rate of 0.40/h, saturation constant of 2,000mgCOD.$\ell$, yield coefficient of 0.35 mgVSS/msCOD utilized and decay constant of 0.04/h for the acid production rate. Similar analysis of data for the gas production rate indicated maximum specific growth rate of 0.003/h, saturation constant of 2,200mgCOD/$\ell$, yield coefficient of 0.035 mgVSS/mgCOD utilized and decay constant of 0.06/h.

• KDI Journal of Economic Policy
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• v.37 no.4
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• pp.1-20
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• 2015

We examine the validity of popular exchange rate models such as the purchasing power parity (PPP) hypothesis and the monetary model for Korean won/US dollar exchange rate. Various specification tests demonstrate that Korean data are more favorable for both models based on time-varying cointegration coefficients as compared to those based on constant cointegration coefficients. When the abilities to predict future exchange rates between those models based on time-varying cointegration coefficients are compared, an in-sample analysis shows that the time-varying PPP (monetary model) has better predictive power over horizons shorter (longer) than one year. Results from an out-of-sample analysis indicate that the time-varying PPP outperforms models based on constant cointegration coefficients when predicting future exchange rate changes in the long run.

• Bulletin of the Korean Chemical Society
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• v.26 no.1
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• pp.139-145
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• 2005

Artificial neural networks (ANNs), for a first time, were successfully developed for the modeling and prediction of solvent effects on rate constant of [2+2] cycloaddition reaction of diethyl azodicarboxylate with ethyl vinyl ether in various solvents with diverse chemical structures using quantitative structure-activity relationship. The most positive charge of hydrogen atom (q$^+$), dipole moment ($\mu$), the Hildebrand solubility parameter (${\delta}_H^2$) and total charges in molecule (q$_t$) are inputs and output of ANN is log k$_2$ . For evaluation of the predictive power of the generated ANN, the optimized network with 68 various solvents as training set was used to predict log k$_2$ of the reaction in 16 solvents in the prediction set. The results obtained using ANN was compared with the experimental values as well as with those obtained using multi-parameter linear regression (MLR) model and showed superiority of the ANN model over the regression model. Mean square error (MSE) of 0.0806 for the prediction set by MLR model should be compared with the value of 0.0275 for ANN model. These improvements are due to the fact that the reaction rate constant shows non-linear correlations with the descriptors.

• Bulletin of the Korean Chemical Society
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• v.12 no.6
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• pp.692-698
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• 1991

The reaction path Smoluchowski equation approach developed in a recent work to calculate the rate constant for a diffusive multidimensional barrier crossing process is extended to incorporate the configuration-dependent diffusion matrix. The resulting formalism is then applied to the investigation of stilbene photoisomerization dynamics. Adapting a model two-dimensional potential and a model diffusion matrix proposed by Agmon and Kosloff [J. Phys. Chem.,91 (1987) 1988], we derive an eigenvalue equlation for the relaxation rate constant of the stilbene photoisomerization. This eigenvalue equation is solved numerically by using the finite element method. The advantages and limitations of the present method are discussed.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.4
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• pp.457-468
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• 2013

Based on the activated sludge model(ASM), a mathematical model which represents the aerobic sludge digestion by sequencing batch reactor(SBR) combined with ultrasonic treatment was composed and performed in this study. Aerobic digestion using sequencing batch reactor(SBR) equipped with ultrasound treatment was also experimented for the purpose of parameter calibration. Most of the presented kinetic parameters in ASM or ASM2 could be used for the aerobic digestion of sludge but the parameters related in hydrolysis and decay rate needed modification. Hydrolysis rate constant of organic matter in aerobic condition was estimated at $0.3day^{-1}$ and the maximum growth rate for autotrophs in aerobic condition was $0.618day^{-1}$. Solubilization reactions of particulate organics and nitrogen by ultrasonication was added in this kinetic model. The solubilization rate is considered to be proportional to the specific energy which is defined by specific ultrasound power and sonication time. The solubilization rate constant by ultrasonication was estimated at $0.202(W/L)^{-1}day^{-1}$ in this study. Autotrophs as well as heterotrophs also decomposed by ultrasonic treatment and the nitrification reaction was limited by the lack of autotrophs accumulation in the digester.