• Journal of the Korean earth science society
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• v.35 no.5
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• pp.362-374
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• 2014

This study investigated the initial mass function (IMF) and star formation history of high-mass stars in the Small Magellanic Cloud (SMC) using a population synthesis technique. We used the photometric survey catalog of Lee (2013) as the observable quantities and compare them with those of synthetic populations based on Bayesian inference. For the IMF slope (${\Gamma}$) range of -1.1 to -3.5 with steps of 0.1, five types of star formation models were tested: 1) continuous; 2) single burst at 10 Myr; 3) single burst at 60 Myr; 4) double bursts at those epochs; and 5) a complex hybrid model. In this study, a total of 125 models were tested. Based on the model calculations, it was found that the continuous model could simulate the high-mass stars of the SMC and that its IMF slope was -1.6 which is slightly steeper than Salpeter's IMF, i.e., ${\Gamma}=-1.35$.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.5
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• pp.718-724
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• 2000

A model for depicting the rocket engine combustion process is presented and several experiments near a design point are provided with a FOOF type of unlike impinging injector for a propellant combination of Jet A-1 fuel and liquid-oxygen. The model is based on the assumption that the vaporization is the rate-controlling combustion process. The effects of initial drop size and initial drop velocity are systematically shown and discussed. It is seen that in the midst of considered parameters the change of initial drop size is more sensitive to the performance. The proposed model describes qualitative trends of combustion process well despite of its simplicity.

• Korean Journal of Food Science and Technology
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• v.36 no.2
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• pp.349-354
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• 2004

Predictive growth model of Vibrio parahaemolyticus in modified surimi-based imitation crab broth was investigated. Growth curves of V. parahaemolyticus were obtained by measuring cell concentration in culture broth under different conditions ($Initial\;cell\;level,\;1{\times}10^{2},\;1{\times}10^{3},\;and\;1{\times}10^{4}\;colony\;forming\;unit\;(CFU)/mL$; temperature, 15, 25 37, and $40^{\circ}C$; pH 6, 7, and 8) and applying them to Gompertz model. Microbial growth indicators, maximum specific growth rate (k), lag time (LT), and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of V. parahaemolyticus increased with increasing temperature, reaching maximum rate at $37^{\circ}C$. LT and GT were also the shortest at $37^{\circ}C$. pH and initial cell number did not influence k, LT, and GT values significantly (p>0.05). Polynomial model, $k=a{\cdot}\exp(-0.5{\cdot}((T-T_{max}/b)^{2}+((pH-pH_{max)/c^{2}))$, and square root model, ${\sqrt{k}\;0.06(T-9.55)[1-\exp(0.07(T-49.98))]$, were developed to express combination effects of temperature and pH under each initial cell number using Gauss-Newton Algorism of Sigma plot 7.0 (SPSS Inc.). Relative coefficients between experimental k and k Predicted by polynomial model were 0.966, 0.979, and 0.965, respectively, at initial cell numbers of $1{\times}10^{2},\;1{\times}10^{3},\;and\;1{\times}10^{4}CFU/mL$, while that between experimental k and k Predicted by square root model was 0.977. Results revealed growth of V. parahaemolyticus was mainly affected by temperature, and square root model showing effect of temperature was more credible than polynomial model for prediction of V. parahaemolyticus growth.

• Journal of the Korean Society of Safety
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• v.37 no.2
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• pp.1-9
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• 2022

Most factories deal with toxic or flammable chemicals in their industrial processes. These hazardous substances pose a risk of leakage due to accidents, such as fire and explosion. In the event of chemical release, massive casualties and property damage can result; hence, quantitative risk prediction and assessment are necessary. Several methods are available for evaluating chemical dispersion in the atmosphere, and most analyses are considered neutral in dispersion models and under far-field wind condition. The foregoing assumption renders a model valid only after a considerable time has elapsed from the moment chemicals are released or dispersed from a source. Hence, an initial dispersion model is required to assess risk quantitatively and predict the extent of damage because the most dangerous locations are those near a leak source. In this study, the dispersion model for initial consequence analysis was developed with three-dimensional unsteady advective diffusion equation. In this expression, instantaneous leakage is assumed as a puff, and wind velocity is considered as a coordinate transform in the solution. To minimize the buoyant force, ethane is used as leaked fuel, and two different diffusion coefficients are introduced. The calculated concentration field with a molecular diffusion coefficient shows a moving circular iso-line in the horizontal plane. The maximum concentration decreases as time progresses and distance increases. In the case of using a coefficient for turbulent diffusion, the dispersion along the wind velocity direction is enhanced, and an elliptic iso-contour line is found. The result yielded by a widely used commercial program, ALOHA, was compared with the end point of the lower explosion limit. In the future, we plan to build a more accurate and general initial risk assessment model by considering the turbulence diffusion and buoyancy effect on dispersion.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.200-205
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• 1999

In this study, a computer program considering iniial imperfectiionof axiymmetric reinforced concrete shell which show plastic deformation by large external loading was developed . Initial imperfection of wall was assumed as 'sine curve' which can be expressed as Wi =W0 sin(n$\pi$/1y). The developed model was applied to the analysis of dynamic response of axisymmetric reinforced concrete shell when it has initial imperfection . The initial imperfection of 0.0, -5.0 and 5 cm and steel ration 0 , 3 and 5% were tested for numerical examples.

• Smart Structures and Systems
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• v.24 no.5
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• pp.631-639
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• 2019

Finite element analysis is one of the important methods to study the structural performance. Due to the simplification, discretization and error of structural parameters, numerical model errors always exist. Besides, structural characteristics may also change because of material aging, structural damage, etc., making the initial finite element model cannot simulate the operational response of the structure accurately. Based on Bayesian methods, the initial model can be updated to obtain a more accurate numerical model. This paper presents the work on the field test, modal identification and model updating of a Chinese reinforced concrete pagoda. Based on the ambient vibration test, the acceleration response of the structure under operational environment was collected. The first six translational modes of the structure were identified by the enhanced frequency domain decomposition method. The initial finite element model of the pagoda was established, and the elastic modulus of columns, beams and slabs were selected as model parameters to be updated. Assuming the error between the measured mode and the calculated one follows a Gaussian distribution, the posterior probability density function (PDF) of the parameter to be updated is obtained and the uncertainty is quantitatively evaluated based on the Bayesian statistical theory and the Metropolis-Hastings algorithm, and then the optimal values of model parameters can be obtained. The results show that the difference between the calculated frequency of the finite element model and the measured one is reduced, and the modal correlation of the mode shape is improved. The updated numerical model can be used to evaluate the safety of the structure as a benchmark model for structural health monitoring (SHM).

• Journal of Ocean Engineering and Technology
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• v.19 no.6 s.67
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• pp.78-85
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• 2005

Initial alignment and localization are important topics in inertial navigation systems, since misalignment and initial position error wholly propagate into the navigation systems and deteriorate the performance of the systems. This paper presents the error convergence characteristics of the hybrid navigation system for underwater vehicles initial position, which is based on an inertial measurement unit (IMU) accompanying a range sensor. This paper demonstrates the improvement on the navigational performance oj the hybrid system with the range information, especially focused on the convergence of the estimation of underwater vehicles initial position error. Simulations are performed with experimental data obtained from a rotating ann test with a fish model. The convergence speed and condition of the initial error removal for random initial position errors are examined with Monte Carlo simulation. In addition, numerical simulation is conducted with an AUV model in lawn-mowing survey mode to illustrate the error convergence of the hybrid navigation System for initial position error.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.10
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• pp.534-539
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• 2013

In general, entire supply air of the BSL3 laboratory should be vented to the outside for its biosafety and the air conditioning system should always be operating to maintain a room pressure difference. In this regard, annual energy consumption is approximately five or ten times greater than the magnitude of the office building. In addition, to adjust room pressure difference to the set value efficiently, the supply and exhaust duct system are installed in each room of the BSL3 lab. Thus, initial construction cost is extremely high. In this study, multizone simulation is performed to estimate maintaining the appropriate room pressure difference in the case of changing model A (each room supply and exhaust system) to model B (each zone supply and exhaust system) for verification of the BSL3 lab biosafety. Also, in the case of these two models, the multizone simulation for three kinds of biohazard scenario is performed as part of risk assessment. The analysis of initial construction cost of two models is conducted for comparison. According to the studies, initial construction cost of model B is less than about 22% of existing model A. Moreover, biosafety of the BSL3 lab is still maintaining in the case of the two models.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.217-229
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• 2018

This paper aims at applying the data mining such as decision tree, neural network, and logistic regression to an unsold apartment complex in Wirye new town and developing the model forecasting the result of initial sale contract by house unit. Raw data are divided into training data and test data. The order of predictability in training data is neural network, decision tree, and logistic regression. On the contrary, the results of test data show that logistic regression is the best model. This means that logistic regression has more data adaptability than neural network which is developed as the model optimized for training data. Determinants of initial sale are the location of floor, direction, the location of unit, the proximity of electricity and generator room, subscriber's residential region and the type of subscription. This suggests that using two models together is more effective in exploring determinants of initial sales. This paper contributes to the development of convergence field by expanding the scope of data mining.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.3
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• pp.116-126
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• 2010

The Korean rolling stock safety regulation stipulates that the collision deceleration of a car body should be maintained under average 5g and maximum 7.5g during train collisions. One-dimensional dynamic model of a full rake train, which is made up of nonlinear springs/bars-dampers-masses, is often used to estimate the collision decelerations of car bodies in a basic design stage. By the way, the previous studies have often used some average force-deformation curve for energy absorbing structures in rolling stock. Through this study, we intended to analyse how much the collision deceleration levels are influenced by the initial peak force modeling in the one-dimensional force-deformation curve. The numerical results of the one-dimensional dynamic model for the Korean High-Speed Train show that the initial peak force modeling gives significant effect on the collision deceleration levels. Therefore the peak force modeling of the force-deformation curve should be considered in one-dimensional dynamic model of a full rake train to evaluate the article 16 of the domestic rolling stock safety regulations.