• Journal of Advanced Marine Engineering and Technology
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• v.39 no.4
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• pp.374-380
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• 2015

In this paper, a dynamic model describing the 2 phase effect on the gas diffusion layer depending on load change of a fuel cell stack was developed to examine the effects of liquid water in fuel cell cathode gas diffusion layer on the fuel cell performance. For the developed model, 2 phase effect on the performance of a fuel cell stack depending on the load changes, concentration distribution of water vapor and oxygen inside a gas diffusion layer, the effect of the thickness and porosity of the gas diffusion layer on the fuel cell stack voltage were examined. As a result, a fuel cell stack voltage for the 2 phase model within the scope of the research become lower than that for the 1 phase model regardless of the load. Although oxygen molar concentration for the gas diffusion layer adjacent to the catalyst layer was the lowest, water vapor concentration is the highest. In addition, as thickness and porosity of the gas diffusion layer increased and decreased, respectively, the fuel cell stack voltage decreased.

• The Journal of the Acoustical Society of Korea
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• v.27 no.2E
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• pp.45-50
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• 2008

In recent years, quantitative ultrasound (QUS) technologies have played a growing role in the diagnosis of osteoporosis. Most of the commercial bone somometers measure speed of sound (SOS) and/or broadband ultrasonic attenuation (EUA) at peripheral skeletal sites. However, the QUS parameters are purely empirical measures that have not yet been firmly linked to physical parameters such as bone strength or porosity. In the present study, the theoretical models for wave propagation in cancellous bone, such as the Biot model, the stratified model, and the modified Biot-Attenborough (MBA) model, were applied to predict the dependence of phase velocity on porosity in cancellous bone. The optimum values for the input parameters of the three models in cancellous bone were determined by comparing the predictions with the previously published measurements in human cancellous bone in vitro. This modeling effort is relevant to the use of QUS in the diagnosis of osteoporosis because SOS is negatively correlated to the fracture risk of bone, and also advances our understanding of the relationship between phase velocity and porosity in cancellous bone.

• 한국연소학회:학술대회논문집
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• 2006.10a
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• pp.202-208
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• 2006

The purpose of this research is to model numerically the turbulent gas-particle flows in a rectangular chamber using Eulerian-Eulerian Method. A computer code using the ${\kappa}-{\varepsilon}-Ap$ two-phase turbulence model is developed for the numerical study. This code and the Eulerian multiphase model in FLUENT were used for the numerical simulations of the two-phase flow in a rectangular chamber. The numerical results calculated by the two different turbulent gas-particle codes have shown that the ${\kappa}-{\varepsilon}-Ap$ model results in a stronger diffusion of the flow momentum in the gas-particle turbulence interaction than the Eulerian multiphase model in FLUENT.

• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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• pp.57-72
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• 2003

This article provides integrated neural network models for the interest rate forecasting using change-point detection. The model is composed of three phases. The first phase is to detect successive structural changes in interest rate dataset. The second phase is to forecast change-point group with data mining classifiers. The final phase is to forecast the interest rate with BPN. Based on this structure, we propose three integrated neural network models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported neural network model, (2) case based reasoning (CBR)-supported neural network model and (3) backpropagation neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. For interest rate forecasting, this study then examines the predictability of integrated neural network models to represent the structural change.

• Knowledge Management Research
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• v.10 no.2
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• pp.35-48
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• 2009

The paper proposes a quantitative causal ordering map (QCOM) to combine qualitative and quantitative methods in a framework. The procedures for developing QCOM consist of three phases. The first phase is to collect partially known causal dependencies from experts and to convert them into relations and causal nodes of a model graph. The second phase is to find the global causal structure by tracing causality among relation and causal nodes and to represent it in causal ordering graph with signed coefficient. Causal ordering graph is converted into QCOM by assigning regression coefficient estimated from path analysis in the third phase. Experiments with the prediction model of Korea stock price show results as following; First, the QCOM can support the design of qualitative and quantitative model by finding the global causal structure from partially known causal dependencies. Second, the QCOM can be used as an integration tool of qualitative and quantitative model to offerhigher explanatory capability and quantitative measurability. The QCOM with static and dynamic analysis is applied to investigate the changes in factors involved in the model at present as well discrete times in the future.

• Journal of the military operations research society of Korea
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• v.25 no.2
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• pp.44-61
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• 1999

Cost estimation has posed a significant challenge to estimators, planners, and managers in both government and military. Considerable historical evidence shows that accurate cost estimation has been difficult to achieve across a wide range of projects, including weapon systems. This paper introduces new cost estimating concept, CAIV(Cost As an Independent Variable) and a cost estimating case study using PRICE model, computer aided parametric estimating models(CAPE) for K1 tank cost estimate. CAIV concept is to set realistic but aggressive cost objectives easily in each acquisition program and to achieve cost, schedule, and performance objectives considering various managing risks with a project manager and industry teams. The Price model is one of computer aided cost estimating models and widely used in U.S. defense system analysis as a tool for CAIV. We analyze theories, inputs, outputs of the PRICE model and present a case study for K1 tank to estimate costs in requirement and concept phase, program and budgeting phase, and life cycle phase. Finally we obtain results that the Price model can be used in various phases of PPBEES depending upon available data and time.

• Journal of the military operations research society of Korea
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• v.27 no.1
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• pp.10-27
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• 2001

This paper deals with the application of PRICE model in estimating the proper acquisition cost for weapon budgeting phase. The PRICE(Parametric Review of Information for Costing and Evaluation) Hardware model is a computerized method for deriving cost estimates of electronic and mechanical hardware assemblies and systems. The model can be used in obtaining not only initial cost estimates in conceptual phase, but also detailed cost estimates in budgeting phase depending on available historical and empirical data. We analyzed first step cost estimate parameters and derived cost equations using PRICe output dta. Using weight and complexity, We can find cost variation. Sensitivity analysis shows that cost increases exponentially as complexity increases exponentially as complexity increases. We estimated KAAV\`s (Korea Amphibious Assault Vehicle) production cost using the PRICE model and compare with engineering cost estimates which is based on actual production data submitted by the production company. The result shows that tow estimates are close within $\pm2%$ differences.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.5
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• pp.289-297
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• 1988

In this paper, the analysis of a generating torque characteristics of 2-phase induction motor driven with the phase control method is presented. The generating torque equations which represent average torque and pulsating torque are derived from the elementary machine model. The calculating equations which can get the values of average torque and pulsating torque is expressed by the parameters of the equivalent circuit of 2-phase induction motor. According to the calculating equations, these performance characteristics are investigated under various conditions. Finally, a strategy to eliminate non-linearity and pulsating torque generated in driving 2-phase induction motor with the phase control method is presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.196-204
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• 2002

The Sinusoidal Transform Coding(STC) is a vocoding scheme based on a sinusoidal model of a speech signal. The low bit-rate speech coding based on sinusoidal model is a method that models and synthesizes speech with fundamental frequency and its harmonic elements, spectral envelope and phase in the frequency region. In this paper, we propose the 2.4kbps low-rate speech coding algorithm using the sinusoidal model of a speech signal. In the proposed coder, the pitch frequency is estimated by choosing the frequency that makes least mean squared error between synthetic speech with all spectrum peaks and speech synthesized with chosen frequency and its harmonics. The spectral envelope is estimated using SEEVOC(Spectral Envelope Estimation VOCoder) algorithm and the discrete all-pole model. The phase information is obtained using the time of pitch pulse occurrence, i.e., the onset time, as well as the phase of the vocal tract system. Experimental results show that the synthetic speech preserves both the formant and phase information of the original speech very well. The performance of the coder has been evaluated in terms of the MOS test based on informal listening tests, and it achieved over the MOS score of 3.1.

• The KSFM Journal of Fluid Machinery
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• v.14 no.6
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• pp.45-53
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• 2011

Multiphase lattice Boltzmann method (LBM) has been used to simulate the nucleate pool boiling directly. For the phase change model, the thermal model and the Stefan boundary condition were introduced to the isothermal LBM. The phase change model was validated by the bubble growth in a superheated liquid under no gravity. The bubble growth on and departure from a superheated wall has been simulated successfully. The preliminary results showed that the detail process of nucleate pool boiling was in good agreement with the experimental results.