• Journal of Mechanical Science and Technology
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• v.14 no.1
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• pp.1-10
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• 2000

This work shows that it is possible to obtain information about more than one parameter from acoustic field information. A variety of ultrasonic Lamb wave modes were utilized to reconstruct thickness and density of an isotropic plate. An image reconstruction of one parameter (thickness of a plate) was carried out for four cases, i.e., the lowest symmetrical and anti symmetrical modes, and the fastest symmetrical and anti symmetrical Lamb waves among multiple modes. For two parameter reconstructions (thickness and density), the image processing was performed using the lowest symmetrical and antisymmetrical modes simultaneously. In this work, a modified version of algebraic reconstruction technique (ART), which is a form of finite-series expansion method, was employed to reconstruct the ultrasonically computed tomographic images. Results from several sample geometries are presented.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.4
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• pp.303-311
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• 2005

The problem of conjugate laminar film condensation of the pure saturated vapor in forced flow over a flat plate has been investigated as boundary layer solutions. A simple and efficient numerical method is proposed for its solution. The interfacial temperature is obtained as a root of 3rd order polynomial for laminar film condensation, and it is presented as a function of the conjugate parameter. The momentum and energy balance equations are reduced to a nonlinear system of ordinary differential equations with four parameters: the Prandtl number, Pr, Jacob number, $Ja^{\ast}$, defined by an overall temperature difference, a property ratio R and the conjugate parameter ${\zeta}$. The approximate solutions thus obtained reveal the effects of the conjugate parameter.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.3
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• pp.227-234
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• 2020

This paper presents the methods for the modeling and parameter optimization of the electric vehicle battery. The state variables of the battery are defined, and the test methods for battery parameters are presented. The state-space equation, which consists of four state variables, and the output equation, which is a combination of to-be-determined parameters, are shown. The parameter optimization method is the key point of this study. The least square of the modeling error can be used as an initial value of the multivariable function. It is equivalent to find the minimum value of the error function to obtain optimal parameters from multivariable function. The SIMULINK model is presented, and the 10-hour full operational range test results are shown to verify the performance of the model. The modeling error for 25 degrees is approximately 1% for full operational ranges. The comments to enhance modeling accuracy are shown in the conclusion.

• Korea-Australia Rheology Journal
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• v.21 no.4
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• pp.289-297
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• 2009

We numerically analyzed flow characteristics of the polymer melt in the screw equipment using a proper modeling and investigated design parameters which have influence on the mixing performance as the capability of the screw equipment. We considered the non-Newtonian and non-isothermal flow in a single rotor equipment to investigate the mixing performance with respect to screw dimensions as shape parameter of the single rotor equipment and screw speed as process parameter. We used Bird-Carreau-Yasuda model as a viscous model of the polymer melt and the particle tracking method to investigate the mixing performance in the screw equipment and considered four mixing performance indexes: residence time distribution, deformation rate, total strain and particle standard deviation as a new mixing performance index. We compared these indexes to determine design parameters and object function. On basis of the analysis results, we carried out the optimal design by using the response surface method and design of experiments. In conclusion, the differences of results between the optimal value and numerical analysis are about 5.0%.

• Structural Engineering and Mechanics
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• v.28 no.3
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• pp.263-280
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• 2008

Information on the distribution of the basic random variable is essential for the accurate analysis of structural reliability. The usual method for determining the distributions is to fit a candidate distribution to the histogram of available statistical data of the variable and perform approximate goodness-of-fit tests. Generally, such candidate distribution would have parameters that may be evaluated from the statistical moments of the statistical data. In the present paper, a cubic normal distribution, whose parameters are determined using the first four moments of available sample data, is investigated. A parameter table based on the first four moments, which simplifies parameter estimation, is given. The simplicity, generality, flexibility and advantages of this distribution in statistical data analysis and its significance in structural reliability evaluation are discussed. Numerical examples are presented to demonstrate these advantages.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.18-18
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• 2017

우리나라뿐만 아니라 세계의 여러 국가에서 과거 발생 했던 강수의 통계적 특성에서 벗어나는 극치사상이 빈번 하게 관측되고 있다. 이와 같은 현상에 가장 큰 영향을 미치고 있는 요인중 하나로서 지구온난화가 원인으로 고려되고 있으며 실제 산업화 이후 온실가스의 증가와 더불어 극한 기상현상의 발생 빈도가 증가하였다. 우리나라는 과거 발생패턴과는 다른 극치 강우 사상이 빈번하게 관측되고 있으며 이로 인한 피해도 증가되고 있는 상황이다. 이러한 점에서 기존의 연구에서 개발한 계절강수량을 입력 자료로 하여 극치강수량을 추정할 수 있는 비정상성 Four - Parameter(4P)-Beta분포를 이용한 알고리즘을 본 연구에서는 기상인자를 이용하여 모형 내에서 계절강수량을 직접적으로 예측할 수 있는 알고리즘을 추가하여, 이를 직접적으로 일단위 이하의 극치강수량을 상세화 시킬 수 있는 모형으로 확장하고자 하며, 이를 통해 기상변동성을 다양한 시간규모에서 고려하기 위한 정보로 활용하고자 하였다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.102-111
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• 1997

In this paper, a patern recognition method of surface mount device(SMD) IC using wavelet transform and neural network is proposed. We chose the feature parameter according to the characteristics of coefficient matrix which is obtained from four level discrete wavelet transform (DWT). These feature parameters are normalized and then used for the input vector of neural network which is capable of adapting the surroundings such as variation of illumination, arrangement of objects and translation. Experimental results show that when the same form of feature pattern, as is used for learning, is put into neural network and gained 100% rate ofrecognition irrespective of SMD IC kinds, location and variation of illumination. In the case of unused feature pattern for learning, the recognition rate is 85.9% under the similar surroundings, where as an average recognition rate is 96.87% for the case of reregulated value of illumination. Proosed method is relatively simple compared with the traditional space domain method in extracting the feature parameter and is also well suited for recognizing the pattern's class, position and existence. It can also shorten the processing tiem better than method extracting feature parameter with the use of discrete cosine transform(DCT) and adapt the surroundings such as variation of illumination, the arrangement and the translation of SMD IC.

• Journal of the Korean Electrochemical Society
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• v.6 no.3
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• pp.217-223
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• 2003

The present work is concerned with characterization of surface roughness and inhomogeneity of four kinds of hot-rolled carbon steels in terms of the fractal dimension and the depression parameter by using image analysis method and electrochemical impedance spectroscopy, respectively. From the analysis of the 3D AFM image, it is realized that all the hot-rolled steel surfaces show the self-affine fractal property. The values of the fractal dimension of the hot-rolled steels were determined by the analyses of the AFM images on the basis of both the perimeter-area method and the triangulation method. In addition, the Nyquist plots were found to be depressed from a perfect semicircle form. From the experimental findings, the changes in the values of the fractal dimension and the depression parameter with chemical composition have been discussed in terms of the change in the value of hardness of base steel.

• Structural Engineering and Mechanics
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• v.35 no.4
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• pp.431-457
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• 2010

This article provides a discussion of the mathematic modeling of connections for designing and qualifying structures, systems, and components subject to monotonic or cyclic loading. To characterize the force-deformation behavior of connections under monotonic loading, a review of the Ramberg-Osgood, Richard-Abbott, and Menegotto-Pinto models is conducted, and it is shown that these nonlinear functions can be mathematically derived by scaling up or down a linear force-deformation function. A generalized four-parameter model for simulating connection behavior is investigated to facilitate nonlinear regression analysis. In order to perform seismic analysis of frameworks, a hysteretic model accounting for loading, unloading, and reloading is described using the established monotonic model. For preliminary analysis, a method is provided to quickly determine the model parameters that fit approximately with the observed data. To reach more accurate values of the parameters, the methods of nonlinear regression analysis are investigated and the modified Levenberg-Marquardt and separable nonlinear least-square algorithms are applied in determining the model parameters. Example case studies illustrate the procedure for the computation through the use of experimental/analytical data taken form the literature. Transformation of connection curves from the three-parameter model to the four-parameter model for structural analysis is conducted based on the modeling of connections subject to fire.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.127-127
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• 2021

In order to estimate parameter uncertainty of hydrological models, the consideration of the likelihood functions which provide reliable parameters of model is necessary. In this study, the Bayesian Markov Chain Monte Carlo (MCMC) method with informal likelihood functions is used to analyze the uncertainty of parameters of the SURR model for estimating the hourly streamflow of Gunnam station of Imjin basin, Korea. Three events were used to calibrate and one event was used to validate the posterior distributions of parameters. Moreover, the performance of four informal likelihood functions (Nash-Sutcliffe efficiency, Normalized absolute error, Index of agreement, and Chiew-McMahon efficiency) on uncertainty of parameter is assessed. The indicators used to assess the uncertainty of the streamflow simulation were P-factor (percentage of observed streamflow included in the uncertainty interval) and R-factor (the average width of the uncertainty interval). The results showed that the sensitivities of parameters strongly depend on the likelihood functions and vary for different likelihood functions. The uncertainty bounds illustrated the slight differences from various likelihood functions. This study confirms the importance of the likelihood function selection in the application of Bayesian MCMC to the uncertainty assessment of the SURR model.