• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.1
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• pp.9-16
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• 2014

Using a level set method and topological derivatives, a topological shape optimization method that is independent of an initial design is developed for linearly elastic structures. In the level set method, the initial domain is kept fixed and its boundary is represented by an implicit moving boundary embedded in the level set function, which facilitates to handle complicated topological shape changes. The "Hamilton-Jacobi(H-J)" equation and computationally robust numerical technique of "up-wind scheme" lead the initial implicit boundary to an optimal one according to the normal velocity field while minimizing the objective function of compliance and satisfying the constraint of allowable volume. Based on the asymptotic regularization concept, the topological derivative is considered as the limit of shape derivative as the radius of hole approaches to zero. The required velocity field to update the H-J equation is determined from the descent direction of Lagrangian derived from optimality conditions. It turns out that the initial holes are not required to get the optimal result since the developed method can create holes whenever and wherever necessary using indicators obtained from the topological derivatives. It is demonstrated that the proper choice of control parameters for nucleation is crucial for efficient optimization process.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.665-679
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• 2017

When measuring productive efficiency, often it is necessary to have knowledge of the production frontier function that shows the maximum possible output of production units as a function of inputs. Canonical parametric forms of the frontier function were initially considered under the framework of stochastic frontier model; however, several additional nonparametric methods have been developed over the last decade. Efforts have been recently made to impose shape constraints such as monotonicity and concavity on the non-parametric estimation of the frontier function; however, most existing methods along that direction suffer from unnecessary non-smooth points of the frontier function. In this paper, we propose methods to estimate the smooth frontier function with monotonicity for stochastic frontier models and investigate the effect of imposing a monotonicity constraint into the estimation of the frontier function and the finite dimensional parameters of the model. Simulation studies suggest that imposing the constraint provide better performance to estimate the frontier function, especially when the sample size is small or moderate. However, no apparent gain was observed concerning the estimation of the parameters of the error distribution regardless of sample size.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.2
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• pp.8-14
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• 1996

Key stream generator consisting of several linear feedback shift registers with a nonlinear combining function have been applied in stream cipher system. Most of the papers until now have been focusing on correlation atack and analysis of key stream generator with nonlinear combining function. Given some part of key stream sequences. We can generate identical output sequences with original key stream sequences if the feedback connection and the maximum order of nonlinear combination function are known.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.9-14
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• 2003

본 연구에서는 원격탐사 화상의 분류를 목적으로 분광정보와 공간적 상관성의 반복적 결합방법을 제안하였다. 퍼지이론을 기반으로 공간적 상관성을 분류 과정에 적용하기 위하여 초기단계에서 정의된 소속 함수에 대해서 주변영역에 대한 필터링을 적용하였고, 특정 수렴 조건을 만족하는 단계까지 반복적 결합을 수행하였다. Landsat TM 화상에 적용한 결과, 향상된 분류정확도와 분광정보만으로 분류가 애매한 화소의 공간적 분포 양상을 확인할 수 있었다.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.247-249
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• 2005

UTM-02 모델의 초기형상을 기반으로 차체 프레임 구조물에 대한 경량화 설계를 수행하였다. 전체 프레임을 14개의 부재로 나누었으며, 부재 두께를 설계변수로 정하였다. 효율적인 설계최적화를 수행하기 위하여 반응면기법을 이용하였다. 반응면기법을 통해 근사된 목적함수와 제한조건을 이용하여 최적화를 수행하였으며 각 설계변수들에 대한 감도도 산출하였다.

• Solar Energy
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• v.10 no.3
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• pp.35-45
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• 1990

An analytical equation to estimate the Rankine power cycle efficiency at maximum power for the given mass flow rates of heating and cooling fluids is derived. The accuracy of the result is shown by comparing the analytical values with those calculated one using detailed thermodynamic data. The results indicate that the thermal efficiency at maximum power depends primarily on the initial temperatures of the heating and cooling fluids, and it also depends on the pinch-temperature differences between the working fluid and the heating and cooling fluids. The efficiency at maximum power provides a measure of the power available in a practical Rankine heat engine.

• Journal of the Korean Wood Science and Technology
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• v.2 no.2
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• pp.5-7
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• 1974

1. This study indicates that above the fiber saturation point the drying rate can be increased with increasing the velocity of the air circutation, i.e., the drying rate of sample boards is proportional to the air velocity, but below the fiber saturation point, the effect of the velocity of air circulation is very low as shown in Figs. 1 and 2. 2. Under the controlled temperature and humidity in the kiln, the more the sample boards have moisture, the higher drying rate of it can be obtained. In other words, this means that even though in the case of drying various moisture content of wood, at the final drying stage, approximately the same percentage of moisture content of wood can be secured by employing the higher velocity of air circulation. 3. This study shows that the rate of drying in kiln changes distinctly at the fiber saturation point, i, e., above the fiber saturation point, the drying curve shows concave aginst the X axsis, but below the fiber saturation point, in the range from 30 percent of moisture content to 20 percent of moisture content, the curve shows convex as shown in Fig. 3. As the drying progresses, however, the drying curve shows concave again below 20 percent of moisture content. This means that inflection point of drying curve may be located clearly at the fiber saturation point, i.e., 30 percent of moisture content. As mentioned above, the 30 percent of moisture content of wood at which the inflectional point appears can be recognized as a critical point, i. e., the fiber saturation point at which all free water was removed from wood. The existence of inflectional point indicates that the evaporation of hygroscopic water in a cell wall is more difficult than the evaporation of free water in a cell cavity and the minor space of cell wall. The convex curve in the range of moisture content from 30 percent to 20 percent means that the evaporation of capillary condensed water has a tendency of the same rates of drying approximately, but as approaching to the 20 percent of moisture, the transfusion of moisture from wood becomes difficult because of having less moisture in cell wall. Below 20 percent of moisture content, the drying curve shows concave again, which means that it is difficult to remove the moisture located nearer to the surface of cellulose molecules and the surface bound water. These relations were revealed in Fig. 4. In comparison AC curve which does not have the two inflection points with BD curve which has two inflection points, i.e., Band D, they are mentioned already, by existence of the inflection points, the curve BD shows that the change of drying rate in the interval from 20 percent of moisture content to 30 percent of moisture content is not greater than in the case of the curve AC in the same interval. At the inflection point of 30 percent of moisture content, it can be noticed that the changing of the drying rate is very conspicuous. This phenomenon also can be recognized, as it is noticed by the Fig. 3, the drying rate from green to 30 percent of moisture content is very great. But the inclination of the curve is very slow from 30 percent of moisture content to 20 percent of moisture content, i.e., the inclination of the curve becomes almost horizontal lines. Acknowledgments Gratitude is expressed to Fred E. Dickinson, Professor of 'Wood Technology, School of Natural Resources, University of Michigan, USA for his suggestion to carry out this study.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.1
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• pp.26-35
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• 1987

As an attempt to make the multi-objection for the line design of the rope way, the resulted formulas from the catenary curve as exact ones were summarized, and it was found out that the Kuhn-Tucker's optimality conditions and regions of the objective functions can analytically be expressed with dimensionless parameters. The Pareto's optimum solution set was analytically obtained through the objective function-the minimum relation of $W^{*}$, and $W^{*}$ is a trade-off relation. From this, The dimension of a rope and the value of an initial tension that are the standard in design of the rope way were determined. It was concluded that $V^{*}$ should become minimum, and that the ratio of the dimension of rope to the value of and initial tension become larger than superposition factor corresponding to curve AB.to curve AB.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.414-414
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• 2015

최근 지구온난화로 인한 기상변동성 증가로 인해 극한기후현상의 발생빈도가 점차 증가하고 있으며 유역단위의 수자원을 효율적으로 운영하는데 문제점을 해소하고자 다양한 측면에서 체계적인 수자원 운영을 위한 연구가 이루어지고 있다. 수공구조물을 설계하는데 있어서 가장 일반적인 가정 사항은 수문모형에 사용되는 강우의 빈도와 유출의 빈도가 동일하다는 가정에 근거한다. 즉, 유역의 초기함수조건, 강우강도, 강우의 시간적 분포와 관계없이 동일한 빈도로 고려되는 문제점이 있다. 이러한 점에서 비교적 장기간의 자료를 확보하고 있는 계측유역에 대해서 다변량 확률밀도함수를 적용하여 비선형관계를 고려한 수문빈도해석기법을 개발하고자 한다. 본 연구에서는 이변량 분석기법(bivariate analysis) 중 전통적인 이변량 분포에 비해 주변분포형(marginal distribution)을 자유롭게 선택할 수 있는 장점이 있는 추계학적 Copula 모형을 활용하여 댐 및 저수지 상류유역의 강우량과 유입량을 대상으로 이변량 분석을 수행하고자 한다. 최종적으로 비선형 관계에 있는 강수량과 유출량 사이에 이변량 빈도해석 모형을 개발하고 기존 해석방법과의 종합적인 비교를 실시하였다.

• Geophysics and Geophysical Exploration
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• v.26 no.3
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• pp.114-125
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• 2023

The physics-informed neural network (PINN) has been proposed to overcome the limitations of various numerical methods used to solve partial differential equations (PDEs) and the drawbacks of purely data-driven machine learning. The PINN directly applies PDEs to the construction of the loss function, introducing physical constraints to machine learning training. This technique can also be applied to wave equation modeling. However, to solve the wave equation using the PINN, second-order differentiations with respect to input data must be performed during neural network training, and the resulting wavefields contain complex dynamical phenomena, requiring careful strategies. This tutorial elucidates the fundamental concepts of the PINN and discusses considerations for wave equation modeling using the PINN approach. These considerations include spatial coordinate normalization, the selection of activation functions, and strategies for incorporating physics loss. Our experimental results demonstrated that normalizing the spatial coordinates of the training data leads to a more accurate reflection of initial conditions in neural network training for wave equation modeling. Furthermore, the characteristics of various functions were compared to select an appropriate activation function for wavefield prediction using neural networks. These comparisons focused on their differentiation with respect to input data and their convergence properties. Finally, the results of two scenarios for incorporating physics loss into the loss function during neural network training were compared. Through numerical experiments, a curriculum-based learning strategy, applying physics loss after the initial training steps, was more effective than utilizing physics loss from the early training steps. In addition, the effectiveness of the PINN technique was confirmed by comparing these results with those of training without any use of physics loss.