• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1992.06a
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• pp.77-81
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• 1992

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.661-664
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• 2007

본 논문은 화학분리공정 중의 하나인 회분식 흡착공정의 시뮬레이션 방법에 관한 것으로, 편미분방정식을 이용한 회분식 흡착공정 시뮬레이션 방법에 있어서, 편미분방정식 해석기법인 CE/SE 방법(Conservation element and Solution element method)을 사용하여 흡착공정의 모델식을 수치해석하고, 이를 그래픽 사용자 인터페이스(Graphical User Interface) 방식에 의한 사용자편이성이 구현된 회분식 흡착공정 시뮬레이터의 설계와 구현에 관한 것이다. 본 연구를 통하여 공정모델선택 과정에서부터 시뮬레이션 결과의 시각화를 포함하는 결과 처리 과정까지의 작업을 사용자가 독립된 하나의 통합된 환경에서 회분식 흡착공정을 편리하게 시뮬레이션 할 수 있으며, 빠른 시간 안에 정확한 수치해를 구할 수 있게 되었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.501-507
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• 2021

Neural networks with differentiable activation functions are differentiable with respect to input variables. We improve the approximation capability of neural networks by using the gradient and Hessian of neural networks to satisfy the differential equations of the problems of interest. We apply differential neural networks to the pricing of financial options, where stochastic differential equations and the Black-Scholes partial differential equation represent the differential relation of price of option and underlying assets, and the first and second derivatives of option price play an important role in financial engineering. The proposed neural network learns - (a) the sample paths of option prices generated by stochastic differential equations and (b) the Black-Scholes equation at each time and asset price. Experimental results show that the proposed method gives accurate option values and the first and second derivatives.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2594-2596
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• 2003

유한요소법(FEM)은 많은 공학문제를 해결하는 가장 중요한 방법 중 하나로 인식되고 있다. 본 논문에서는 자동제어 및 신호처리 문제해결에 효율적이며 강력한 수치해석 패키지인 CEMTool환경에서 유한요소법을 이용하여 일반적인 편미분방정식 Solver 구현에 관한사항을 논의하고자 한다. 기본적으로 영역정보 및 노드수 등의 정보를 입력받아 각 노드의 정보를 출력하는 Mesh함수를 구현하며, 생성된 요소방정식들을 조립하는 Assemble함수를 작성한 뒤, Boundary함수를 통해 경계조건을 적용시킨 후 선형행렬 방정식을 풀어 전체노드의 값을 찾아내는 Solve함수를 구현하는 과정을 알아본다. 구현된 FEM Solver의 전체적인 구조를 통해 구현시 고려해야 할 사항을 논의하며 기본적인 편미분방정식의 예제를 통해 FEM PDE Solver의 동작과정을 검증할 것이다.

• Convergence Security Journal
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• v.5 no.3
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• pp.93-97
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• 2005

MacCormack's method is an explicit, second order finite difference scheme that is widely used in the solution of hyperbolic partial differential equations. Apparently, however, it has shown entropy violations under small discontinuity. This non-physical shock grows fast and eventually all the meaningful information of the solution disappears. Some modifications of MacCormack's methods follow ideas of central schemes with an advantage of second order accuracy for space and conserve the high order accuracy for time step also. Numerical results are shown to perform well for the one-dimensional Burgers' equation and Euler equations gas dynamic.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.4
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• pp.427-436
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• 2000

This study presents the nonlinear responses of a hinged-clamped beam under broadband random excitation. By using Galerkin's method the governing equation is reduced to a system or nonautonomous nonlinear ordinary differential equations. The Fokker-Planck equation is used to generate a general first-order differential equation in the joint moments of response coordinates. Gaussian and non-Gaussian closure schemes are used to close the infinite coupled moment equations. The closed equations are then solved for response statistics in terms of system and excitation parameters. The case of two mode interaction is considered in order to compare it with the case of three mode interaction. Monte Carlo simulation is used for numerical verification.

• Clean Technology
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• v.10 no.1
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• pp.9-17
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• 2004

Direct methanol fuel cell(DMFC) with proton exchange membrane (PEM) has advantages over the conventional power source (e.g. vehicle). DMFC, however, has a problem to be solved such as methanol crossover, high anodic overpotential and limiting current density, etc. The physicochemical phenomena in DMFC can be described by coupled PDEs (partial differential equations), which can be solved by a PDE solver. In this paper, we utilized a commercial software FEMLAB to solve the PDEs. The FEMLAB is one of the software programs available which are developed as a solver for building physics problems based on PDEs and is designed to simulate systems of coupled PDEs which may be 1D, 2D, 3D, non-liner and time dependent. We performed simulation using the Tafel equation as an electrochemical reaction model to analyze methanol concentration profile in DMFC system. We confirm that the rapid decrease of methanol concentration at anodic catalyst layer with the increase of the current density is a main reason of the low performance in DMFC through simulation results.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.7
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• pp.553-564
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• 1990

The co-efficient matrix of linear second-order partial differential equations in the general form is partitioned with (n-1)x(n-1) submartices and is transformed into the block tridiagonal system. Then the cyclic odd-even reduction technique is applied to this system with the large-grain data granularity and the block cyclic reduction algorithm to solve unknown vectors of this system is created. But this block cyclic reduction technique is not suitable for the parallel processing system because of its parallelism chanigng at every computing stages. So a new algorithm for solving linear second-order partical differential equations is presentes by the block cyclic reduction technique which is modified in order to keep its parallelism constant, and to reduce gteatly its execution time. Both of these algoriths are compared and studied.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.6
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• pp.82-88
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• 2001

This paper considers the problem of the identification of the time invariant parameters of distributed systems. In general, the parameters are identified by using the CBPOM(Conventional Block Pulse Operational Matrices), but in this paper, the parameters ard identified by using the EBPOMS(Extended Block Pulse Operational Matrices) which can reduce the burden of operation md the volume of error caused by matrices multiplication. The simulation cloves the effectiveness of the proposed method.