• Title/Summary/Keyword: model-based method

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Development of Two Dimensional Chloride Ion Penetration Model Using Moving Mesh Technique (Moving Mesh Technique을 이용한 2차원 염해 침투 예측 모델의 개발)

  • Choi, Won;Kim, Hanjoong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.57 no.6
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    • pp.1-7
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    • 2015
  • Most of chloride diffusion models based on finite difference method (FDM) could not express the diffusion in horizontal direction at each elevation. To overcome these weakness, two dimensional chloride ion penetration model based on finite element method (FEM) to be able to combine various multi-physics simultaneously was suggested by introducing moving mesh technique. To avoid the generation of mesh being able to be distorted depending on the relative movement of water level to static concrete, a rectangular type of mesh was intentionally adopted and the total number of meshes was empirically selected. The simulated results showed that the contents of surface chloride decreased following to the increase of elevation in the top part of low sea level, whereas there were no changes in the bottom part of low level. In the DuraCrete model, the diffusion coefficient of splashed zone is generally smaller than submerged zone, whereas the trend of Life365 model is reverse. Therefore, it could be understood that the developed model using moving mesh technique effectively reflects $DuraCrete^{TM}$ model rather than $Life365^{TM}$ model. In the future, the model will be easily expanded to be combined with various multi-physics models considering water evaporation, heat of hydration, irradiation effect of sun and so on because it is based on FEM.

Modified Tikhonov regularization in model updating for damage identification

  • Wang, J.;Yang, Q.S.
    • Structural Engineering and Mechanics
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    • v.44 no.5
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    • pp.585-600
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    • 2012
  • This paper presents a Modified Tikhonov Regularization (MTR) method in model updating for damage identification with model errors and measurement noise influences consideration. The identification equation based on sensitivity approach from the dynamic responses is ill-conditioned and is usually solved with regularization method. When the structural system contains model errors and measurement noise, the identified results from Tikhonov Regularization (TR) method often diverge after several iterations. In the MTR method, new side conditions with limits on the identification of physical parameters allow for the presence of model errors and ensure the physical meanings of the identified parameters. Chebyshev polynomial is applied to approximate the acceleration response for moderation of measurement noise. The identified physical parameter can converge to a relative correct direction. A three-dimensional unsymmetrical frame structure with different scenarios is studied to illustrate the proposed method. Results revealed show that the proposed method has superior performance than TR Method when there are both model errors and measurement noise in the structure system.

Information-based NPD Organization Design : A Case Study (정보기반의 신제품개발 조직설계 : 사례 연구)

  • 안효정;김영배
    • Korean Management Science Review
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    • v.16 no.2
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    • pp.13-32
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    • 1999
  • Concurrent Engineering is one of the information-based product development approach. Yet, the method of organizing the project team for the concurrent engineering is not clear. This study focuses on deriving a method to organize an information-based project team. The model consists of 4 layers : IT infrastructure, organization of the information-based project team, operation of the project team, an organization culture. Based on an analysis of new product development case, this study attempts to verify the model and to suggest more effective way of organization design and management for new product development.

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Comparative Study on Proposed Simulation Based Optimization Methods for Dynamic Load Model Parameter Estimation (동적 부하모델 파라미터 추정을 위한 시뮬레이션 기반 최적화 기법 비교 연구)

  • Del Castillo, Manuelito Jr.;Song, Hwa-Chang;Lee, Byong-Jun
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.187-188
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    • 2011
  • This paper proposes the hybrid Complex-PSO algorithm based on the complex search method and particle swarm optimization (PSO) for unconstrained optimization. This hybridization intends to produce faster and more accurate convergence to the optimum value. These hybrid will concentrate on determining the dynamic load model parameters, the ZIP model and induction motor model parameters. Measurement-based parameter estimation, which employs measurement data to derive load model parameters, is used. The theoretical foundation of the measurement-based approach is system identification. The main objective of this paper is to demonstrate how the standard particle swarm optimization and complex method can be improved through hybridization of the two methods and the results will be compared with that of their original forms.

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Static Equivalent Model of Inverter-based Distributed Energy Resource for Fault Analysis of Power Distribution Grid

  • Kim, Dong-Eok;Cho, Namhun;Yang, Seung-Kwon
    • KEPCO Journal on Electric Power and Energy
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    • v.2 no.4
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    • pp.569-575
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    • 2016
  • In this paper, we propose a method to develop a static equivalent model of an inverter-based distributed energy resource (DER), where the model is used for a steady-state fault analysis of a power grid. First, we introduce the characteristics of an inverter-based DER as well as its general configuration. Then, we derive the equivalent model of the DER on the basis of the characteristics. Last, the performance of the proposed method is proven by the results of computer simulations.

Design of PID Controller to Ensure Specified Phase margin and Iso-damping property Using Reduction Model (축소 모델을 이용한 위상여유와 등 제동 특성을 만족하는 PID 제어기 설계)

  • Cho, Joon-Ho;Hwang, Hyung-Soo
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.113-118
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    • 2007
  • In this paper, a new method is proposed for robust proportional- integral - derivative (PID) control that is to ensure specified phase margin and iso - damping property using reduction model. This method is based on the second order plus dead time(SOPDT) reduction model of the high order model. Reduction model used to ensure iso-damping property in the feature frequency. Simulation results gives proof of effectiveness of proposed method.

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MapReduce-based Localized Linear Regression for Electricity Price Forecasting (전기 가격 예측을 위한 맵리듀스 기반의 로컬 단위 선형회귀 모델)

  • Han, Jinju;Lee, Ingyu;On, Byung-Won
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.67 no.4
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    • pp.183-190
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    • 2018
  • Predicting accurate electricity prices is an important task in the electricity trading market. To address the electricity price forecasting problem, various approaches have been proposed so far and it is known that linear regression-based approaches are the best. However, the use of such linear regression-based methods is limited due to low accuracy and performance. In traditional linear regression methods, it is not practical to find a nonlinear regression model that explains the training data well. If the training data is complex (i.e., small-sized individual data and large-sized features), it is difficult to find the polynomial function with n terms as the model that fits to the training data. On the other hand, as a linear regression model approximating a nonlinear regression model is used, the accuracy of the model drops considerably because it does not accurately reflect the characteristics of the training data. To cope with this problem, we propose a new electricity price forecasting method that divides the entire dataset to multiple split datasets and find the best linear regression models, each of which is the optimal model in each dataset. Meanwhile, to improve the performance of the proposed method, we modify the proposed localized linear regression method in the map and reduce way that is a framework for parallel processing data stored in a Hadoop distributed file system. Our experimental results show that the proposed model outperforms the existing linear regression model. Specifically, the accuracy of the proposed method is improved by 45% and the performance is faster 5 times than the existing linear regression-based model.

Livestock Anti-theft System Using Morphological Feature-based Model (형태학적 특징 기반 모델을 이용한 가축 도난 판단 시스템)

  • Kim, Jun Hyoung;Joo, Yung Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.4
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    • pp.578-585
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    • 2018
  • In this paper, we propose a classification and theft detection system for human and livestock for various moving objects in a barn. To do this, first, we extract the moving objects using the GMM method. Second, the noise generated when extracting the moving object is removed, and the moving object is recognized through the labeling method. And we propose a method to classify human and livestock using model formation and color for the unique form of the detected moving object. In addition, we propose a method of tracking and overlapping the classified moving objects using Kalman filter. Through this overlap determination method, an event notifying a dangerous situation is generated and a theft determination system is constructed. Finally, we demonstrate the feasibility and applicability of the proposed system through several experiments.

Computational view-point reconstruction method in three-dimensional integral imaging using lenslet array model (렌즈배열 모델을 적용한 3차원 집적영상 기술에서의 컴퓨터적 시점 재생 방법)

  • Shin, Dong-Hak;Kwon, Young-Man;Kim, Eun-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.10
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    • pp.1848-1853
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    • 2006
  • In this paper, we propose a method to reconstruct resolution-improved 3D images computationally based on lenslet array model in integral imaging technique and analyze its performance. While conventional view-point reconstruction method has low resolution based on pinhole array model, the proposed method can obtain resolution-improved 3D images because of extracting multiple pixels from elemental images by use of lenslet way model. To show the usefulness of proposed method, we perform computational experiments and present its results.

Precise Edge Detection Method Using Sigmoid Function in Blurry and Noisy Image for TFT-LCD 2D Critical Dimension Measurement

  • Lee, Seung Woo;Lee, Sin Yong;Pahk, Heui Jae
    • Current Optics and Photonics
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    • v.2 no.1
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    • pp.69-78
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    • 2018
  • This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.