• Structural Engineering and Mechanics
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• 제28권2호
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• pp.129-152
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• 2008

This paper considers the solution of the stochastic differential equations (SDEs) with random operator and/or random excitation using the spectral SFEM. The random system parameters (involved in the operator) and the random excitations are modeled as second order stochastic processes defined only by their means and covariance functions. All random fields dealt with in this paper are continuous and do not have known explicit forms dependent on the spatial dimension. This fact makes the usage of the finite element (FE) analysis be difficult. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used to represent these processes to overcome this difficulty. Then, a spectral approximation for the stochastic response (solution) of the SDE is obtained based on the implementation of the concept of generalized inverse defined by the Neumann expansion. This leads to an explicit expression for the solution process as a multivariate polynomial functional of a set of uncorrelated random variables that enables us to compute the statistical moments of the solution vector. To check the validity of this method, two applications are introduced which are, randomly loaded simply supported reinforced concrete beam and reinforced concrete cantilever beam with random bending rigidity. Finally, a more general application, randomly loaded simply supported reinforced concrete beam with random bending rigidity, is presented to illustrate the method.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 가을 학술발표회 논문집
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• pp.11-18
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• 2004

In this paper, an efficient model reduction scheme is presented for large scale dynamic systems. The method is founded on a modal analysis in which optimal eigenvalue is extracted from time samples of the given system response. The techniques we discuss are based on classical theory such as the Karhunen-Loeve expansion. Only recently has it been applied to structural dynamics problems. It consists in obtaining a set of orthogonal eigenfunctions where the dynamics is to be projected. Practically, one constructs a spatial autocorrelation tensor and then performs its spectral decomposition. The resulting eigenfunctions will provide the required proper orthogonal modes(POMs) or empirical eigenmodes and the correspondent empirical eigenvalues (or proper orthogonal values, POVs) represent the mean energy contained in that projection. The purpose of this paper is to compare the reduced order model using Karhunen-Loeve expansion with the full model analysis. A cantilever beam and a simply supported plate subjected to sinusoidal force demonstrated the validity and efficiency of the reduced order technique by K-L method.

• Architectural research
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• 제10권2호
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• pp.21-26
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• 2008

The number of measured degrees of freedom for detecting the damage of any structures is usually less than the number of model degrees of freedom. It is necessary to expand the measured data to full set of model degrees of freedom for updating modal data. This study presents the expansion methods to estimate all static displacements and dynamic modal data of finite element model from the measured data. The static and dynamic methods are derived by minimizing the variation of the potential energy and the Gauss's function, respectively. The applications illustrate the validity of the proposed methods. It is observed that the numerical results obtained by the static approach correspond with the Guyan condensation method and the derived static and dynamic approaches provide the fundamental idea for damage detection.

• Journal of Astronomy and Space Sciences
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• 제27권4호
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• pp.359-366
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• 2010

In this study, we developed a global ionosphere model based on measurements from a worldwide network of global positioning system (GPS). The total number of the international GPS reference stations for development of ionospheric model is about 100 and the spherical harmonic expansion approach as a mathematical method was used. In order to produce the ionospheric total electron content (TEC) based on grid form, we defined spatial resolution of 2.0 degree and 5.0 degree in latitude and longitude, respectively. Two-dimensional TEC maps were constructed within the interval of one hour, and have a high temporal resolution compared to global ionosphere maps which are produced by several analysis centers. As a result, we could detect the sudden increase of TEC by processing GPS observables on 29 October, 2003 when the massive solar flare took place.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.172-176
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• 1989

In this paper, a simple method for designing iterative learning control scheme is proposed. The proposed learning algorithm is designed based on series expansion of inverse plant model. The proposed scheme has simple structure and fast convergency so that it is suitable for implementing it on conventional micro processor based controllers. The effectiveness of the proposed algorithm is investigated through a series of computer simulations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.793-796
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• 1996

This study proposes a new algorithm which performs a production simulation under various constraints and maintains computational efficiency. In order to consider the environmental and operational constraints, the proposed algorithm is based on optimization techniques formulated in LP form In the algorithm, "system characteristic constraints" reflect the system characteristics such as LDC shape, unit loading order and forced outage rate. By using the concept of Energy Invariance Property and two operational rules i.e. Compliance Rule for Emission Constraint, Compliance Rule for Limited Energy of Individual Unit, the number of system characteristic constraints is appreciably reduced. As a solution method of the optimization problem, the author uses Karmarkar's method which performs effectively in solving large scale LP problem. The efficiency of production simulation is meaningful when it is effectively used in power system planning. With the proposed production simulation algorithm, an optimal expansion planning model which can cope with operational constraints, environmental restriction, and various uncertainties is developed. This expansion planning model is applied to the long range planning schemes by WASP, and determines an optimal expansion scheme which considers the effect of supply interruption, load forecasting errors, multistates of unit operation, plural limited energy plants etc.

• Smart Structures and Systems
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• 제29권2호
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• pp.321-336
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• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• 한국소음진동공학회논문집
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• 제21권7호
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• pp.665-673
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• 2011

Simplified formulae for axial and bending natural frequencies of a bellows are developed using an equivalent thin-walled pipe model. The axial and bending stiffness of bellows is determined using lumped transfer matrix method. Transfer matrix method which includes the rotary inertia is used to calculate the natural frequencies for axial and lateral vibration. The result from the simplified formula are verified by those from as experiment result and a finite element analysis. This comparisons show good agreement with the each other.

• 한국수자원학회논문집
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• 제35권1호
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• pp.91-96
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• 2002

본 연구에서는 경계요소법을 이용하여 비스듬히 입사하는 파랑의 반사에 대하여 다루었으며, 비스듬히 입사하는 파랑이 정현파형 지형을 통과하는 경우 그 때의 반사율과 Bragg반사에 대하여 조사하였다. 특히, 비스듬히 입사하는 파랑의 Bragg반사를 발생시키는 파수를 계산하여 이론적인 결과와 비교하였다. 해석결과의 검증을 위하여 고유 함수전개법에 의한 정현파형 지형의 반사율과 본 모형의 결과를 비교하였으며, 전체적으로 본 연구의 결과는 기존의 연구결과들과 비교적 양호하게 일치하였다.

• 대한기계학회논문집B
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• 제22권12호
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• pp.1669-1680
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• 1998

A method is developed to include the effect of volume expansion in the description of the flame dynamics using G-equation. Line volume-source is used to represent the effect of the exothermic process of combustion with source strength assigned by the density difference between the burned and the unburned region. The present model provides good agreement with the experimental results. Including volume expansion, the flow field is adjusted to accommodate the increased volume flow rate which crossing the flame front and the result predicts the same behavior of measured velocity field qualitatively. The effect of increasing volume expansion does not change the initial growth rate of flame area but increase the residence time. Consequently this effect increases the maximum area of flame front. The flame propagation in varying flow field due to volume expansion provides a promising way to represent the wrinkled turbulent premixed flames in a numerically efficient manner.