• 대한전기학회논문지:전력기술부문A
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• 제54권2호
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• pp.67-72
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• 2005

In conventional small signal stability analysis, system is assumed to be invariant and the state space equations are used to calculate the eigenvalues of state matrix. However, when a system contains switching elements such as FACTS devices, it becomes non-continuous system. In this case, a mathematically rigorous approach to system small signal stability analysis is by means of eigenvalue analysis of the system periodic transition matrix based on discrete system analysis method. In this paper, RCF(Resistive Companion Form) method is used to analyse small signal stability of a non-continuous system including switching elements. Applying the RCF method to the differential and integral equations of power system, generator, controllers and FACTS devices including switching elements should be modeled in the form of state transition equations. From this state transition matrix eigenvalues which are mapped to unit circle can be calculated.

• International Journal of Precision Engineering and Manufacturing
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• 제3권3호
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• pp.44-49
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• 2002

A study of free vibration of axisymmetric circular plates based on Mindlin theory using a pseudospectral method is presented. The analysis is based on Chebyshev polynomials that are widely used in the fluid mechanics research community. Clamped, simply supported and flee boundary conditions are considered, and numerical results are presented for various thickness-to-radius ratios.

• 대한기계학회논문집A
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• 제32권11호
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• pp.930-936
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• 2008

This paper studies the effect of pad at initial stage and wear during braking on the dynamic contact pressure distribution. Wear is influenced by variable factor (contact pressure, sliding speed, radius, temperature) during dynamic braking and variation in contact pressure distribution. Many researchers have conducted complex eigenvalue analysis considering wear characteristic with Lim and Ashby wear map. The conventional analysis method is assumed the pad has smooth and flat surfaces. The purpose of this paper is to validate that wear rate induced by braking is considered for the precise squeal prediction. After obtaining pad wear from experiment, it is incorporated with FE model of brake system. Finally, the comparisons in fugitive nature of squeal will be carried out between the complex eigenvalue analysis and noise dynamometer experiment.

• KIEE International Transactions on Power Engineering
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• 제4A권2호
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• pp.79-83
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• 2004

A new small signal stability analysis method for eigenvalue analysis is presented. This method utilizes the Resistive Companion Form (RCF) for the computation of the transition matrix over a specified time interval, which corresponds to a single cycle operation of the system. This method is applicable to any system, with or without switching element. An illustrative example of the method is presented and the eigenvalues are compared with those of the conventional state space method (analog) in order to demonstrate the accuracy of the proposed eigenvalue analysis method. Also, the variations of oscillation modes that are caused by the switching operation can be precisely analyzed using this method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.602-603
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• 2007

In this paper, the RCF method is applied to analyze small signal stability of power systems including thyristor controlled FACTS equipments such as SVC. The eigenvalue sensitivity analysis algorithm in discrete systems by the RCF method are presented and applied to the power system including SVC. As a result of simulation, the RCF analysis method is very powerful to calculate the newly generated unstable oscillation modes precisely after periodic switching operations of SVC. Also the RCF analysis method enabled to precisely calculate eigenvalue sensitivity coefficients of dominant oscillation modes after periodic switching operations. These simulation results are very different from those of the conventional continuous system analysis method such as the state space equation method.

• Wind and Structures
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• 제10권1호
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• pp.61-82
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• 2007

This paper presents a novel finite element (FE) model for analyzing coupled flutter of long-span bridges using the commercial FE package ANSYS. This model utilizes a specific user-defined element Matrix27 in ANSYS to model the aeroelastic forces acting on the bridge, wherein the stiffness and damping matrices are expressed in terms of the reduced wind velocity and flutter derivatives. Making use of this FE model, damped complex eigenvalue analysis is carried out to determine the complex eigenvalues, of which the real part is the logarithm decay rate and the imaginary part is the damped vibration frequency. The condition for onset of flutter instability becomes that, at a certain wind velocity, the structural system incorporating fictitious Matrix27 elements has a complex eigenvalue with zero or near-zero real part, with the imaginary part of this eigenvalue being the flutter frequency. Case studies are provided to validate the developed procedure as well as to demonstrate the flutter analysis of cable-supported bridges using ANSYS. The proposed method enables the bridge designers and engineering practitioners to analyze flutter instability by using the commercial FE package ANSYS.

• Nuclear Engineering and Technology
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• 제49권6호
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• pp.1259-1268
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• 2017

The alpha eigenvalue problem in multigroup neutron diffusion is studied with particular attention to the theoretical analysis of the model. Contrary to previous literature results, the existence of eigenvalue and eigenflux clustering is investigated here without the simplification of a unique fissile isotope or a single emission spectrum. A discussion about the negative decay constants of the neutron precursors concentrations as potential eigenvalues is provided. An in-hour equation is derived by a perturbation approach recurring to the steady state adjoint and direct eigenvalue problems of the effective multiplication factor and is used to suggest proper detection criteria of flux clustering. In spite of the prior work, the in-hour equation results give a necessary and sufficient condition for the existence of the eigenvalue-eigenvector pair. A simplified asymptotic analysis is used to predict bands of accumulation of eigenvalues close to the negative decay constants of the precursors concentrations. The resolution of the problem in one-dimensional heterogeneous problems shows numerical evidence of the predicted clustering occurrences and also confirms previous theoretical analysis and numerical results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.237-238
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• 2008

In this paper, the RCF method is applied to analyze small signal stability of power systems including thyristor controlled FACTS equipments such as TCSC. The eigenvalue sensitivity analysis algorithm in discrete systems by the RCF method are presented and applied to the power system including TCSC. The RCF analysis method enabled to precisely calculate eigenvalue sensitivity coefficients of dominant oscillation modes after periodic switching operations. These simulation results are very different from those of the conventional continuous system analysis method such as the state space equation method.

• 대한전기학회논문지:전력기술부문A
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• 제53권3호
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• pp.140-151
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• 2004

This paper presents the HVDC system modelling for analysis of subsynchronous oscillation and the design of the subsynchronous oscillation damping controller in HVDC system with the aid of novel eigenvalue analysis program. The HVDC system models include both the steady-state model for power flow calculation and the dynamic model for constructing the state matrix. The design procedures of the subsynchronous oscillation damping controller (SODC), which is integrated with PI controller at rectifier, consist of three steps:1) to identify the dominant torsional oscillation mode in the AC/DC system;2) to determine the parameters of the SODC for compensating the phase lagging due to the rectifier controller;3) to validate the control parameters and to determine the appropriate gain using a time-domain simulation program. The proposed design method has been tested against two AC/DC systems for validation.

• 말소리와 음성과학
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• 제1권1호
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• pp.69-73
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• 2009

This paper proposes an efficient global covariance-based principal component analysis (GCPCA) for speaker identification. Principal component analysis (PCA) is a feature extraction method which reduces the dimension of the feature vectors and the correlation among the feature vectors by projecting the original feature space into a small subspace through a transformation. However, it requires a larger amount of training data when performing PCA to find the eigenvalue and eigenvector matrix using the full covariance matrix by each speaker. The proposed method first calculates the global covariance matrix using training data of all speakers. It then finds the eigenvalue matrix and the corresponding eigenvector matrix from the global covariance matrix. Compared to conventional PCA and Gaussian mixture model (GMM) methods, the proposed method shows better performance while requiring less storage space and complexity in speaker identification.