• The Journal of Natural Sciences
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• v.8 no.2
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• pp.9-11
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• 1996

We apply a full mutigrid scheme to computing eigenvalues of the Laplace eigenvalue problem with Dirichlet boundary condition. We use finite difference method to get an algebraic equation and apply inverse power method to estimating the smallest eigenvalue. Our result shows that combined method of inverse power method and full multigrid scheme is very effective in calculating eigenvalue of the eigenvalue problem.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.10a
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• pp.240-240
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• 2003

V-노치 균열에서 열하중이 작용하는 경우는 비제차형 경계조건의 문제가 되고, 이 조건에 대한 방정식의 일반해를 구하기 위해서 재차형 연립방정식에 대한 일반해(Homogeneous solution)와 비제차형 연립방정식에 대한 특수해(Particular solution)의 두 가지 해를 구할 수 있다. 이들 해는 V-노치 균열에 대한 고유치가 되고 이 고유치가 중복근을 가지게 되는 경우에는 로그항(1n[r])이 나타나게 되고 이 항에 의해서 응력을 무한대로 발산시키므로 이를 대수응력특이성이라 한다. 열하중이 작용할 때 대수응력특이성을 나타내는 로그항의 계수가 영(0)이 되어 대수응력특이성이 사라지게 되므로 V-노치 선단에서의 응력특이성은 고유치와 그에 대한 고유벡터에 의해 결정된다. 본 논문에서는 비정상상태 열하중이 가해지는 등방성 이종재료 내의 V-노치 균열문제에서 패기 각도와 이종재료의 기계적 성질에 의해 결정되는 응력특이성지수를 구하고 이에 대한 응력강도계수를 유한요소해석 프로그램인 ANSYS와 상반일 경로 적분법(RWCIM)을 이용하여 구하였다.

• The Journal of Natural Sciences
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• v.9 no.1
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• pp.69-74
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• 1997

We introduce the Crawford number and codal metric to analyze perturbation bounds of the generalized eigenvalue problem.

• Computational Structural Engineering
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• v.4 no.2
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• pp.111-117
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• 1991

The analysis method calculating the mean and standard deviation for the eigenvalue of complicated structures in which the limit state equation is implicitly expressed is formulated and applied to the buckling analysis by combining probabilistic finite element method with direct differential method which is a kind of sensitivity analysis technique. Also, the probability of buckling failure is calculated by combining classical reliability techniques such a MVFOSM and AFOSM. As random variables external load, elastic modulus, sectional moment of inertia and member length are chosen and Parkinson's iteration algorithm in AFOSM is used. The accuracy of the results by this study is verified by comparing the results with the crude Monte Carlo simulation and Importance Sampling Method. Through the case study of some structures the important aspects of buckling reliability analysis are discussed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.371-383
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• 1999

An efficient and numerically stable eigensolution method for structures with multiple natural frequencies is presented. The proposed method is developed by improving the well-known subspace iteration method with shift. A major difficulty of the subspace iteration method with shift is that because of singularity problem, a shift close to an eigenvalue can not be used, resulting in slower convergence. In this paper, the above singularity problem has been solved by introducing side conditions without sacrifice of convergence. The proposed method is always nonsingular even if a shift is on a distinct eigenvalue or multiple ones. This is one of the significant characteristics of the proposed method. The nonsingularity is proved analytically. The convergence of the proposed method is at least equal to that of the subspace iteration method with shift, and the operation counts of above two methods are almost the same when a large number of eigenpairs are required. To show the effectiveness of the proposed method, two numerical examples are considered.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.147-154
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• 2019

The finite element model updating can be defined as the problem of finding the parameters of the finite element model which gives the closest response to the actual response of the structure by measurement. In the previous researches, optimization based methods have been developed to minimize the error of the response of the actual structure and the analytical model. In this study, we propose an inverse eigenvalue problem that can directly obtain the parameters of the finite element model from the target mode information. Deep Neural Networks are constructed to solve the inverse eigenvalue problem quickly and accurately. As an application example of the developed method, the dynamic finite element model update of a suspension bridge is presented in which the deep neural network simulating the inverse eigenvalue function is utilized. The analysis results show that the proposed method can find the finite element model parameters corresponding to the target modes with very high accuracy.

• Computational Structural Engineering
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• v.4 no.1
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• pp.73-82
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• 1991

Recently, the finite element method has been sucessfully extended to treat the rather complex phenomena such as nonlinear buckling problems which are of considerable practical interest. In this study, a finite element program to evaluate the elasto-plastic buckling stress is developed. The Stowell's deformation theory for the plastic buckling of flat plates, which is in good agreement with experimental results, is used to evaluate bending stiffness matrix. A bifurcation analysis is performed to compute the elasto-plastic buckling stress. The subspace iteration method is employed to find the eigenvalues. The results are compared with corresponding exact solutions to the governing equations presented by Stowell and also with experimental data due to Pride. The developed program is applied to obtain elastic and elasto-plastic buckling stresses for various loading cases. The effect of different plate aspect ratio is also investigated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.117-119
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• 2005

For large structural eigen-analysis, the whole structure is divided into some partitioned structures and through synthesis of partitioned structural model the eigen-data of structure can be obtained. In that case, eigenvalue problem consists of semidefinite mass matrix form because of displacement constraint condition. In this work the eigenvalue problem is considered by means of several method, determinant search and null space reduction method.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.5
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• pp.59-66
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• 2002

Many important scientific and engineering problems require the computation of a small number of eigenvalues for large nonsymmetric matrices. The biorthogonal Lanczos method is one of the methods to solve that problem, but it faces serious breakdown problems. In this paper, we introduce a modified biorthogonal Lanczos method to find a few eigenvalues of a large sparse nonsymmetric matrix. The proposed method generates reduction matrices that are similar to those generated by the standard biorthogonal Lanczos method. We prove that the breakdown conditions of our method are less stringent than the standard method. We then implement the modified biorthogonal Lanczos method on the CRAY machine and discuss the decreased breakdown conditions.

• Computational Structural Engineering
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• v.11 no.1
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• pp.205-216
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• 1998

A solution method is presented to solve the eigenvalue problem arising in the dynamic analysis of nonclassicary damped structural systems with multiple eigenvalues. The proposed method is obtained by applying the modified Newton-Raphson technique and the orthonormal condition of the eigenvectors to the linear eigenproblem through matrix augmentation of the quadratic eigenvalue problem. In the iteration methods such as the inverse iteration method and the subspace iteration method, singularity may be occurred during the factorizing process when the shift value is close to an eigenvalue of the system. However, even though the shift value is an eigenvalue of the system, the proposed method provides nonsingularity, and that is analytically proved. Since the modified Newton-Raphson technique is adopted to the proposed method, initial values are need. Because the Lanczos method effectively produces better initial values than other methods, the results of the Lanczos method are taken as the initial values of the proposed method. Two numerical examples are presented to demonstrate the effectiveness of the proposed method and the results are compared with those of the well-known subspace iteration method and the Lanczos method.