• 대한기계학회논문집A
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• 제31권2호
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• pp.211-220
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• 2007

This work presents an iterated improved reduced system (IIRS) procedure combined with sub-structuring scheme for large structures. Iterated IRS methods are usually more efficient than others because the dynamic condensation matrix is updated repeatedly until the desired convergent values are obtained. However, using these methods simply for large structures causes expensive computational cost and even makes analyses intractable because of the limited computer storage. Therefore, the application of sub-structuring scheme is necessary. Because the large structures are subdivided into several (or more) sub-domains, the construction of dynamic condensation matrix does not require much computation cost in every iteration. This makes the present method much more efficient to compute the eigenpairs both in lower and intermediate modes. In Part I, iterated IRS method combined with sub-structuring scheme for undamped structures is presented. The validation of the proposed method and the evaluation of computational efficiency are demonstrated through the numerical examples.

• 대한기계학회논문집A
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• 제31권2호
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• pp.221-230
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• 2007

An iterated improved reduced system (IIRS) procedure combined with sub-structuring scheme for nonclassically damped structural systems is presented. For dynamic analysis of such systems, complex eigenproperties are required to incorporate properly the nonclassical damping effect. In complex structural systems, the equations of motion are written in the state space from. Thus, the number of degrees of freedom of the new equations of motion and the size of the associated eigenvalue problem required to obtain the complex eigenvalues and eigenvectors are doubled. Iterated IRS method is an efficient reduction technique because the eigenproperties obtained in each iteration step improve the condensation matrix in the next iteration step. However, although this reduction technique reduces the size of problem drastically, it is not efficient to apply this technique to a single domain finite element model with degrees of freedom over several thousands. Therefore, for a practical application of the reduction method, accompanying sub-structuring scheme is necessary. In the present study, iterated IRS method combined with sub-structuring scheme for nonclssically damped structures is developed. Numerical examples demonstrate the convergence and the efficiency of a newly developed scheme.

• Structural Monitoring and Maintenance
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• 제5권3호
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• pp.417-428
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• 2018

In this paper, various model reduction methods were assessed using a shear frame, plane and space truss structures. Each of the structures is one-dimensional, two-dimensional and three-dimensional, respectively. Three scenarios of poor, better, and the best were considered for each of the structures in which 25%, 40%, and 60% of the total degrees of freedom (DOFs) were measured in each of them, respectively. Natural frequencies of the full and reduced order structures were compared in each of the numerical examples to assess the performance of model reduction methods. Generally, it was found that system equivalent reduction expansion process (SEREP) provides full accuracy in the model reduction in all of the numerical examples and scenarios. Iterated improved reduced system (IIRS) was the second-best, providing acceptable results and lower error in higher modes in comparison to the improved reduced system (IRS) method. Although the Guyan's method has very low levels of accuracy. Structures were classified with the excitation frequency. High-frequency structures compared to low-frequency structures have been poor performance in the model reduction methods (Guyan, IRS, and IIRS).

• 한국전산구조공학회논문집
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• 제21권3호
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• pp.281-285
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• 2008

축소시스템 기법은 전체 구조의 거동을 나타내는 저차 고유모드를 근사화한다. 지난 연구에서 축소시스템을 구축하기 위한 2단계 축소기법을 제안하였다. 또, 기존의 2단계 축소기법을 반복적 IRS기법을 통해 중간 주파수 대역의 고유모드에 대한 해의 정확도를 높이는 방안에 대해 연구가 제안되었다. 본 연구에서는 기존의 향상된 2단계 축소기법에 다단계 부구조화 기법을 적용하는 기법을 제안한다. 첫 단계에서는 전체 시스템을 그래프 분할을 통해 계층적으로 부구조로 분할되고, 두 번째 단계에서는 각각의 부구조를 개선된 2단계 축소기법을 이용하여 축소한다. 각각의 축소된 분절화된 고유치문제의 조합을 총해 최종적 축소시스템을 구축하고 이렇게 구한 축소된 고유치 문제를 란초스 기법(ARPACK)을 통해 해석한다. 최종적으로 제안된 기법의 성능을 수치 예제를 통해 검증한다.