• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.98-104
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• 2002

System condensation technique improves the efficiency of the inverse perturbation method of damage detection developed in the previous work. The technique is applied to transform the unmeasured DOFs to the measured DOFs. This approach makes it possible to eliminate the unmeasured DOFs, which accelerates the computational efficiency. The numerical instability problems due to the system condensation technique are also resolved by updating the transformation matrix for each step, and also by adopting the accelerated improved reduced system(AIRS) condensation method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.1
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• pp.65-73
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• 2007

In the inverse perturbation method, enormous computational resource was required to obtain reliable results, because all unspecified DOFs were considered as unknown variables. Thus, in the present study, a reduced system method is used to condense the unspecified DOFs by using the specified DOFs, and to improve the computational efficiency as well as the solution accuracy. In most of the conventional reduction methods, transformation errors occur in the transformation matrix between the unspecified DOFs and the specified DOFs. Thus it is hard to obtain reliable and accurate solution of inverse perturbation problems by reduction methods due to the error in the transformation matrix. This numerical trouble is resolved in the present study by adopting iterative improved reduced system(IIRS) as well as by updating the transformation matrix at every step. In this reduction method, system accuracy is related to the selection of the primary DOFs and Iteration time. And both are dependent to each other So, the two level condensation method (TLCS) is selected as Selection method of primary DOFs for increasing accuracy and reducing iteration time. Finally, numerical verification results of the present iterative inverse perturbation method (IIPM) are presented.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.146-150
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• 2009

구조 시스템 식별은 역문제로서 이상화된 유한요소 모델을 실험치와 일치시키기 위해 유한요소모델을 보정하는 형태로 주로 이루어진다. 이를 위해 비선형 섭동법이 사용되고 있으며 이 방법을 실제 문제에 사용하기 위해서 시스템 축소법에 대한 연구가 진행 되고 있다. 하지만 기존의 방법에서는 유한요소모델의 모든 요소가 실험치와 다르다고 가정하여서 전체 요소 수만큼의 설계 변수를 두어서 역해석을 수행한다. 이런 기존의 방법에서는 시스템이 커짐에 따라 연산 시간이 기하급수적으로 증가하게 되어 어려움이 있다. 설계 변수의 증가는 해공간(solution space)의 확장을 의미하며 이는 해의 정확성에 큰 영향을 끼친다. 본 연구에서는 모델을 적은 수의 설계영역으로 나누어서 반복연산 단계마다 해의 경향성을 이용해서 설계 영역을 전략적으로 변경하는 적응성 설계영역기법을 제안한다. 수치예제를 통해 본 연구에서 제안하는 기법의 정확도와 효용성을 고찰한다.