• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.211-216
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• 2002

실제적인 문제에서 신뢰성 기반 최적 설계(RBDO)를 구현하기 위해서는 유한요소 모델을 해석하기 위한 상용 프로그램과 설계한 것에 대한 신뢰성을 산정할 수 있는 프로그램을 통합하고 최적화 알고리듬을 적용하여야 최적화를 수행하여야만 한다. 또한 최적화 과정에서 최적상태에서 제약조건이 비활성 영역에서 놓이게 되는 것을 방지하기 위해서 제약조건 최적화 문제를 비제약 조건 최적화 문제로 바꾸어 주는 장애 함수를 사용하여 최적화를 수행하였다. 그리고 이 방법론을 기존의 신뢰성기반 최적화 방법론, 즉 신뢰도지수 접근방법과 목표성능치 접근방법과의 비교를 하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.14 no.2
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• pp.213-224
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• 2001

확률론적 구조설계 최적화는 구조물의 역학적 특성이나 하중의 불확실성이나 임의성과 같은 변동성을 정량적이고 합리적으로 고려할 수 있다는 점에서 기존의 전통적인 확정론적 최적화와 비교된다. 확률론적 최적화의 방법론으로는 개선된 일계이차모멘트법을 이용하는 신뢰도지수에 기반한 접근법(MPFP search)이 널리 알려져 있으며, 최근 목표성능치에 기반한 접근법(MPTP search)이 새롭게 제안되었다. 본 논문에서는 이들 두 가지 접근법에 대한 정식화를 수행하고, 특히 탐색과정에서 소모적인 반복계산을 발견하고 제거하는 알고리즘을 제시하였다. 예제에서 두 접근법에 의한 확률론적 최적화를 수행하고 구조설계 최적화의 관점에서 두 접근법의 장단점을 비교·검토하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3A
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• pp.193-200
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• 2010

Structural design requires simultaneously to ensure safety by considering quantitatively uncertainties in the applied loadings, material properties and fabrication error and to maximize economical efficiency. As a solution, system reliability-based design optimization (SRBDO), which takes into consideration both uncertainties and economical efficiency, has been extensively researched and numerous attempts have been done to apply it to structural design. Contrary to conventional deterministic optimization, SRBDO involves the evaluation of component and system probabilistic constraints. However, because of the complicated algorithm for calculating component reliability indices and system reliability, excessive computational time is required when the large-scale finite element analysis is involved in evaluating the probabilistic constraints. Accordingly, an algorithm for SRBDO exhibiting improved stability and efficiency needs to be developed for the large-scale problems. In this study, a more stable and efficient SRBDO based on the performance measure approach (PMA) is developed. PMA shows good performance when it is applied to reliability-based design optimization (RBDO) which has only component probabilistic constraints. However, PMA could not be applied to SRBDO because PMA only calculates the probabilistic performance measure for limit state functions and does not evaluate the reliability indices. In order to overcome these difficulties, the decoupled algorithm is proposed where RBDO based on PMA is sequentially performed with updated target component reliability indices until the calculated system reliability index approaches the target system reliability index. Through a mathematical problem and ten-bar truss problem, the proposed method shows better convergence and efficiency than other approaches.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1130-1135
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• 2003

The need to increase the reliability of a structural system has been significantly brought in the procedure of real designs to consider, for instance, the material properties or geometric dimensions that reveal a random or incompletely known nature. Reliability based design optimization of a real system now becomes an emerging technique to achieve reliability, robustness and safety of these problems. Finite element analysis program and the reliability analysis program are necessary to evaluate the responses and the probabilities of failure of the system, respectively. Moreover, integration of these programs is required during the procedure of reliability based design optimization. It is well known that reliability based design optimization can often have so many local minima that it cannot converge to the specified probability of failure. To overcome this problem, barrier function method in reliability based design optimization is suggested. To illustrate the proposed formulation, reliability based design optimization of a bracket is performed. AMV and FORM are employed for reliability analysis and their optimization results are compared based on the accuracy and efficiency.