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Reliability-based Structural Design Optimization Considering Probability Model Uncertainties - Part 1: Design Method

확률모델 불확실성을 고려한 구조물의 신뢰도 기반 최적설계 - 제1편: 설계 방법

  • Received : 2012.07.26
  • Accepted : 2012.09.27
  • Published : 2012.10.31

Abstract

Reliability-based design optimization (RBDO) problem is usually formulated as an optimization problem to minimize an objective function subjected to probabilistic constraint functions which may include deterministic design variables as well as random variables. The challenging task is that, because the probability models of the random variables are often assumed based on limited data, there exists a possibility of selecting inappropriate distribution models and/or model parameters for the random variables, which can often lead to disastrous consequences. In order to select the most appropriate distribution model from the limited observation data as well as model parameters, this study takes into account a set of possible candidate models for the random variables. The suitability of each model is then investigated by employing performance and risk functions. In this regard, this study enables structural design optimization and fitness assessment of the distribution models of the random variables at the same time. As the first paper of a two-part series, this paper describes a new design method considering probability model uncertainties. The robust performance of the proposed method is presented in Part 2. To demonstrate the effectiveness of the proposed method, an example of ten-bar truss structure is considered. The numerical results show that the proposed method can provide the optimal design variables while guaranteeing the most desirable distribution models for the random variables even in case the limited data are only available.

Keywords

reliability-based design optimization;probability model uncertainty;candidate model;random variable;distribution model;limited data

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Acknowledgement

Grant : 에너지저감에 따른 물류시설 및 설비의 안전성 및 신뢰성 연구