Transactions of the Korean Society of Mechanical Engineers A (대한기계학회논문집A)

The Korean Society of Mechanical Engineers (대한기계학회)
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Development of Computational Orthogonal Array based Fatigue Life Prediction Model for Shape Optimization of Turbine Blade

터빈 블레이드 형상 최적설계를 위한 전산 직교배열 기반 피로수명 예측 모델 개발

  • Received : 2009.12.29
  • Accepted : 2010.03.10
  • Published : 2010.05.01
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Abstract

A complex system involves a large number of design variables, and its operation is non-linear. To explore the characteristics in its design space, a Kriging meta-model can be utilized; this model has replaced expensive computational analysis that was performed in traditional parametric design optimization. In this study, a Kriging meta-model with a computational orthogonal array for the design of experiments was developed to optimize the fatigue life of a turbine blade whose behavior under cyclic rotational loads is significantly non-linear. The results not only show that the maximum fatigue life is improved but also indicate that the accuracy of computational analysis is achieved. In addition, the robustness of the results obtained by six-sigma optimization can be verified by comparison with the results obtained by performing Monte Carlo simulations.

터빈 블레이드와 같은 시스템의 피로수명은 형상 설계변수의 변화에 따라 비선형적으로 복잡하게 나타난다. 방대한 계산시간이 요구되는 이러한 시스템의 CAE 기반 파라메트릭 설계최적화 문제에 근사기법인 크리깅 메타모델 방법이 활용되고 있다. 본 연구에서는 터빈 블레이드의 피로수명을 향상시키기 위하여, 설계변수 변화에 따른 피로수명의 비선형성을 고려함은 물론 직교성과 균형성을 모두 만족하는 다 수준 전산 실험계획법을 수행하여 크리깅 메타모델을 구축하였다. 크리깅 메타모델로부터 만족도 함수를 적용하여 피로 수명을 최적화하였고, 몬테카를로 모의실험법을 적용한 식스시그마 최적설계를 수행하여 피로수명의 결함률을 향상시킨 최적해의 강건성을 확보하였다.

Keywords

References

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