Journal of computational fluids engineering (한국전산유체공학회지)

Korean Society of Computational Fluids Engineering (한국전산유체공학회)
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A STUDY ON CONSTRAINED EGO METHOD FOR NOISY CFD DATA

Noisy 한 CFD 결과에 대한 구속조건을 고려한 EGO 방법 연구

  • Bae, H.G. (Dept. of Aerospace Engineering, KAIST) ;
  • Kwon, J.H. (Dept. of Aerospace Engineering, KAIST)
  • 배효길 (한국과학기술원 항공우주공학과) ;
  • 권장혁 (한국과학기술원 항공우주공학과)
  • Received : 2012.06.27
  • Accepted : 2012.12.14
  • Published : 2012.12.31
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Abstract

Efficient Global Optimization (EGO) method is a global optimization technique which can select the next sample point automatically by infill sampling criteria (ISC) and search for the global minimum with less samples than what the conventional global optimization method needs. ISC function consists of the predictor and mean square error (MSE) provided from the kriging model which is a stochastic metamodel. Also the constrained EGO method can minimize the objective function dealing with the constraints under EGO concept. In this study the constrained EGO method applied to the RAE2822 airfoil shape design formulated with the constraint. But the noisy CFD data caused the kriging model to fail to depict the true function. The distorted kriging model would make the EGO deviate from the correct search. This distortion of kriging model can be handled with the interpolation(p=free) kriging model. With the interpolation(p=free) kriging model, however, the search of EGO solution was stalled in the narrow feasible region without the chance to update the objective and constraint functions. Then the accuracy of EGO solution was not good enough. So the three-step search method was proposed to obtain the accurate global minimum as well as prevent from the distortion of kriging model for the noisy constrained CFD problem.

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References

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