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Sensitivity Validation Technique for Sequential Kriging Metamodel

순차적 크리깅 메타모델의 민감도 검증법

  • Huh, Seung-Kyun (Dept. Automotive Engineering, College of Engineering, Hanyang Univ.) ;
  • Lee, Jin-Min (Dept. Automotive Engineering, College of Engineering, Hanyang Univ.) ;
  • Lee, Tae-Hee (Dept. Automotive Engineering, College of Engineering, Hanyang Univ.)
  • 허승균 (한양대학교 공과대학 자동차공학과) ;
  • 이진민 (한양대학교 공과대학 자동차공학과) ;
  • 이태희 (한양대학교 공과대학 자동차공학과)
  • Received : 2011.12.21
  • Accepted : 2012.05.24
  • Published : 2012.08.01

Abstract

Metamodels have been developed with a variety of design optimization techniques in the field of structural engineering over the last decade because they are efficient, show excellent prediction performance, and provide easy interconnections into design frameworks. To construct a metamodel, a sequential procedure involving steps such as the design of experiments, metamodeling techniques, and validation techniques is performed. Because validation techniques can measure the accuracy of the metamodel, the number of presampled points for an accurate kriging metamodel is decided by the validation technique in the sequential kriging metamodel. Because the interpolation model such as the kriging metamodel based on computer experiments passes through responses at presampled points, additional analyses or reconstructions of the metamodels are required to measure the accuracy of the metamodel if existing validation techniques are applied. In this study, we suggest a sensitivity validation that does not require additional analyses or reconstructions of the metamodels. Fourteen two-dimensional mathematical problems and an engineering problem are illustrated to show the feasibility of the suggested method.

메타모델은 설계 프레임워크 안에서 높은 효율성과 우수한 예측 능력, 타 프로그램과 쉬운 연동성 때문에 공학분야에서 지난 10 년간 최적설계 기법들과 함께 발전해왔다. 메타모델을 구성하기 위해서는 실험계획법, 메타모델링 기법, 검증법과 같은 절차가 요구된다. 검증법은 메타모델의 정확성을 판단하기 때문에 순차적 크리깅 메타모델에서 정확한 크리깅 메타모델을 구성하기 위한 표본점의 개수를 결정한다. 크리깅 메타모델과 같은 보간모델은 표본점에서의 응답을 항상 지나기 때문에 기존 방법으로 메타모델의 정확성을 판단하기 위해서는 추가적인 해석이나 메타모델의 재구성이 요구된다. 본 연구에서는 이러한 추가적인 해석과 메타모델의 재구성을 요구하지 않는 메타모델의 해석적 민감도를 이용하는 민감도 검증법을 제안한다. 14 개의 2 차원 수학예제와 공학예제를 이용하여 이 방법의 타당성을 검증한다.

Keywords

References

  1. Lee, T.H., Lee, C.J. and Lee, K.K., 2003, "Shape Optimization of a CRT Based on Response Surface and Kriging Metamodels," Trans. of the KSME (A), Vol. 27, No. 3, pp. 381-386.
  2. Simpson, T.W., Mauery, T.M., Korte, J.J. and Mistree, F., 2001, "Kriging Models for Global Approximation in Simulation-Based Multidisciplinary Design Optimization," AIAA Journal, Vol. 39, No. 12, pp. 2234-2241.
  3. Johnson, M.E., Moore, L.M. and Ylvisaker, D., 1990, "Minimax and Maximin Distance Designs," Journal of Statistical Planning and Inference, Vol. 26(2), pp. 131-148. https://doi.org/10.1016/0378-3758(90)90122-B
  4. Shewry M.C. and Wynn H.P., 1987, "Maximum Entropy Sampling," Journal of Applied Statistics, vol. 14, No. 2, pp. 165-170. https://doi.org/10.1080/02664768700000020
  5. Sacks, J., Welch, W.J., Mitchell, T.J. and Wynn, H.P., 1989, "Design and Analysis of Computer Experiments," Statistical Science, Vol. 4, No.4, pp. 409-435. https://doi.org/10.1214/ss/1177012413
  6. Meckesheimer, M., Barton, R.R., Simpson, T.W., and Booker, A.j., 2002, "Computationally Inexpensive Metamodel Assessment Strategies,'' AIAA Journal, Vol. 40, No.10, pp. 2053-2060. https://doi.org/10.2514/2.1538
  7. Shao, j., 1993, "Linear Model Selection by Cross- Validation," Journal of American Statistical Association, Vol.88, No. 422, pp. 486-494. https://doi.org/10.1080/01621459.1993.10476299
  8. Jin, R., Chen, W. and Sudjianto, A., 2002, "On Sequential Sampling for Global Metamodeling in Engineering Design," Proceeding of DETC'02 ASME 2002 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2002/DAC-32092.
  9. Jang, J., Lee, J.M. and Lee, T.H., 2011, "A Study of C1-continuity of Split Region Kriging model according to Correlation Functions," Proceedings of the KSME(A ), pp. 174-179.
  10. Kim, H.S. and Lee, T.H., 2010, "Mean-Variance- Validation Technique for Sequential Kriging Metamodels," Trans. of the KSME (A), Vol. 34, No. 5, pp. 511-657. https://doi.org/10.3795/KSME-A.2010.34.5.541

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