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Reliability-Based Design Optimization Using Kriging Metamodel with Sequential Sampling Technique

순차적 샘플링과 크리깅 메타모델을 이용한 신뢰도 기반 최적설계

  • 최규선 ((주) LG 전자 에어컨 사업본부) ;
  • 이갑성 (한양대학교 대학원 기계공학과) ;
  • 최동훈 (한양대학교 기계공학부)
  • Published : 2009.12.01

Abstract

RBDO approach based on a sampling method with the Kriging metamodel and Constraint Boundary Sampling (CBS), which is sequential sampling method to generate metamodels is proposed. The major advantage of the proposed RBDO approach is that it does not require Most Probable failure Point (MPP) which is essential for First-Order Reliability Method (FORM)-based RBDO approach. The Monte Carlo Sampling (MCS), most well-known method of the sampling methods for the reliability analysis is used to assess the reliability of constraints. In addition, a Cumulative Distribution Function (CDF) of the constraints is approximated using Moving Least Square (MLS) method from empirical distribution function. It is possible to acquire a probability of failure and its analytic sensitivities by using an approximate function of the CDF for the constraints. Moreover, a concept of inactive design is adapted to improve a numerical efficiency of the proposed approach. Computational accuracy and efficiency of the proposed RBDO approach are demonstrated by numerical and engineering problems.

Keywords

RBDO;Kriging Metamodel;Constraint Boundary Sampling;Inactive Design

References

  1. Xu, H. and Rahman, S., 2005, "Decomposition Methods for Structural Reliability Analysis," Prob. Eng. Mech., Vol. 20, Issue 3, pp. 239~250 https://doi.org/10.1016/j.probengmech.2005.05.005
  2. Melchers, R.E. and Ahammed, M., 2004, "A Fast Approximate Method for Parameter Sensitivity Estimation in Monte Carlo Structural Reliability," Computers and Structures, Vol. 82, No. 1, pp. 55~61 https://doi.org/10.1016/j.compstruc.2003.08.003
  3. Lee, T. H. and Jung, J. J., 2008, "A Sampling Technique Enhancing Accuracy and Efficiency of Metamodel-Based RBDO: Constraint Boundary Sampling," Computer and Structures, Vol. 86, No. 13-14, pp. 1463~1476 https://doi.org/10.1016/j.compstruc.2007.05.023
  4. Youn, B. D. and Choi, K. K., 2004, "A New Response Surface Methodology for Reliability-Based Design Optimization," Computers and Structures, Vol. 82, No. 2, pp. 241~256 https://doi.org/10.1016/j.compstruc.2003.09.002
  5. Choi, B. L., Choi, J. H. and Choi, D. H., 2004, "Reliability-Based Design Optimization Using Enhanced Initial Design and Two-Point Approximation Technique," proceedings of 10th AIAA/ISSMO MAO conference 2004-4518
  6. Karush, W., 1939, Minima of Functions of Several Variables with Inequalities as Side Constraint, M. Sc Thesis, Dept. of Mathematics, Univ. of Chicago, Chicago, Illinois
  7. Kuhn, H. W. and Tucker, A. W., 1951, "Nonlinear Programming", Proceedings of 2nd Berkeley Symposium, Berkeley, University of California Press, pp. 481~492
  8. Youn, B. D., Choi, K. K., 2004, "An Investigation of Nonlinearity of Reliability-Based Design Optimization Approaches," Journal of Mechanical Design, Vol. 126, Issue 3, pp. 403~411 https://doi.org/10.1115/1.1701880
  9. Arora, J. S., 2004, Introduction to Optimum Design, McGraw-Hill, New York

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  1. RBDO of Coil Spring Considering Transversal Direction Mode Tracking vol.37, pp.6, 2013, https://doi.org/10.3795/KSME-A.2013.37.6.821
  2. Role of multi-response principal component analysis in reliability-based robust design optimization: an application to commercial vehicle design vol.58, pp.2, 2018, https://doi.org/10.1007/s00158-018-1908-4