• 제목/요약/키워드: Kriging based sequential approximate optimization

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FPSO Riser 지지구조의 설계최적화에 대한 근사화 기법의 비교 연구 (A Comparative Study of Approximation Techniques on Design Optimization of a FPSO Riser Support Structure)

  • 심천식;송창용
    • 한국전산구조공학회논문집
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    • 제24권5호
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    • pp.543-551
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    • 2011
  • 본 논문에서는 해양작업 상태의 하중조건을 고려한 부유식 원유생산 저장 하역장치에 설치된 라이져 보강구조의 강도설계에 관련하여 다양한 근사화 기법 기반 설계최적화 및 그 성능을 비교하고자 한다. 설계최적화 문제는 하중조건별 구조강도의 제한조건 하에서 중량을 최소화하여 설계변수인 구조 부재치수가 결정되도록 정식화된다. 비교 연구를 위해 사용된 근사화 기법은 반응표면법 기반 순차적 근사최적화(RBSAO), 크리깅 기반 순차적 근사최적화(KBSAO), 그리고 개선된 이동최소자승법(MLSM) 기반 근사최적화 기법인 CF-MLSM와 Post-MLSM이다. RBSAO와 KBSAO의 적용을 위하여 상용프로세스 통합 설계최적화(PIDO) 코드를 사용하였다. 본 연구에 적용한 MLSM 기반 근사최적화 기법들은 제한조건의 가용성을 보장할 수 있도록 새롭게 개발되었다. 다양한 근사화 모델 기반 설계최적화 기법에 의한 결과는 설계 해의 개선 및 수렴속도 등의 수치적 성능을 기준으로 실제 비근사 설계최적화 결과와 비교 검토하였다.

A Robust Optimization Using the Statistics Based on Kriging Metamodel

  • Lee Kwon-Hee;Kang Dong-Heon
    • Journal of Mechanical Science and Technology
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    • 제20권8호
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    • pp.1169-1182
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    • 2006
  • Robust design technology has been applied to versatile engineering problems to ensure consistency in product performance. Since 1980s, the concept of robust design has been introduced to numerical optimization field, which is called the robust optimization. The robustness in the robust optimization is determined by a measure of insensitiveness with respect to the variation of a response. However, there are significant difficulties associated with the calculation of variations represented as its mean and variance. To overcome the current limitation, this research presents an implementation of the approximate statistical moment method based on kriging metamodel. Two sampling methods are simultaneously utilized to obtain the sequential surrogate model of a response. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method. Then, the simulated annealing algorithm of global optimization methods is adopted to find the global robust optimum. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.

순차적 샘플링과 크리깅 메타모델을 이용한 신뢰도 기반 최적설계 (Reliability-Based Design Optimization Using Kriging Metamodel with Sequential Sampling Technique)

  • 최규선;이갑성;최동훈
    • 대한기계학회논문집A
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    • 제33권12호
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    • pp.1464-1470
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    • 2009
  • 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.

Conceptual Design Optimization of Tensairity Girder Using Variable Complexity Modeling Method

  • Yin, Shi;Zhu, Ming;Liang, Haoquan;Zhao, Da
    • International Journal of Aeronautical and Space Sciences
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    • 제17권1호
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    • pp.29-36
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    • 2016
  • Tensairity girder is a light weight inflatable fabric structural concept which can be used in road emergency transportation. It uses low pressure air to stabilize compression elements against buckling. With the purpose of obtaining the comprehensive target of minimum deflection and weight under ultimate load, the cross-section and the inner pressure of tensairity girder was optimized in this paper. The Variable Complexity Modeling (VCM) method was used in this paper combining the Kriging approximate method with the Finite Element Analysis (FEA) method, which was implemented by ABAQUS. In the Kriging method, the sample points of the surrogate model were outlined by Design of Experiment (DOE) technique based on Optimal Latin Hypercube. The optimization framework was constructed in iSIGHT with a global optimization method, Multi-Island Genetic Algorithm (MIGA), followed by a local optimization method, Sequential Quadratic Program (SQP). The result of the optimization gives a prominent conceptual design of the tensairity girder, which approves the solution architecture of VCM is feasible and efficient. Furthermore, a useful trend of sensitivity between optimization variables and responses was performed to guide future design. It was proved that the inner pressure is the key parameter to balance the maximum Von Mises stress and deflection on tensairity girder, and the parameters of cross section impact the mass of tensairity girder obviously.

크리깅 대체모델을 이용한 순차적 신뢰성기반 최적설계를 위한 효율적인 제한조건경계 샘플링 기법 (An Efficient Constraint Boundary Sampling Method for Sequential RBDO Using Kriging Surrogate Model)

  • 김지훈;장준용;김신유;이태희;조수길;김형우;홍섭
    • 대한기계학회논문집A
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    • 제40권6호
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    • pp.587-593
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    • 2016
  • 대체모델을 이용한 신뢰성기반 최적설계에서 최적해와 신뢰도의 정확성은 제한조건경계의 대체모델의 정확도에 영향을 받는다. 기존 제안된 제한조건경계 샘플링 기법은 제한조건경계에 실험점을 생성하여 이러한 정확성을 높일 수 있었다. 하지만, 제한조건경계 샘플링 기법은 최적해와 먼 부근의 제한조건경계에도 불필요한 실험점을 생성하여 과도한 계산비용이 발생한다. 본 논문에서는 크리깅 대체모델의 통계적 정보를 이용하여 최적해 근처의 제한조건경계에 실험점을 생성하는 효율적인 제한조건경계 샘플링 기법을 제안한다. 제안한 기법의 효율성과 정확성은 수학예제를 통하여 확인한다.