• 한국산학기술학회논문지
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• 제15권7호
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• pp.4057-4064
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• 2014

본 연구는 본 연구에서 제안하는 근사 최적화 방법(메타모델 기반의 시뮬레이션 최적화)을 사용하여 저렴한 해석 비용으로 펀치 단조품의 예비성형체(preform)를 설계한다. 본 연구에서 사용한 설계목표는 유효변형률의 균일한 분포이고 설계변수는 예비성형체 치수이며, 구속조건으로 최대 미충진 비율을 사용한다. 이를 위해 먼저 예비성형펀치(반재), 마스터펀치(상부다이) 및 하부다이로 구성되는 단조성형 공정을 DEFORM 시뮬레이션에 의해 모사하고, 이 시뮬레이션 결과가 실제 단조 공정을 모사하고 있는지 확인하는 검증 방법에 관해 소개한다. 또한 본 연구에서 수행한 설계 최적화 과정, 즉 (i) 초기 메타모델의 생성, (ii) 메타모델의 최적화 수행, (iii) 메타모델 최적해의 검증, (iv) 메타모델의 개선에 관하여 상세히 기술한다.

• 대한기계학회논문집A
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• 제33권9호
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• pp.892-902
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• 2009

An efficient sequential optimization approach for metamodel was presented by Choi et al. This paper describes a new approach of the multilevel optimization method studied in Refs. [2] and [20,21]. The basic idea is concerned with multilevel iterative methods which combine a descent scheme with a hierarchy of auxiliary problems in lower dimensional subspaces. After fitting a metamodel based on an initial space filling design, this model is sequentially refined by the expected improvement criterion. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to understand and use. As a check on effectiveness, the proposed method is applied to an engineering example.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1198-1203
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• 2008

An efficient sequential optimization approach for metamodel was presented by Choi et al [6]. This paper describes a new approach of the multilevel optimization method studied in Refs. [5] and [21-25]. The basic idea is concerned with multilevel iterative methods which combine a descent scheme with a hierarchy of auxiliary problems in lower dimensional subspaces. After fitting a metamodel based on an initial space filling design, this model is sequentially refined by the expected improvement criterion. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to understand and use. As a check on effectiveness, the proposed method is applied to a classical cantilever beam.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.537-542
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• 2001

In recent engineering, the designer has become more and more dependent on computer simulation. But defining exact model using computer simulation is too expensive and time consuming in the complicate systems. Thus, designers often use approximation models, which express the relation between design variables and response variables. These models are called metamodel. In this paper, we introduce one of the metamodel, named Kriging. This model employs an interpolation scheme and is developed in the fields of spatial statistics and geostatistics. This class of interpolating model has flexibility to model response data with multiple local extreme. By reason of this multi modality, we can't use any gradient-based optimization algorithm to find global extreme value of this model. Thus we have to introduce global optimization algorithm. To do this, we introduce DE(Differential Evolution). DE algorithm is developed by Ken Price and Rainer Storn, and it has recently proven to be an efficient method for optimizing real-valued multi-modal objective functions. This algorithm is similar to GA(Genetic Algorithm) in populating points, crossing over, and mutating. But it introduces vector concept in populating process. So it is very simple and easy to use. Finally, we show how we determine Kriging metamodel and find global extreme value through two mathematical examples.

• 항공우주시스템공학회지
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• 제8권4호
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• pp.18-23
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• 2014

In preliminary design phase, the wing geometry of the civil aircraft was determined using the empirical equation and historical data. To make wing geometry more aerodynamically efficient, an aerodynamic shape optimization was conducted. For this purpose the parametric modeling, high fidelity CFD analysis and metamodel-based optimal design technique were adopted. The parametric modeling got the design process to achieve the improvement by generating the configuration outputs easily for the major design variables. The optimal design equations were formularized as the type of the multi-objective functions considering low/high speed and lift/drag coefficient. The optimal solution was explored with the help of the kriging metamodel and the desirability function, therefore the optimal wing planform was sought to be excellent at both low and high speed region. Additionally the optimal wing planform was validated that it was excellent not only at the specific AOA, but also all over the range of AOA.

• 대한기계학회논문집A
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• 제27권3호
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• pp.381-386
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• 2003

Gradually engineering designers are determined based on computer simulations. Modeling of the computer simulation however is too expensive and time consuming in a complicate system. Thus, designers often use approximation models called metamodels, which represent approximately the relations between design and response variables. There arc general metamodels such as response surface model and kriging metamodel. Response surface model is easy to obtain and provides explicit function. but it is not suitable for highly nonlinear and large scaled problems. For complicate case, we may use kriging model that employs an interpolation scheme developed in the fields of spatial statistics and geostatistics. This class of into interpolating model has flexibility to model response data with multiple local extreme. In this study. metamodeling techniques are adopted to carry out the shape optimization of a funnel of Cathode Ray Tube. which finds the shape minimizing the local maximum principal stress Optimum designs using two metamodels are compared and proper metamodel is recommended based on this research.

• Structural Engineering and Mechanics
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• 제70권5호
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• pp.513-524
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• 2019

This study proposed an improved particle swarm optimization (IPSO) method ensemble with kriging model for model updating. By introducing genetic algorithm (GA) and grouping strategy together with elite selection into standard particle optimization (PSO), the IPSO is obtained. Kriging metamodel serves for predicting the structural responses to avoid complex computation via finite element model. The combination of IPSO and kriging model shall provide more accurate searching results and obtain global optimal solution for model updating compared with the PSO, Simulate Annealing PSO (SimuAPSO), BreedPSO and PSOGA. A plane truss structure and ASCE Benchmark frame structure are adopted to verify the proposed approach. The results indicated that the hybrid of kriging model and IPSO could serve for model updating effectively and efficiently. The updating results further illustrated that IPSO can provide superior convergent solutions compared with PSO, SimuAPSO, BreedPSO and PSOGA.

• 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.

• 한국자동차공학회논문집
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• 제21권5호
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• pp.8-14
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• 2013

In this study, we propose the method of optimally selecting material of front pillar (A-pillar) and package tray for minimizing weight while satisfying vehicle requirements on static stiffness and dynamic stiffness. First, we formulate a material selection optimization problem. Next, we establish the CAE procedure of evaluating static stiffness and dynamic stiffness. Then, to enhance the efficiency of design work, we integrate and automate the established CAE procedure using a commercial process integration and design optimization (PIDO) tool, PIAnO. For effective optimization, we adopt the approach of metamodel based approximate optimization. As a sampling method, an orthogonal array (OA) is used for selecting sampling points. The response values are evaluated at the sampling points and then these response values are used to generate a metamodel of each response using the radial basis function regression (RBFr). Using the RBFr models, optimization is carried out an evolutionary algorithm that can handle discrete design variables. Material optimization result reveals that the weight is reduced by 49.8% while satisfying all the design constraints.

• Journal of Advanced Marine Engineering and Technology
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• 제37권8호
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• pp.893-904
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• 2013

NSGA-II와 함께 크리깅 메타모델기반 다목적최적설계 전략을 3차원 CFD 시뮬레이션을 통해 액셜 피스톤 펌프의 밸브 플레이트 형상을 최적화하는데 적용하였다. 펌프의 압력 변동을 저감하고 수력 효율을 최대화하기 위한 최적설계 과정은 두 단계, 즉 (1) 밸브 플레이트 상의 6개 형상 설계 변수를 선정하고 각 설계변수의 변화에 따른 CFD 해석을 수행하며, (2) CFD 데이터를 이용한 NSGA-II에 기반한 다목적최적설계 접근방식으로 최소 맥동 압력과 펌프 효율 설계에 대해 파레토 프론트를 평가하는 것으로 구성된다. 이들 결과로부터 최소 맥동 압력을 가지며 액셜 피스톤 펌프의 목표 효율에 도달하는 최적 절충해를 선택할 수 있었다.