• 한국항공우주학회지
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• 제47권7호
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• pp.535-540
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• 2019

MDO(Multi-disciplinary Optimization)를 위한 서로 다른 모델 간의 결합은 계산 프레임 워크의 복잡성을 크게 증가시키는 동시에 CPU 시간과 메모리 사용을 증가시킨다. 이러한 어려움을 극복하기 위해 POD(Proper Orthogonal Decomposition)와 RBF(Radial Basis Function)를 사용하여 복합 샌드위치 구조가 항공기 날개 스킨 재료로 사용될 때 복합재와 샌드위치 코어의 두께를 결정하는 최적화 문제의 해를 구했다. POD와 RBF를 사용하여 날개 형상과 하중 데이터에 대한 대리 모델을 만들었으며 대리 모델에 의해 얻어진 목적 함수 및 제약 함수 값을 사용하여 최적해를 구하였다.

• 한국CDE학회논문집
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• 제16권3호
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• pp.236-245
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• 2011

Many researchers have recently studied multi-level formulation strategies to solve the MDO problems and they basically distributed the coupling compatibilities across all disciplines, while single-level formulations concentrate all the controls at the system-level. In addition, approximation techniques became remedies for computationally expensive analyses and simulations. This paper studies comparisons of the MDO methods with respect to computing performance considering both conventional sequential and modem distributed/parallel processing environments. The comparisons show Individual Disciplinary Feasible (IDF) formulation is the most efficient for sequential processing and IDF with approximation (IDFa) is the most efficient for parallel processing. Results incorporating to popular design examples show this finding. The author suggests design engineers should firstly choose IDF formulation to solve MDO problems because of its simplicity of implementation and not-bad performance. A single drawback of IDF is requiring more memory for local design variables and coupling variables. Adding cheap memories can save engineers valuable time and effort for complicated multi-level formulations and let them free out of no solution headache of Multi-Disciplinary Analysis (MDA) of the Multi-Disciplinary Feasible (MDF) formulation.

• 한국생산제조학회지
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• 제26권1호
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• pp.30-35
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• 2017

The major parts of a vacuum cleaner are molded. The vacuum cleaner works in multi-load conditions. Therefore, the designer needs to optimize the structure and injection molding conditions simultaneously. Here, the main factor of design is the rib shape and thickness. The greater the rib thickness, the greater the stiffness of the structure. However, it causes an increase in weight. On the other hand, the lower the rib thickness, the greater the increase in the injection pressure. However, the weight will be reduced. Therefore, the designer needs to optimize the rib shape and thickness for structure stiffness and injection molding. In order to solve this problem, we propose an optimization method using D.O.E and a response surface model, which is a multi-objective optimization method using the multi-objective genetic algorithm.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2013년도 추계학술대회 논문집
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• pp.358-359
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• 2013

• 한국군사과학기술학회지
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• 제3권2호
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• pp.179-188
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• 2000

Multi-disciplinary optimization design concept can provide a solution to many engineering problems. In the field of structural analysis, much development of size or topology optimization has been achieved in the application of research. This paper demonstrates an optimum design of a multi-layer cylindrical tube which behaves thermoelastically. A multi-layer cylindrical tube that has several different material properties at each layer is optimized within allowable stress and temperature range when mechanical and thermal loads are applied simultaneously. When thermal loads are applied to a multi-layer tube, stress phenomena become complicated due to each layer's thermal expansion and the layer thicknesses. Factors like temperature; stress; and material thermal thicknesses of each tube layer are very difficult undertaking. To analyze these problems using an efficient and precise method, the optimization theories are adopted to perform thermoelastic finite element analysis.

• 한국자동차공학회논문집
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• 제14권1호
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• pp.1-7
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• 2006

This paper presents an ASF (Aluminum Space Frame) BIW optimal design, which minimizes the weight and satisfies multi-disciplinary constraints such as the static stiffness, vibration characteristics, low-speed crash, high-speed crash and occupant protection. As only one cycle CPU time for all the analyses is 12 hours, the ASF design having 11-design variable is a large scaled problem. In this study, ISCD-II and conservative least square fitting method is used for efficient RSM modeling. Then, ALM method is used to solve the approximate optimization problem. The approximate optimum is sequentially added to remodel the RSM. The proposed optimization method used only 20 analyses to solve the 11-design variable design problem. Also, the optimal design can reduce the] $15\%$ of total weight while satisfying all of the multi-disciplinary design constraints.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.339-344
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• 2001

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM (Finite Element Method) and BEM (Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta-modeling technique has been developed for solving such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building meta-models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty-six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.381-384
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• 2000

Multi-disciplinary optimization design concept can provide a solution to many engineering problems. In the field of structural analysis, much development of size or topology optimization has been achieved in the application of research. This paper demonstrates an optimum design of a multi-layer cylindrical tube which behaves thermoelastically. A multi-layer cylindrical tube that has several different material properties at each layer is optimized within allowable stress and temperature range when mechanical and thermal loads are applied simultaneously. To analyze these problems using an efficient and precise method, the optimization theories are adopted to perform thermoelastic finite element analysis.

• 한국항공우주학회지
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• 제36권3호
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• pp.229-237
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• 2008

본 연구에서는 항공기 날개를 설계하기 위하여 공기역학과 구조해석을 통합한 다분야 설계최적화(MDO) 프레임웍을 구성하였다. 파라미터 모델링 기법을 사용하여 최적화 전 과정을 자동화하였다. 공력해석은 Fluent를 사용하였으며 이를 위한 격자는 CATIA의 파라미터 모델과 Gridgen을 사용하여 자동으로 생성되도록 하였다. 유한요소해석을 위한 격자는 MSC.Patran의 PCL 기능을 사용한 파라미터 방법으로 자동으로 생성되도록 하였다. 공력하중은 volume spline method를 사용하여 구조하중으로 변환시켰다. 최적화 방법은 전역해를 구하기 유리한 반응표면법을 사용하였다. 최적화 문제로 목적 함수는 날개의 무게의 최소화, 제약조건은 양항비와 날개의 변위로 정하였다. 그리고 종횡비, 테이퍼 비 및 후퇴각을 설계변수로 정의하였다. 최적화 시험 결과는 본 MDO 프레임웍이 성공적으로 구성되었음을 보여주었다.

• 대한기계학회논문집A
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• 제27권6호
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• pp.864-870
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• 2003

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM(Finite Element Method) and BEM(Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta -modeling technique has been developed for solving such a complex problems combined with the DACE(Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building approximation models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty -six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging model of a train suspension. After each Kriging model is constructed, multi -objective optimal solutions are achieved by using a nonlinear programming method called SQP(Sequential Quadratic Programming).