• Journal of Mechanical Science and Technology
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• 제16권5호
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• pp.609-618
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• 2002

In practical designs, most of the multidisciplinary problems have a large-size and complicate design system. Since multidisciplinary problems have hundreds of analyses and thousands of variables, the grouping of analyses and the order of the analyses in the group affect the speed of the total design cycle. Therefore, it is very important to reorder and regroup the original design processes in order to minimize the total computational cost by decomposing large multidisciplinary problems into several multidisciplinary analysis subsystems (MDASS) and by processing them in parallel. In this study, a new decomposition method is proposed for parallel processing of multidisciplinary design optimization, such as collaborative optimization (CO) and individual discipline feasible (IDF) method. Numerical results for two example problems are presented to show the feasibility of the proposed method.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 추계학술대회논문집A
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• pp.818-823
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• 2000

In practical design studies, most of designers solve multidisciplinary problems with complex design structure. These multidisciplinary problems have hundreds of analysis and thousands of variables. The sequence of process to solve these problems affects the speed of total design cycle. Thus it is very important for designer to reorder original design processes to minimize total cost and time. This is accomplished by decomposing large multidisciplinary problem into several multidisciplinary analysis subsystem (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problem to raise design efficiency by using genetic algorithm and shows the relationship between decomposition and multidisciplinary design optimization (MDO) methodology.

• 한국CDE학회논문집
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• 제14권3호
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• pp.207-216
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• 2009

Modern engineering design problems involve complexity of disciplinary coupling and difficulty of problem formulation. Multidisciplinary design optimization can overcome the complexity and design optimization software or frameworks can lessen the difficulty. Recently, a growing number of new multidisciplinary design optimization techniques have been proposed. However, each technique has its own pros and cons and it is hard to predict a priori which technique is more efficient than others for a specific problem. In this study, a software system has been developed to directly solve MDO problems with minimal input required. Since the system is based on MATLAB, it can exploit the optimization toolbox which is already developed and proven to be effective and robust. The framework is devised to change an MDO technique to another as the optimization goes on and it is called a reconfigurable MDO framework. Several numerical examples are shown to prove the validity of the reconfiguration idea and its effectiveness.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.822-827
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• 2005

Recently engineering systems problems become quite large and complicated. For those problems, design requirements are fairly complex. It is not easy to design such systems by considering only one discipline. Therefore, we need a design methodology that can consider various disciplines. Multidisciplinary Design Optimization (MDO) is an emerging optimization method to include multiple disciplines. So far, about seven MDO methodologies have been proposed for MDO. They are Multidisciplinary Feasible (MDF), Individual Feasible (IDF), All-at-Once (AAO), Concurrent Subspace Optimization (CSSO), Collaborative Optimization (CO), Bi-Level Integrated System Synthesis (BLISS) and Multidisciplinary Optimization Based on Independent Subspaces (MDOIS). In this research, the performances of the methods are evaluated and compared. Practical engineering problems may not be appropriate for fairness. Therefore, mathematical problems are developed for the comparison. Conditions for fair comparison are defined and the mathematical problems are defined based on the conditions. All the methods are coded and the performances of the methods are compared qualitatively as well as quantitatively.

• 대한기계학회논문집A
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• 제25권5호
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• pp.883-890
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• 2001

In practical design studies, most of designers solve multidisciplinary problems with large size and complex design system. These multidisciplinary problems have hundreds of analysis and thousands of variables. The sequence of process to solve these problems affects the speed of total design cycle. Thus it is very important for designer to reorder the original design processes to minimize total computational cost. This is accomplished by decomposing large multidisciplinary problem into several multidisciplinary analysis subsystem (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problem to raise design efficiency by using genetic algorithm and shows the relationship between decomposition and multidisciplinary design optimization (MDO) methodology.

• 한국CDE학회논문집
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• 제5권3호
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• pp.263-275
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• 2000

Multidisciplinary design optimization(MDO) can yield optimal design considering all the disciplinary requirements concurrently. A method to implement the collaborative optimization(CO) approach, one of the MDO methodologies, is developed using a pre-compiler “EzpreCompiler”, a design optimization library “EzOptimizer”, and a common object request broker architecture(CORBA) in distributed computing environment. The CO approach is applied to a mathematical example to show its applicability and equivalence to standard optimization(SO) formulation. In a realistic engineering problem such as optimal design of a two-member hub frame, optimal design of a speed reducer and initial design of a bulk carrier, the CO yields better results than the SO. Furthermore, the CO allows the distributed processing using the CORBA, which leads to reduction of overall computation time.

• 한국항공우주학회지
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• 제37권7호
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• pp.685-692
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• 2009

본 논문에서는 회전익 비행체 개발과정에서 사용되는 다양한 해석데이터를 관리하기 위한 KHP - SDM 시스템 개발 및 회전익 비행체 개념설계를 위한 다분야통합 최적설계 프레임워크 개발에 관해 기술하였다. KHP-SDM 시스템 상에 개발된 다분야 해석 모듈을 통합하고 KHP-SDM의 최적화 모듈을 적용하여 KHP-SDM RMDO 프레임워크를 구축하였다. KHP-SDM RMDO 프레임워크를 이용한 회전익 비행체 개념설계 결과 프레임워크가 성공적으로 구성되었음을 보여주었다.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2005년도 춘계 학술대회논문집
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• pp.187-190
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• 2005

In this study, the reliablility based design optimization is peformed for an aircraft wing. The flexiblility of the wing was assumed by considering the interaction modeled by static aeroelasticity between aerodynamic forces and the structure. For a multidisciplinary design optimization the results of aerodynamic analysis and structural analysis were included in the optimization formulation. The First Order Reliability Method(FORM) was employed to consider the uncertainty of the designed points.

• 대한기계학회논문집A
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• 제29권3호
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• pp.395-402
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• 2005

Recently Multidisciplinary Design Optimization Based on Independent Subspaces (MDOIS), an MDO (multidisciplinary design optimization) algorithm, has been proposed. In this research, an MDO problem is defined for design of a belt integrated seat considering crashworthiness, and MDOIS is applied to solve the problem. The crash model consists of an airbag, a belt integrated seat (BIS), an energy absorbing steering system, and a safety belt. It is found that the current design problem has two disciplines - structural nonlin- ear analysis and occupant analysis. The interdisciplinary relationship between the disciplines is identified and is addressed in the system analysis step in MDOIS. Interdisciplinary variables are belt load and stiffness of the seat, which are determined in system analysis step. The belt load is passed to the structural analysis subspace and stiffness of the seat back frame to the occupant analysis subspace. Determined design vari- ables in each subspace are passed to the system analysis step. In this way, the design process iterates until the convergence criterion is satisfied. As a result of the design, the weight of the BIS and Head Injury Crite- rion (HIC) of an occupant are reduced with specified constraints satisfied at the same time. Since the system analysis cannot be formulated in an explicit form in the current example, an optimization problem is formu - lated to solve the system analysis. The results from MDOIS are discussed.

• International Journal of Automotive Technology
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• 제6권6호
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• pp.635-641
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• 2005

This paper presents an ASF (Aluminum Space Frame) BIW (Body in White) optimal design, which minimizes weight and satisfies multidisciplinary constraints such as static stiffness, vibration characteristics, low-/high-speed crash, and occupant safety. 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 were used for efficient RSM modeling. Likewise, the ALM method was used to solve the approximate optimization problem. The approximate optimum was sequentially added to remodel the RSM. The proposed optimization method uses only 20 analyses to solve the 11-design variable problem. Moreover, the optimal design can achieve $15.6\%$ weight reduction while satisfying all the multidisciplinary design constraints.