• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.1-10
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• 2002

Multidisciplinary Design Optimization (MDO) is a new design approach, which aims to reduce the design cycle and the development cost, while improving the performance of the product. In order to develop a framework software where the multidisciplinary design is possible, several methods about the analysis codes integration, the analysis and optimization process management, and the software architecture, are proposed in this study. Centralized DataBase Management System (DBMS) is adopted. Both the Dynamic Link Library(DLL) and the File Interface are suggested and implemented as analysis codes integration methods. To efficiently manage the optimization process and the data flow, the Graphic Programming approach is introduced. The proposed integration methods are verified by two test case examples: Simple house design example and the aircraft wing design problem using three dimensional Panel Code.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.8
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• pp.34-41
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• 2005

A parallel computing technique was applied to large scale structure analysis or aerodynamic design and it is a essential element in reducing the huge computation time for large scale design problem. We can use a many computers for reducing the analysis time of multidisciplinary design optimization. But previous MDO frameworks can not support a parallel design process technique so still existing which calls an analysis program continuously. In this paper, We developed a MDO framework(MLR) which supports a parallel design process to solve sequential analysis call. Finally, three sample cases are presented to show the efficiency of design time using the suggested MDO framework.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.12
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• pp.1150-1156
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• 2007

Multidisciplinary design optimization methodologies play an essential role in modern engineering design which involves many inter-related disciplines. These methodologies usually require very long computing time and design tasks are hard to finish within a specified design cycle time. Parallel processing can be effectively utilized to reduce the computing time. The research on the parallel computing performance of MDO methodologies has been just begun and developing. This study investigates performances of MDF, IDF, SAND and CO among MDO methodologies in view of parallel computing. Finally, the best out of four methodologies is suggested for parallel processing purpose.

• Korean Journal of Computational Design and Engineering
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• v.7 no.1
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• pp.27-33
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• 2002

MDO(Multidisciplinary Design Optimization) methodology is a new technology to solve a complicate design problem with a large number of design variables and constraints. The design of a dental implant system is a typical complicate problem, and so it requires the MDO methodology. Actually, several analyses such as rigid body dynamic analysis and structural stress analysis etc. should be carried out in the MDO methodology application to the design of a dental implant system. In this paper, as a first step of MDO methodology application to the design of a dental implant system, the impact force which is applied on the tooth in masticating is calculated through the rigid body dynamic analysis of upper and lower jaw-bones. This analysis is done using ADAMS. The impact force calculated through the rigid body dynamic analysis can be used for the structural stress analysis of a dental implant system which is needed for the design of a dental implant system. In addition, the rigid body dynamic analysis results also show that the impact time decreases as the impact force increases, the largest impact force occurs on the front tooth, and the impact force is almost normal to the tooth surface with a slight tangential force.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.359-369
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• 1999

The paper describes the study of concurrent subspace optimization(CSSO) for coupled multidisciplinary design optimization (MDO) techniques in mechanical systems. This method is a solution to large scale coupled multidisciplinary system, wherein the original problem is decomposed into a set of smaller, more tractable subproblems. Key elements in CSSO are consisted of global sensitivity equation(GSE), subspace optimization (SSO), optimum sensitivity analysis(OSA), and coordination optimization problem(COP) so as to inquiry valanced design solutions finally, Automatic differentiation has an ability to provide a robust sensitivity solution, and have shown the numerical numerical effectiveness over finite difference schemes wherein the perturbed step size in design variable is required. The present paper will develop the automatic differentiation based concurrent subspace optimization(AD-CSSO) in MDO. An automatic differentiation tool in FORTRAN(ADIFOR) will be employed to evaluate sensitivities. The use of exact function derivatives in GSE, OSA and COP makes Possible to enhance the numerical accuracy during the iterative design process. The paper discusses how much influence on final optimal design compared with traditional all-in-one approach, finite difference based CSSO and AD-CSSO applying coupled design variables.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.3661-3666
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• 2015

The paper describes the integrated design system using MDO and approximation technique. In MDO related research, final target is an integrated and automated MDO framework systems. However, in order to construct the integrated design system, the prerequisite condition is how much save computational cost because of iterative process in optimization design and lots of data information in CAD/CAE integration. Therefore, this paper presents that an efficient approximation method, Adaptive approximation, is a competent strategy via MDO framework systems.

• Proceedings of the KSME Conference
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• 2000.11a
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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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.716-726
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• 2010

In this research, design optimization of an aircraft wing has been performed using the fully automated Multidisciplinary Design Optimization (MDO) framework, which integrates aerodynamic and structural analysis considering nonlinear structural behavior. A computational fluid dynamics (CFD) mesh is generated automatically from parametric modeling using CATIA and Gambit, followed by an automatic flow analysis using FLUENT. A computational structure mechanics (CSM) mesh is generated automatically by the parametric method of the CATIA and visual basic script of NASTRAN-FX. The structure is analyzed by ABAQUS. Interaction between CFD and CSM is performed by a fully automated system. The Response Surface Method (RSM) is applied for optimization, helping to achieve the global optimum. The optimization design result demonstrates successful application of the fully automated MDO framework.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.3 s.234
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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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.5
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• pp.25-36
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• 2003

Aircraft design pursues integrated design efforts by considering all design elements together. In the integrated design environment, it is crucial for the design data to be consistent, free of errorm, and most recent. Database design process consists of the analysis of the data which shall be stored and managed, the construction of the E-R Diagram, and the mapping of the database table. As a DBMS (DataBase Management System), Oracle 8i is employed to design and construct the database. The database design methodology is devised to apply for the several MDO(Multidisciplinary Design Optimization) techniques like MDF(MultiDisplinary Feasible), IDF(Individual Discipline Feasible), and CO(Collaborative Optimization). The defined process is demonstrated through a couple of design examples, including a simple numerical example and a UCAV(Unmanned Combat Aerial Vehicle) design optimization.