• Journal of Mechanical Science and Technology
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• v.16 no.5
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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.

• 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.

• Korean Journal of Computational Design and Engineering
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• v.14 no.3
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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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.5
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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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.

• Korean Journal of Computational Design and Engineering
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• v.5 no.3
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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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.7
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• pp.685-692
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• 2009

This paper dealt with the development of the Framework for Multidisciplinary Design Optimization for the rotorcraft design concept and the building process of KHP(Korea Helicopter Project) - SDM(Simulation Data Management) system to manage various analysis data, which are used in the rotorcraft development phase. KHP-SDM RMDO(Rotorcraft Multidisciplinary Design Optimization) framework, which applied optimization modules of KHP-SDM and integrated the developed Multidisciplinary analysis modules, was constructed in the KHP-SDM. The results of the rotorcraft conceptual design using KHP-SDM RMDO showed that the framework was evaluated to be successfully constructed.

• 한국전산유체공학회:학술대회논문집
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• 2005.04a
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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.

• The KSFM Journal of Fluid Machinery
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• v.13 no.6
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• pp.19-24
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• 2010

The demands for small, high performance and high loaded aircraft compressor are increased in the world. But the design requirements become increasingly complex to design these high technical engines, the requirement of the design optimization become increased. The optimal design result of several disciplines show different tendencies and nonlinear characteristics of the compressor design, the multidisciplinary design optimization method must be considered in compressor design. Therefore, the artificial Neural Net method is adapted to make the approximation model of 3-stage axial compressor design optimization for considering the nonlinear characteristic. At last, the optimal result of this study is compared to that of previous study.

• International Journal of Automotive Technology
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• v.6 no.6
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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.