• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.3 s.258
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• pp.355-364
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• 2007

Multidisciplinary design optimization based on independent subspaces (MDOIS) is a simple and practical method that can be applied to the practical engineering MDO problems. However, the current version of MDOIS does not handle the common design variables. A new version of MDOIS is proposed and named as MDOIS/2006. It is a two-level MDO method while the original MDOIS is a single-level method. At first, system analysis is performed to solve the coupling in the analysis. If the termination criteria are not satisfied, each discipline solves its own design problem. Each discipline in the lower level solves the problem with common design variables while they are constrained by equality constraints. In the upper level, the common design variables of related disciplines are determined by using the optimum sensitivity of the objective function. To validate MDOIS/2006, mathematical problem and NASA test bed problem are solved. The results are compared with those from other MDO methods. Finally, MDOIS/2006 is applied to flow patterner design and shows that it can be successfully applied to the practical engineering MDO problem.

• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.210-218
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• 2003

MDO (multidisciplinary design optimization) technology has been proposed and applied to solve large and complex optimization problems where multiple disciplinaries are involved. In this research. an MDO problem is defined for automobile design which has crashworthiness analyses. Crash model which are consisted of airbag, belt integrated seat (BIS), energy absorbing steering system .and safety belt is selected as a practical example for MDO application to vehicle system. Through disciplinary analysis, vehicle system is decomposed into structure subspace and occupant subspace, and coupling variables are identified. Before subspace optimization, values of coupling variables at given design point must be determined with system analysis. The system analysis in MDO is very important in that the coupling between disciplines can be temporary disconnected through the system analysis. As a result of system analysis, subspace optimizations are independently conducted. However, in vehicle crash, system analysis methods such as Newton method and fixed-point iteration can not be applied to one. Therefore, new system analysis algorithm is developed to apply to crashworthiness. It is conducted for system analysis to determine values of coupling variables. MDO algorithm which is applied to vehicle crash is MDOIS (Multidisciplinary Design Optimization Based on Independent Subspaces). Then, structure and occupant subspaces are independently optimized by using MDOIS.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.2
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• pp.109-117
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• 2004

Optimization has been successfully applied to systems with a single discipline. As many disciplines are involved in coupled fashion, MDO (multidisciplinary design optimization) technology has been developed. MDO algorithms are trying to solve the coupled aspects generated from interdisciplinary relationship. In a general MDO algorithms, a large design problem is decomposed into small ones which can be easily solved. Although various methods have been proposed for MDO, the research is still in the early stage. This research proposes a new MDO method which is named as MDOIS (Multidisciplinary Design Optimization Based on Independent Subspaces). Many real engineering problems consist of physically separate components and they can be independently designed. The inter-relationship occurs through coupled physics. MDOIS is developed for such problems. In MDOIS, a large system is decomposed into small subsystems. The coupled aspects are solved via system analysis which solves the coupled physics. The algorithm is mathematically validated by showing that the solution satisfies the Karush-Kuhn-Tucker condition.

• 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.