• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.05a
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• pp.211-214
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• 2002

Almost all buildings/infrastructures made of composite materials are fabricated without proper design. Unlike airplane or automobile parts, prototype test is impossible. One cannot destroy 10 story buildings or 100-meter long bridges. People try to build 100-story buildings or several thousand meter long bridges. In order to realize "composites in construction", the following subjects must be studied in detail, for his design. Concept optimization, Simple method of analysis, Folded plate theory, Size effects in failure, and Critical frequency. Unlike the design procedure with conventional materials, his design should include material design, selection of manufacturing methods, and quality control methods, in addition to the fabrication method. In this paper, concept optimization and folded plate theory are presented for practicing engineers.engineers.

• International Journal of Ocean System Engineering
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• v.3 no.1
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• pp.1-9
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• 2013

A design procedure for a ship with minimum resistance had been developed using a numerical optimization method called SQP (Sequential Quadratic Programming) combined with computational fluid dynamics (CFD) technique. The frictional resistance coefficient was estimated by the ITTC 1957 model-ship correlation line formula and the wave-making resistance coefficient was evaluated by the potential-flow panel method with the nonlinear free surface boundary conditions. The geometry of the hull surface was represented and modified by B-spline surface modeling technique during the optimization process. The Series 60 ($C_B$=0.60) hull was selected as a parent hull to obtain an optimized hull that produces minimum resistance. The models of the parent and optimized hull forms were tested at calm water condition in order to demonstrate the validity of the proposed methodolgy.

• Journal of Korean Society for Quality Management
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• v.41 no.4
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• pp.673-681
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• 2013

Purpose: The purpose of this study is to investigate the design optimization modeling of screening procedures based on the assessment of misclassification errors. Methods: Misclassification errors due to measurement variability are derived for normally distributed quality characteristics. Further, an optimization model for ensuring the level of outgoing quality is proposed and demonstrated through an illustrative example. Results: It is shown that two types of misclassification errors (i.e., false acceptance and false rejection) may be properly compromised through an analytical assessment of measurement errors and an optimization modeling. It is also discussed that a variety of optimization modeling may be enabled based on the derivation of measurement errors. Conclusion: It may be concluded that the design of screening inspection may further be facilitated by including the effect of measurement errors on the performance of screening inspection procedure.

• 한국전산유체공학회:학술대회논문집
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• 2001.05a
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• pp.72-77
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• 2001

The computational efficiency of an shape optimization procedure is highly dependent upon the proper selection of shape representation methods and design variables. In this study, shape functions, Bezier and NURBS(non-uniform rational B-splines) curves are selected as configuration generation methods and their efficiencies on the nose shape design of high-speed air vehicles, are compared. The effects of the number of control points, weighting factors and the optimization methods when utilizing the NURBS curves, are investigated. By implementing Bezier and NURBS curves, shapes having lower drag than the optimization case utilizing the shape functions, were obtained, hence it was demonstrated that these curves have better capability in representing the configuration. Efforts will be given to improve the convergence behavior when utilizing the NURBS, hence to reduce the number of Navier-Stokes analysis calculations.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.6
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• pp.21-28
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• 2010

This study shows an optimization procedure for an automatic determination on the gate position to ensure the fill-uniformity within a part cavity by using the injection molding simulation. For an optimization, the maximum pressure-difference within a part cavity induced at the stage of filling is used to evaluate degree of fill-uniformity. In addition, a direct search scheme based on the reduction of design space is developed and applied in the optimization problem. This corresponding proposed methodology was applied in the optimization on the gate location for a CD-tray molding, as a result, showed the improvement of the fill-uniformity within the cavity.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.1
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• pp.175-180
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• 2008

Due to the global environment problems and the consumer's need for higher vehicle performance, it becomes very important for the global car makers to reduce vehicle weight. To reduce vehicle weight, many car makers have tried to use lightweight materials, for example, aluminum, magnesium, and plastics, for the vehicle structures and components. Especially, the ASF(aluminum space frame) is known for the excellent concept of the vehicle to satisfy structural rigidity, safety performance and weight reduction. In this research, the design of experiments and the multi-disciplinary optimization technique were utilized to meet the weight and structural rigidity target of the ASF. For the structural performance of the ASF, the locations and the size of aluminum extruded frames, aluminum cast nodes, and the aluminum sheets were optimized. As a result, the optimization design procedure has been set up to meet both structural and weight target of the ASF, and the assembled ASF showed good structural performance and weight reduction.

• Journal of the Korean Society of Safety
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• v.12 no.3
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• pp.120-131
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• 1997

This paper presents an approximate reanalysis methods of structures based on substructuring for an effective optimization of large-scale structural systems. In most optimal design procedures the analysis of the structure must be repeated many times. In particular, one of the main obstacles in the optimization of structural systems are involved high computational cost and expended long time in the optimization of large-scale structures. The purpose of this paper is to evaluate efficiently the structural behavior of new designs using information from previous ones, without solving basic equations for successive modification in the optimal design. The proposed reanalysis procedure is combined Taylor series expansions which is a local approximation and reduced basis method which is a global approximation based on substructuring. This technique is to choose each of the terms of Taylor series expansions as the basis vector of reduced basis method in substructuring system which is one of the most effective analysis of large -scale structures. Several numerical examples illustrate the effectiveness of the solution process.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.2
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• pp.33-41
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• 1994

The procedure to design the engine mount is briefly discussed and the optimum shape design process of engine mounting rubber using a parametric approach is suggested. An optimization code is developed to determine the shape to meet the stiffness requirements of engine mounts, coupled with the commercial nonlinear finite element program ABAQUS. A bush type engine mount used in a current passenger car is chosen for an application model. The shape from the result of the parameter optimization is determined as a final model with some modifications. The shape and stiffness of each optimization stage are shown and the stiffness of the optimized model along the principal direction is compared with the design specification of the current model. Finally, an overview of the current status and future works for the engine mount design are discussed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.513-524
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• 2006

The ammunition allocation problem is a Multi-objective optimization(MOO) problem, maximizing fill-rate of multiple user troops and minimizing transportation time. Recent studies attempted to solve this problem by the prior preference articulation approach such as goal programming. They require that all the preference information of decision makers(DM) should be extracted prior to solving the problem. However, the prior preference information is difficult to implement properly in a rapidly changing state of war. Moreover they have some limitations such as heavy cognitive effort required to DM. This paper proposes a new ammunition allocation model based on more reasonable assumptions and uses an interactive MOO method to the ammunition allocation problem to overcome the limitations mentioned above. In particular, this article uses the GDF procedure, one of the well-known interactive optimization methods in the MOO liter-ature, in solving the ammunition allocation problem.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.155-157
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• 2005

We propose a new category of hybrid multi-layer neural networks with hetero nodes such as Fuzzy Set based Polynomial Neurons (FSPNs) and Polynomial Neurons (PNs). These networks are based on a genetically optimized multi-layer perceptron. We develop a comprehensive design methodology involving mechanisms of genetic optimization and genetic algorithms, in particular. The augmented genetically optimized HFPNN (namely gHFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of HFPNN leads to the selection of preferred nodes (FPNs or PNs) available within the HFPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFPNNs quantified through experimentation where we use a number of modeling benchmarks-synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.