• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1354-1359
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• 2011

This paper presents a novel methodology for improving the reliability of electromagnetic devices and machines based on the reliability-based design optimization method. To achieve this, the method includes reliability analysis and optimization process taking into account uncertainties of design variables. One of the first-order reliability analysis techniques, called reliability index approach, is adopted to evaluate the reliability of performance functions with respect to probabilistic design variables. The proposed method has been successfully applied to designing a superconducting magnetic energy storage system. For verifying the efficiency and accuracy of the method, the results are compared with those of conventional optimization methods.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.563-573
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• 2007

Optimal design of an automotive catalytic converter for minimization of cold-start emissions is numerically performed using a micro genetic algorithm for two optimization problems: optimal geometry design of the monolith for various operating conditions and optimal axial catalyst distribution. The optimal design process considered in this study consists of three modules: analysis, optimization, and control. The analysis module is used to evaluate the objective functions with a one-dimensional single channel model and the Romberg integration method. It obtains new design variables from the control module, produces the CO cumulative emissions and the integral value of a catalyst distribution function over the monolith volume, and provides objective function values to the control module. The optimal design variables for minimizing the objective functions are determined by the optimization module using a micro genetic algorithm. The control module manages the optimal design process that mainly takes place in both the analysis and optimization modules.

• Structural Engineering and Mechanics
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• v.60 no.6
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• pp.1093-1117
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• 2016

Global sensitivity analysis (GSA) has been widely used to investigate the sensitivity of the model output with respect to its input parameters. In this paper a new single-solution search optimization algorithm is developed based on the GSA, and applied to the size optimization of truss structures. In this method the search space of the optimization is determined using the sensitivity indicator of variables. Unlike the common meta-heuristic algorithms, where all the variables are simultaneously changed in the optimization process, in this approach the sensitive variables of solution are iteratively changed more rapidly than the less sensitive ones in the search space. Comparisons of the present results with those of some previous population-based meta-heuristic algorithms demonstrate its capability, especially for decreasing the number of fitness functions evaluations, in solving the presented benchmark problems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.568-573
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• 1996

In this paper, A design strategy of the Surface Mounting Device for accurate and better performance is studied. Analytical Modeling. Sensitivity analysis and optimization are being conducted. The ANSYS software and experimental method are used for verification of the analytical equations withboundary conditons. Through the sensitivity analysis, the most dominant design parameters can be detected. The optimum design parameters for performing given performing given perfomances are selected by using the optimization algorithm. The design tool based on the design strategy for the analysis, modeling and optimization will be useful for a re-design and better perofrmance of the SMD.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.120-128
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• 1997

In this paper, A design strategy of the Surface Mounting Device for accurate and better performance is studied. Analytical modeling, sensitivity analysis, and optimization are being conducted. The ANSYS software and experimental method are used for the verification of the analytical equations with boundary conditions. Through the sensitivity analysis, the most dominant design parameter can be detected. The optimum design parameters for improving the given performances are selected by using the optimiza- tion algorithm. The design tool based on the design strategy for the analysis, modeling, and optimization will be useful for are-design and better improving of the SMD.

• Journal of Korean Society of Steel Construction
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• v.12 no.5 s.48
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• pp.503-513
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• 2000

This study treats the criteria, considering the fuzziness occurred by optimization design. And we applied two weighting methods to show the relative importance of criteria. This study develops multi-objective optimization programs implementing plain stress analysis by FEM and discrete optimization design uniformaly. The developed program performs a sample design of 10-member steel truss. This study can carry over the multi-objective optimization based on total system fuzzy-genetic algorithms while performing the stress analysis and optimization design. Especially, when general optimization with unreliable constraints is cannot be solve this study can make optimization design closed to realistic with fuzzy theory.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.2
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• pp.496-506
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• 2014

In this paper the scenario based optimization of the bulbous bow of the KRISO Container Ship (KCS) is presented. The optimization of the parametrically modeled vessel is based on a statistically developed operational profile generated from noon-to-noon reports of a comparable 3600 TEU container vessel and specific development functions representing the growth of global economy during the vessels service time. In order to consider uncertainties, statistical fluctuations are added. An analysis of these data lead to a number of most probable upcoming operating conditions (OC) the vessel will stay in the future. According to their respective likeliness an objective function for the evaluation of the optimal design variant of the vessel is derived and implemented within the parametrical optimization workbench FRIENDSHIP Framework. In the following this evaluation is done with respect to vessel's calculated effective power based on the usage of potential flow code. The evaluation shows, that the usage of scenarios within the optimization process has a strong influence on the hull form.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.303-310
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• 2005

The systems with probe and SIL(Solid Immersion Lens) mechanisms have been researched as the technology to perform NFR(Near Field Recording). Most of them use the flying head mechanism to accomplish high recording density and fast data transfer rate. In this paper, ABS shape of flying head was optimized with the object of securing the maximum compliance ability of OFH. We suggest low different optimization processes to predict the static flying characteristics for the OFH. Two different approximation methods, regression analysis and back propagation neural network were used. And we compared the result of directly connected(between CAE and optimizer) method and two approximated optimization results. Design Optimization Tool(DOT) and ${\mu}GA$ were used as the optimizers.

• Korean Journal of Computational Design and Engineering
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• v.16 no.6
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• pp.397-406
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• 2011

Since tolerance allocation in a mobile phone camera manufacturing process greatly affects production cost and reliability of optical performance, a systematic design methodology for allocating optimal tolerances is required. In this study, we proposed the tolerance optimization procedure for determining tolerances that minimize production cost while satisfying the reliability constraints on important optical performance indices. We employed Latin hypercube sampling for evaluating the reliabilities of optical performance and a function-based sequential approximate optimization technique that can reduce computational burden and well handle numerical noise in the tolerance optimization process. Using the suggested tolerance optimization approach, the optimal production cost was decreased by 30.3 % compared to the initial cost while satisfying the two constraints on the reliabilities of optical performance.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.04a
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• pp.143-148
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• 2000

In this article, we presents multi-objective design optimization of laminated composite beam using Fuzzy programming method. At first, the two design objectives are minimizing the structural weight and maximizing the buckling load respectively. Fuzzy multi-optimization problem can be formulated based on results of single optimizations. Due to different relative importance of design objectives, membership functions are constructed by adding exponential parameters for different objective's weights. Finite element analysis of composite beam for buckling behavior are carried by Natural mode method proposed by J.Argyris and computational time of analysis can be reduced. With this scheme, a designer can conveniently obtain a compromise optimal solution of a multi-objective optimization problem only by providing some exponential parameters corresponding to the importance of the objective functions.