• Transactions of Materials Processing
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• v.7 no.3
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• pp.207-214
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• 1998

Influence of final thickness distribution in superplastic forming processes on mechanical properties of the product becomes very crucial. We should improve the thickness distribution of products by combining process parameters adequately In this paper we adopt a non-linear optimization technique for optimal process design of superplastic forming. And optimum design variable which makes the most adequate thickness distribution in combined stretc/blow forming and blow forming is predicted by this optimization scheme and rigid-viscoplastic finite element method.

• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.337-345
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• 2009

Deregulation in power industry has made the reactive power ancillary service management a critical task to power system operators from both technical and economic perspectives. Reactive power management in power systems is a complex combinatorial optimization problem involving nonlinear functions with multiple local minima and nonlinear constraints. This paper proposes a practical market-based reactive power ancillary service management scheme to tackle the challenge. In this paper a new model for voltage security and reactive power management is presented. The proposed model minimizes reactive support cost as an economic aspect and insures the voltage security as a technical constraint. For modeling validation study, two optimization algorithm, a genetic algorithm (GA) and particle swarm optimization (PSO) method are used to solve the problem of optimum allocation of reactive power in power systems under open market environment and the results are compared. As a case study, the IEEE-30 bus power system is used. Results show that the algorithm is well competent for optimal allocation of reactive power under practical constraints and price based conditions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.179-182
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• 2003

This paper proposes an adaptive hybrid genetic algorithm (aHGA) for effectively solving the complex reliability optimization problems. The proposed aHGA uses a loca1 search technique and an adaptive scheme for respectively constructing hybrid algorithm and adaptive ability. For more various comparisons with the proposed adaptive algorithm, other aHGAs with conventional adaptive schemes are considered. These aHGAs are tested and analyzed using two complex reliability optimization problems. Numerical result shows that the proposed aHGA outperforms the other competing aHGAs.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.392-397
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• 2001

Topology optimization is applied to determine the layout of a structure whose eigenfrequency coincides with a specified frequency. The topology optimization problem is formulated to minimize the difference between the structural frequency and a given frequency using the homogenization method and the modified optimality criteria method. It turns out that the value of a weighting factor in the updating scheme plays an important role to achieve both a suitable speed and a stable convergence of an algorithm. Unlike a constant weighting factor in previous works, it is suggested that a weight factor is varied during the iteration to control the amount of the frequency change. To substantiate the proposed approach two-dimensional structural design problems are presented and the resulted topology layouts for the specified eigenfrequency are compared to layouts for maximizing the corresponding eigenfrequency.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.580-585
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• 2001

A response surface method(RSM) is utilized for structural optimization and implemented on a parametric CAD platform. Once an approximation of the performance function is made, no formal design sensitivity analysis is necessary. The approximation gives the designer the sensitivity information and furthermore intuition on the performance functions. The scheme for the design of experiment chosen for the RSM has a large influence on the accuracy of converged solutions and the amount of computation. The D-optimal design criterion as implemented in this paper is found efficient for the structural optimization. The program is developed on a parametric CAD platform and tested using several shape design problems of such as a torque arm and a belt clip. It is observed that the RSM used provides a faster convergence than other approximation methods for design sensitivity.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.1
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• pp.125-132
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• 2002

Recently, ULSAB(Ultra Light Steel Auto Body) concept is getting more attention due to various benefits in automotive body design. One of the ULSAB efforts is making a door with TWB(Tailor Welded Blanks). In TWB, two or more patches of steel panels are welded together before stamping process. In this research, domains and thicknesses of the patches in a front door structure are determined by a series of optimization schemes composed of topology, size and shape optimization and DOE(Design of Experiments) scheme. A door is designed to have better performances compared to exiting structure considering static stiffness and natural frequency. The final design is discussed and compared to the existing design.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.840-848
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• 2009

This paper proposes a new multi-start scheme that generates guided random bits in selecting initial search points for global optimization with univariate dynamic encoding algorithm for searches (uDEAS). The proposed method counts the number of 1 in each bit position from all the previously generated initial search matrices and, based on this information, generates 0 in proportion with the probability of selecting 1. This rule is simple and effective for improving diversity of initial search points. The performance improvement of the proposed multi-start is validated through implementation in uDEAS and function optimization experiments.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.538-543
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• 2007

A procedure is proposed to generate optimal grid with minimal user intervention while keeping a prescribed level of accuracy, using an adaptive X-FEM and applied to shape optimization. In spite of various advantages of X-FEM, however, there are several obstacles for practical applications. Because of using a uniform background mesh and additional degree of freedoms for enrichment, an X-FEM is usually computationally more expensive than traditional finite element method. Furthermore, there are often accuracy problems. For an automatic procedure of optimal mesh generation, an h-adaptive scheme and a posteriori error estimation obtained by a post-processing process are utilized. The procedure is shown by 2-D shape optimization examples.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1873-1881
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• 2014

This paper deals with the design of multi-machine power system stabilizers (PSSs) and Static var compensator (SVC) using Modified shuffled frog leaping algorithm (MSFLA). The effectiveness of the proposed scheme for optimal setting of the PSSs and SVC controllers has been attended. The PSSs and SVC controllers designing is converted to an optimization problem in which the speed deviations between generators are involved. In order to compare the capability of PSS and SVC, they are designed independently once, and in a coordinated mode once again. The proposed method is applied on a multi-machine power system under different operating conditions and disturbances to confirm the effectiveness of it. The results of tuned PSS controller based on MSFLA (MSFLAPSS) and tuned SVC controller based on MSFLA (MSFLA SVC) are compared with the Strength pareto evolutionary algorithm (SPEA) and Particle swarm optimization (PSO) based optimized PSS and SVC through some performance to reveal its strong performance.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.197-205
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• 2014

As computer vision algorithms are developed on a continuous basis, the visual information from vision sensors has been widely used in the context of simultaneous localization and mapping (SLAM), called visual SLAM, which utilizes relative motion information between images. This research addresses a visual SLAM framework for online localization and mapping in an unstructured seabed environment that can be applied to a low-cost unmanned underwater vehicle equipped with a single monocular camera as a major measurement sensor. Typically, an image motion model with a predefined dimensionality can be corrupted by errors due to the violation of the model assumptions, which may lead to performance degradation of the visual SLAM estimation. To deal with the erroneous image motion model, this study employs a local bundle optimization (LBO) scheme when a closed loop is detected. The results of comparison between visual SLAM estimation with LBO and the other case are presented to validate the effectiveness of the proposed methodology.