• Journal of Magnetics
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• 제20권2호
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• pp.193-200
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• 2015

Direct-acting solenoid valves are used in the automotive industry due to their simple structure and quick response in controlling the flow of fluid. We performed an optimization study of response time in order to improve the dynamic performance of a direct-acting solenoid valve. For the optimal design process, we used the commercial optimization software PIAnO, which provides various tools for efficient optimization including design of experiments (DOE), approximation techniques, and a design optimization algorithm. 35 sampling points of computational experiments are performed to find the optimum values of the design variables. In all cases, ANSYS Maxwell electromagnetic analysis software was used to model the electromagnetic dynamics. An approximate model generated from the electromagnetic analysis was estimated and used for the optimization. The best optimization model was selected using the verified approximation model called the Kriging model, and an optimization algorithm called the progressive quadratic response surface method (PQRSM).

• 대한기계학회논문집A
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• 제21권10호
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• pp.1561-1570
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• 1997

This study explores the treatment of the max-value cost function over a parameter interval in parametric optimization. To avoid the computational burden of the transformation treatment using an artificial variable, a direct treatment of the original max-value cost function is proposed. It is theoretically shown that the transformation treatment results in demanding an additional equality constraint of dual variables as a part of the Kuhn-Tucker necessary conditions. Also, it is demonstrated that the usability and feasibility conditions on the search direction of the transformation treatment retard convergence rate. To investigate numerical performances of both treatments, typical optimization algorithms in ADS are employed to solve a min-max steady-state response optimization. All the algorithm tested reveal that the suggested direct treatment is more efficient and stable than the transformation treatment. Also, the better performing of the direct treatment over the transformation treatment is clearly shown by constrasting the convergence paths in the design space of the sample problem. Six min-max transient response optimization problems are also solved by using both treatments, and the comparisons of the results confirm that the performances of the direct treatment is better than those of the tranformation treatment.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1999년도 춘계학술대회 논문집
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• pp.212-216
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• 1999

We propose a method for simulation optimization using stochastic genetic algorithm(GA) to get the best design and operating policies in a Direct-Input-Output Automated Manufacturing System (DIOMS).

• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.600-607
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• 1998

일반적인 비선형 동역학 최적화문제를 비선형 프로그래밍 문제로 변환하는데 제어변수들을 방사성 기본 함수로 근사화하는 방법이 사용되었다. 방사성 기본 함수의 계수들을 연속적으로 보정하기 위하여 최소수정기법에 기초를 둔 비선형 프로그래밍 알고리즘이 연구되었다. 이러한 알고리즘을 실제적인 다변수 제어 시스템에 적용하여 성능을 검증하였다.

• 한국전산유체공학회지
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• 제13권4호
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• pp.96-106
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• 2008

We review a series of studies on turbulent skin friction drag reduction in wall-turbulence recently conducted in Japan. First, an identity equation relating the skin friction drag and the Reynolds shearstress (the FIK identity) is introduced. Based on the implication of the FIK identity, a new analytical suboptimal feedback control law requiring the streamwise wall-shear stress only is introduced and direct numerical simulation (DNS) results of turbulent pipe flow with that control is reported. We also introduce DNS of an anisotropic compliant surface and parameter optimization using an evolutionary optimization technique.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 학술대회
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• pp.347-354
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• 2008

We introduce a series of studies on turbulent skin friction drag reduction in wall-turbulence. First, an identity equation relating the skin friction drag and the Reynolds shear stress (the FIK identity) is introduced. Based on the implication of the FIK identity, a new analytical suboptimal feedback control law requiring the streamwise wall-shear stress only is introduced and direct numerical simulation (DNS) results of turbulent pipe flow with that control is reported. We also introduce DNS of an anisotropic compliant surface and parameter optimization using an evolutionary optimization technique.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년 추계학술대회논문집
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• pp.347-354
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• 2008

We introduce a series of studies on turbulent skin friction drag reduction in wall-turbulence. First, an identity equation relating the skin friction drag and the Reynolds shear stress (the FIK identity) is introduced. Based on the implication of the FIK identity, a new analytical suboptimal feedback control law requiring the streamwise wall-shear stress only is introduced and direct numerical simulation (DNS) results of turbulent pipe flow with that control is reported. We also introduce DNS of an anisotropic compliant surface and parameter optimization using an evolutionary optimization technique.

• International Journal of Control, Automation, and Systems
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• 제6권4호
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• pp.571-582
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• 2008

This paper analyzes global convergence of the univariate dynamic encoding algorithm for searches (uDEAS) and provides an application result to function optimization. uDEAS is a more advanced optimization method than its predecessor in terms of the number of neighborhood points. This improvement should be validated through mathematical analysis for further research and application. Since uDEAS can be categorized into the generating set search method also established recently, the global convergence property of uDEAS is proved in the context of the direct search method. To show the strong performance of uDEAS, the global minima of four 30 dimensional benchmark functions are attempted to be located by uDEAS and the other direct search methods. The proof of global convergence and the successful optimization result guarantee that uDEAS is a reliable and effective global optimization method.

• 오토저널
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• 제15권1호
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• pp.81-88
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• 1993

A direct treatment of the min-max type objective function of the dynamic response optimization problem is proposed. Previously, the min-max type objective function was transformed to an artificial design variable and an additional point-wise state variable constraint function was imposed, which increased the complexity of the optimization problem. Especially, the design sensitivity analysis for the augmented Lagrangian functional with the suggested treatment is established by using the adjoint variable method and a computer program to implement the proposed algorithm is developed. The optimization result of the proposed treatment are obtained for three typical problems and compared with those of the previous treatment. It is concluded that the suggested treatment in much more efficient in the computational effort than the previous treatment with giving the similar optimal solutions.

• Journal of Magnetics
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• 제16권4호
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• pp.379-385
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• 2011

This paper presents an optimal design of a direct-drive permanent magnet synchronous generator for a small-scale wind energy conversion system. An analytical model of a small-scale grid-connected wind energy conversion system is presented, and the effects of generator design parameters on the payback period of the system are investigated. An optimization procedure based on genetic algorithm method is then employed to optimize four design parameters of the generator for use in a region with relatively low wind-speed. The aim of optimization is minimizing the payback period of the initial investment on wind energy conversion systems for residential applications. This makes the use of these systems more economical and appealing. Finite element method is employed to evaluate the performance of the optimized generator. The results obtained from finite element analysis are close to those achieved by analytical model.