• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.635-638
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• 2001

본 논문에서는 수중 환경에서 분산 소나 시스템의 최적 정보 융합에 관한 알고리즘을 제시하였다. 기존의 방법은 Bayesian 법칙을 이용하여 local 소나와 퓨전 센터의 문턱치를 적절히 조절하여 분산 소나 시스템을 최적화했다. 그러나, 이러한 최적화 과정에서 소나의 개수를 늘려감에 따라 P/sub F/(false alarm probability)가 단조 증가하는 현상이 발생하였고 이러한 단점을 보완하기 위해 P/sub F/를 작은 간에 제한시키고 Bayesian 법칙과 Neyman-Pearson 법칙을 함께 적용하여 분산 소나 시스템을 최적화시킨다. 그러나, 이러한 조건 하에 시스템을 최적화시키는 것은 N-P hard 문제에 의해 계산 부하가 매우 크므로 unate 함수와 SQP(Sequential Quadratic Programming)을 이용하여 계산 부하를 감소시켰다.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.137.2-137.2
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• 2005

• Journal of Mechanical Science and Technology
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• v.17 no.1
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• pp.40-47
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• 2003

In this paper, we constructed the analytic model of control valve as a function of electric and geometric parameters, and analyzed the influence of the design parameters on the dynamic characteristics. For improving the dynamic characteristics, optimal design is conducted by applying sequential quadratic programming method to the analytic model. This optimal design aims to minimize the response time and maximize force efficiency. By this procedure, control valve can be designed to have fast response in motion.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1994.11a
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• pp.146-149
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• 1994

A nonlinear dynamic optimization has been performed for reactor power control system of CANDU 6 nuclear power plant considering xenon, fuel and moderator temperature feedback effects. Integral-of-Time-multiplied Absolute-Error (ITAE) criterion has been used as a performance index of the system behavior. Optimum controller gain are found by searching algorithm of Sequential Quadratic Programming (SQP). System models are referenced from most recent literatures. Signal flow network construction and optimization have been done by using commercial computer software package.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.395-402
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• 2003

Characteristics of base isolators including frictional and hysteretic types may be described by Bouc-Wen model. A probabilistic optimum design method of the base isolation system using Bouc-Wen model is presented in this paper. For optimum design, the objective function and constraints are derived based on the stochastic responses of the system. As a numerical example, the optimum design problem of a three-story base isolated shear type structure is formulated and solved by the sequential quadratic programming method.

• Journal of Electrical Engineering and Technology
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• v.7 no.4
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• pp.501-512
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• 2012

Social welfare maximization in a double-sided auction market is performed by implementing an aggregation-based particle swarm optimization (CAPSO) algorithm for optimal placement and sizing of one Static Synchronous Series Compensator (SSSC) device. Dallied simulation results (without/with line flow constraints and without/with SSSC) are generated to demonstrate the impact of SSSC on the congestion levels of the modified IEEE 14-bus test system. The proposed CAPSO algorithm employs conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. CAPSO also employs quadratic smooth consumer benefit functions. The proposed approach relies on particle swarm optimization to capture the near-optimal GenCos and DisCos, as well as the location and rating of SSSC while the Newton based load flow solution minimizes the mismatch equations. Simulation results of the proposed CAPSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and a recently implemented Fuzzy based genetic algorithm (Fuzzy-GA). The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of SSSC.

• Journal of Power System Engineering
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• v.21 no.6
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• pp.56-61
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• 2017

The check valves are mechanical valves that permit fluids to flow in only one direction, preventing flow from reversing. It is classified as one way directional valves. There are various types of check valves that used in a marine application. A lift type check valve uses the disc to open and close the passage of fluid. The disc lift up from seat as pressure below the disc increases, while drop in pressure on the inlet side or a build up of pressure on the outlet side causes the valve to close. An important concept in check valves is the cracking pressure which is the minimum upstream pressure at which the valve will operate. On the other hand, optimization is a process of finding the best set of parameters to reach a goal while not violating certain constraints. The AMESim software provides NLPQL(Nonlinear Programming by Quadratic Lagrangian) and genetic algorithm(GA) for optimization. NLPQL is the implementation of a SQP(sequential quadratic programming) algorithm. SQP is a standard method, based on the use of a gradient of objective functions and constraints to solve a non-linear optimization problem. A characteristic of the NLPQL is that it stops as soon as it finds a local minimum. Thus, the simulation results may be highly dependent on the starting point which user give to the algorithm. In this paper, we carried out optimization design of the check valve with NLPQL algorithm.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.4
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• pp.217-224
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• 2020

In this study, a framework for optimizing the opening in an outrigger wall is proposed. To solve a constrained bounded optimization problem, an in-house finite element program and SQP algorithm in Python SciPy library are utilized. The openings of the outrigger wall are located according to the strut-tie behavior of the outrigger wall deep beam. A linear interpolation method is used to obtain differentiable continuous functions required for optimization, whereas a database is used for the efficiency of the optimization program. By comparing the result of the two-variable optimization through the moving path of the search algorithm, it is confirmed that the algorithm efficiently determines the optimized result. When the size of each opening is set to individual variables rather than the same width of all openings, the value of the objective function is minimized to obtain better optimization results. It was confirmed that the optimization time can be effectively reduced when using the database in the optimization process.

• Journal of Korea Game Society
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• v.9 no.5
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• pp.137-144
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• 2009

This paper predicts 6 facial regions that may have sharply different scattering properties, rendering the face more realistically based on their diffusion profiles. The scattering properties are acquired in the form of high dynamic range by photographing the pattern formed around an unit ray incident on facial skin. The acquired data are fitted to a 'linear combination of Gaussian functions', which well approximates the original diffusion profile of skin and has good characteristics as the filter. During the process, to prevent its solutions from converging into local minima, we take advantage of the genetic algorithm to set up the initial value. Each Gaussian term is applied to the irradiance map as a filter, expressing subsurface scattering effect. In this paper, to efficiently handle the maximum 12 Gaussian filterings, we make use of the parallel capacity of CUDA.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.4
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• pp.675-691
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• 2002

The focus of this work is on the development of large-scale numerical optimization methods for optimal control of steady incompressible Navier-Stokes flows. The control is affected by the suction or injection of fluid on portions of the boundary, and the objective function of fluid on portions of the boundary, and the objective function represents the rate at which energy is dissipated in the fluid. We develop reduced Hessian sequential quadratic programming. Both quasi-Newton and Newton variants are developed and compared to the approach of eliminating the flow equations and variables, which is effectively the generalized reduced gradient method. Optimal control problems we solved for two-dimensional flow around a cylinder. The examples demonstrate at least an order-of-magnitude reduction in time taken, allowing the optimal solution of flow control problems in as little as half an hour on a desktop workstation.