• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.6
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• pp.715-726
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• 2010

In this paper, a comparative study of metallic and non-metallic stiffened plates under a lateral pressure load is performed using conventional statistically determinate and SQP(Sequential Quadratic Programming) optimisation approaches. Initially, a metallic flat-bar stiffened plate is exemplified from the superstructure of a marine vessel and, subsequently, its structural topology is varied as hat-section stiffened FRP(Fibre Reinforced Plastics) single skin plates and monocoque FRP sandwich plates having a PVC foam core. These proposed structural alternatives are analysed using elastic closed-form solutions and SQP optimisation method under stress and deflection limits obtained from practice to calculate and optimise geometry dimensions and weights. Results obtained from the comparative study provide useful information for marine designers especially at the preliminary design stage where various building materials and structural configurations are dealt with.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.4
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• pp.183-190
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• 2018

This paper presents optimization of the main spar of Human-Powered Aircraft (HPA) wing. Mass minimization was attempted, while considering large torsional deformation of the beam. Sequential Quadratic Programming (SQP) method was adopted as a relevant tool to conduct structural optimization algorithm. An inner diameter and ply thicknesses of the main spar were selected as the design variables. The objective function includes factors such as mass minimization, constant tip bending displacement, and constant tip twist of the beam. For estimation of bending and torsional deformation, the geometrically exact beam model, which is appropriate for large deflection, was adopted. Properties of the cross sectional area which the geometrically exact beam model requires were obtained by Variational Asymptotic Beam Sectional Analysis (VABS), which is a cross sectional analysis program. As a result, maintaining tip bending displacement and tip twist within 1.45%, optimal design that accomplished 7.88% of the mass reduction was acquired. By the stress and strain recovery, structural integrity of the optimal design and validity of the present optimization procedure were authenticated.

• 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.

• 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 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.1
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• pp.90-99
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• 1995

In this study, the algorithm for the optimum design of cantilever retaining wall was de veloped and solved using Modified Method of Feasible Directions(MMFD), Sequential Linear Programming(SLP) and Sequential Quadratic Programming(SQP). The algorithm was applied to the optimum design of 3-different height cantilever re tairing walls. It was shown that even though the starting points and optimization strategies are dif- ferent, the objective function and optimum design variables converge to within a close range, and consequently the reliability and efficiency of the underlying optimum design algorithm can be verified. It is expected that the optimum design algorithm developed in this study can be utilized efficiently for the optimum design of any scale cantilever retaining wall. Using optimum design method, cantilever retaining wall will be designed more economi- cally and reasonably than using traditional design method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.11
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• pp.447-452
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• 2006

This paper presents a scheme to solve the congestion problem with phase-shifting transformer(PST) controls and power generation controls using linear programming method. A good design of PST and power generation control can improve total transfer capability(TTC) in interconnected systems. This paper deals with an application of optimization technique for TTC calculation. Linear programming method is used to maximize power flow of tie line subject to security constraints such as voltage magnitude and real power flow in interconnected systems. The results are compared with that of repeat power flow(RPF) and sequential quadratic programming(SQP). The proposed method is applied to 10 machines 39 buses model systems to show its effectiveness.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.5 s.149
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• pp.550-559
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• 2006

A design procedure for a ship with minimum total resistance was developed using a numerical optimization method called SQP(Sequential Quadratic Programming) and a CFD technique based on the Rankine source panel method with the nonlinear free surface boundary conditions. During the whole optimization process the geometry of the hull shape was represented based on the NURBS(Non-uniform rational B-spline) technique and the modification of the hull shape was controlled using the Bell-shaped distribution function to keep the fairness of the hull shape before and after the hull modification. The numerical analysis was carried out using 4000TEU container ship in the towing tank facility installed in the Pusan national university to know the validity of the developed algorithm for this study. As the results of the numerical analysis it proved that the resistance of the optimized hull is conspicuously reduced in comparison with the original hull in a wave-making resistance point of view.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1872-1882
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• 2017

Medium voltage drive systems driven by high-power multi-level inverters operating at low switching frequency can reduce the switching losses of the power device and increase the output power. Employing subsection synchronous current harmonic minimum pulse width modulation (CHMPWM) technique can maintain the total harmonic distortion of current at a very low level. It can also reduce the losses of the system, improve the system control performance and increase the efficiency of DC-link voltage accordingly. This paper proposes a subsection synchronous CHMPWM approach of active neutral point clamped five-level (ANPC-5L) inverter under low switching frequency operation. The subsection synchronous scheme is obtained by theoretical calculation based on the allowed maximum switching frequency. The genetic algorithm (GA) is adopted to get the high-precision initial values. So the expected switching angles can be achieved with the help of sequential quadratic programming (SQP) algorithm. The selection principle of multiple sets of the switching angles is also presented. Finally, the validity of the theoretical analysis and the superiority of the CHMPWM are verified through both the simulation results and experimental results.

• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.