• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.239-242
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• 2001

This paper presents a windows program package for solving security constrained OPF in interconnected power systems, which is based on the combined application of evolutionary programming(EP) and sequential quadratic programming(SQP). The objective functions are the minimization of generation fuel costs and system power losses. The control variables are the active power of the generating units, the voltage magnitude of the generator, transformer tap settings and SVC setting. The state variables are the bus voltage magnitude, the reactive power of the generating unit, line flows and the tie line flow. In OPF considering security, the outages are selected by contingency ranking method. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). The OPF package proposed is applied to 10 machines 39 buses model system.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.318-324
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• 2006

The mobile manipulator is expected to work in partially defined or unstructured environments. In our global/local approach to path planning, joint trajectories are generated for a desired Cartesian space path, designed by the global path planner. For a local path planner, inverse kinematics for a redundant system is used. Joint displacement limit for the manipulator links is considered in the motion planner. In an event of failure to obtain feasible trajectories, the task cannot be accomplished. At the point of failure, a deviation in the Cartesian space path is obtained and a replanner gives a new path that would achieve the goal position. To calculate the deviation, a nonlinear optimization problem is formulated and solved by standard Sequential Quadratic Programming (SQP) method.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.169-171
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• 2004

Available transfer capability(ATC) is an important indicator of the usable amount of transmission capacity accessible by several parties for commercial trading in power transaction activities. This paper deals with an application of optimization technique for available transfer capability(ATC) calculation and analyzes the results of ATC by considering several constraints. Sequential quadratic programming(SQP) is used to calculate the ATC problem with state-steady security constraints. The proposed method is applied to 10 machines 39 buses model systems to show its effectiveness.

• Proceedings of the KIEE Conference
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• summer
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• pp.183-185
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• 2004

This paper deals with an application of optimization technique for available transfer capability(ATC) calculation. ATC is an important indicator of the usable amount of transmission capacity accessible by several parties for commercial trading. Sequential quadratic programming(SQP) is used to calculate the ATC problem with state-steady security constraints. The proposed method is applied to 10 machines 39 buses model systems. The results are discussed and compared to those obtained by continuation power flow(CPF).

• Proceedings of the Korean Geotechical Society Conference
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• 2001.10c
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• pp.103-122
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• 2001

For prediction of ground movement per the excavation step, observational results of ground movement during the construction was very different with prediction during the analysis of design. step because of the uncertainty of the numerical analysis modelling, the soil parameter, and the condition of a construction field, etc. however accuratly numerical analysis method was applied. Therefore, the management system through the construction field measurement should be achieved for grasping the situation during the excavation. Until present, the measurement system restricted by ‘Absolute Value Management system’only analyzing the stability of present step was executed. So, it was difficult situation to expect the prediction of ground movement for the next excavation step. In this situation, it was developed that ‘The Management system TOMAS-EXCAV’ consisted of ‘Absolute value management system’ analyzing the stability of present step and ‘Prediction management system’ expecting the ground movement of next excavation step and analyzing the stability of next excavation step by‘Back Analysis’. TOMAS-EXCAV could be applied to all uncertainty of earth retaining structures analysis by connecting ‘Forward analysis program’ and ‘Back analysis program’ and optimizing the main design variables using SQP-MMFD optimization method through measurement results. The application of TOMAS-EXCAV was confirmed that verifed the three earth retaing construction field by back analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.144-151
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• 2003

In this paper, an optimum design problem for endosseous implant in dentistry is studied to find best implant design. An optimum design problem is formulated to reduce stresses arising at the cortical as well as cancellous bones, in which sufficient design parameters are chosen fur design definition that encompasses major implants in popular use. Optimization at once (OAO) with the large number of design variables, however, causes too costly solution or even failure to converge. A concept of multilevel optimization (MLO) is employed to this end, which is to group the design variables of similar nature, solve the sub-problem of smaller size fur each group in sequence, and this is iterated until convergence. Each sub-problem is solved based on the response surface method (RSM) due to its efficiency for small sized problem. Favorable solution is obtained by the MLO, which is compared to both solutions made by RSM and sequential quadratic programming (SQP) in the OAO problem.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.864-870
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• 2003

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM(Finite Element Method) and BEM(Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta -modeling technique has been developed for solving such a complex problems combined with the DACE(Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building approximation models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty -six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging model of a train suspension. After each Kriging model is constructed, multi -objective optimal solutions are achieved by using a nonlinear programming method called SQP(Sequential Quadratic Programming).

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.74-80
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• 2006

This paper addresses the trajectory optimization of Unmanned Aerial Vehicles(UAVs) under multiple ground threats like enemy's anti-air radar sites. The power of radar signal reflected by the vehicle and the flight time are considered in the performance cost to be minimized. The bank angle is regarded as control input for a 1st-order lag vehicle, and input parameter optimization method based on Sequential Quadratic Programming (SQP) is used for trajectory optimization. The proposed path planning method provides more practical trajectories with enhanced survivability than those of Voronoi diagram method.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.37-42
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• 2003

Fundamental Study for optimizing ship hull form using SQP(sequential quadratic programming) method in a resistance point of view is presented. The Wigley hull is used as an initial hull and numerical calculations are carried out according to various froude numbers. To obtain the ship resistance the wave resistance is evaluated by a Rankine source panel method with nonlinear free surface conditions and the ITTC 1957 friction line is used to predict the frictional resistance coefficient. The geometry of a hull surface is represented and modified by B-spline surface patch. The displacement and the waterplane transverse 2nd moment of inertia of the hull is fixed during the optimization process. And the shp design program called EzHULL is used to draw the lines of the optimized hull form to perform the model test.