• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.792-800
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• 2021

This paper presents a new structure for a linear active magnetic bearing using a Halbach magnet array. The proposed magnetic bearing consisted of a Halbach magnet array, center magnet, and single coil. The proposed linear active magnetic bearing has a high dynamic force compared to the previous study. The high dynamic force could be obtained by varying the thickness of a horizontally magnetized magnet. The new structure of Halbach linear active magnetic bearing has a high dynamic force. Therefore, the proposed linear active magnetic bearing increased the bandwidth of the system. Magnetic modeling and optimal design of the new structure of the Halbach linear active magnetic bearing were performed. The optimal design was executed on the geometric parameters of the proposed linear active magnetic bearing using Sequential Quadratic Programming. The proposed linear active magnetic bearing had a static force of 45.06 N and a Lorentz force constant of 19.54 N/A, which is higher than previous research.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.339-344
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• 2001

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 meta-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 meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.249-256
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• 1999

The conventional robot manipulability is decomposed into linear manipulability and angular manipulability so that they may be analysed and visualized in easy way even in the case of 3 dimensional task space with 6 variables. After the Jacobian matrix is decomposed into linear part and angular part, constraint on joint velocities is transformed into linear task velocity and angular task velocity through the decomposed Jacobian matrices. Under the assumption of redundant robot manipulators, several optimization problems which utilize the redundancy are formulated to be solved by linear programming technique or sequential quadratic programming technique. After deriving the solutions of the optimization problems, we give graphical interpretations for the solutions.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.194-196
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• 2001

This paper presents a hybrid algorithm 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. In OPF considering security, the outages are selected by contingency ranking method. 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. The method proposed is applied to the modified IEEE 14buses model system.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.714-716
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• 1996

This paper presents an optimization method for optimal reactive power dispatch which minimizes real power loss and improves voltage profile of power systems using evolutionary computation such as genetic algorithms(GAs), evolutionary programming(EP). and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most these approaches have the common defect of being caught to a local minimum solution. Recently, global search methods such as GAs, EP, and ES are introduced. The proposed methods were applied to the IEEE 30-bus system. Each simulation result, compared with that obtained by using a conventional gradient-based optimization method, Sequential Quadratic Programming (SQP), shows the possibility of applications of evolutionary computation to large scale power systems.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.493-504
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• 2011

The present paper presents a genetic algorithm (GA) to maximize social welfare and perform congestion management by optimally placing and sizing one Thyristor-Controlled Series Capacitor (TCSC) device in a double-sided auction market. Simulation results, with line flow constraints before and after the compensation, are compared through the Sequential Quadratic Programming SQP method, and are used to analyze the effect of TCSC on the congestion levels of modified IEEE 14-bus and 30-bus test systems. Quadratic, smooth and nonsmooth (with sine components due to valve point loading effect) generator cost curves, and quadratic smooth consumer benefit functions are considered. The main aims of the present study are the inclusion of customer benefit in the social welfare maximization and congestion management objective function, the consideration of nonsmooth generator characteristics, and the optimal locating and sizing of the TCSC using real code-based GA to guarantee fast convergence to the best solution.

• Structural Engineering and Mechanics
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• v.76 no.6
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• pp.799-821
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• 2020

The optimum design of truss structures is one of the significant categories in structural optimization that has widely been applied by researchers. In the present study, new mathematical programming called Consistent Approximation (CONAP) method is utilized for the simultaneous optimization of the size and shape of truss structures. The CONAP algorithm has already been introduced to optimize some structures and functions. In the CONAP algorithm, some important parameters are designed by employing design sensitivities to enhance the capability of the method and its consistency in various optimum design problems, especially structural optimization. The cross-sectional area of the bar elements and the nodal coordinates of the truss are assumed to be the size and shape design variables, respectively. The displacement, allowable stress and the Euler buckling stress are taken as the design constraints for the problem. In the proposed method, the primary optimization problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the sequential quadratic programming (SQP) algorithm. Several truss structures are designed by employing the CONAP method to illustrate the efficiency of the algorithm for simultaneous shape and size optimization. The optimal solutions are compared with some of the mathematical programming algorithms, the approximation methods and metaheuristic algorithms those reported in the literature. Results demonstrate that the accuracy of the optimization is improved and the convergence rate speeds up.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.8
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• pp.649-656
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• 2013

High-lift devices have a major influence on takeoff, landing and stall performance of an aircraft. Therefore, a slotted flap design optimization process is proposed in this paper to obtain the most effective flap configuration from supported 2D flap configuration. Flap deflection, Gap and Overlap are considered as main contributors to flap lift increment. ANSYS Fluent 13.0.0$^{(R)}$ is used as aerodynamic analysis software that provides accurate solution at given flight conditions. Optimum configuration is obtained by Sequential Quadratic Programing (SQP) algorithm. Performance of the aircraft with optimized flap is estimated using Aircraft Design Synthesis Program (ADSP), the in-house performance analysis code. Obtained parameters such as takeoff, landing distance and stall speed met KAS-VLA airworthiness requirements.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.46-55
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• 2006

In general, 3-dimensional point-mass equation has been widely used for the trajectory optimization of the fixed-wing aircraft and reentry vehicle. But it should be modified and represent target vehicle's own characteristics. For a lighter-than-air vehicle such as an airship, there exists different and peculiar flight characteristics compared with the aircraft. The first part of this paper is to derive the dynamic equation of motion for the mid-altitude unmanned airship and the second part is to obtain the optimal trajectories under the minimal time flight given constraints. The trajectory optimization problem is converted into the nonlinear programming problem using Sequential Quadratic Programming approach. Finally numerical solutions are presented in the last part of the paper.

• 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).