• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.65-68
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• 2008

The Mobile IP provides the mobility of Mobile Node, but does not provide the mobility of network. For support the mobility of network, the IETF has proposed NEMO(Network Mobility). Route Optimization is a serious problem in mobile network, so several solutions for route optimization in nested mobile network have been suggested by the IETF NEMO WG. This paper proposes scheme about Route Optimization in nested mobile network.

• Proceedings of the KSME Conference
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• 2001.06e
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• pp.684-689
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• 2001

In this study, three-dimensional viscous flow analysis and optimization are presented for the design of a mixed-flow fan. Steady, imcompressible, three-dimensional Reynolds averaged Navier-Stokes equations are used as governing equations, and standard $k-{\varepsilon}$ turbulence model is chosen as a turbulence model. Governimg equations are discretized using finite volume method. Upwind difference scheme is used for the discretization of the convective term and SIMPLEC algorithm is used as a velocity-pressure correction procedure. The computational results are compared with the results obtained by TASCflow. For the numerical optimization of the design, objective function is defined as a ratio of generation of the turbulent energy to pressure head. Sweep angles are used as design variables.

• Journal of Mechanical Science and Technology
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• v.14 no.9
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• pp.1005-1012
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• 2000

Numerical optimization techniques combined with a three-dimensional thin-layer Navier-Stokes solver are presented to find an optimum shape of a stator blade in an axial compressor through calculations of single stage rotor-stator flow. Governing differential equations are discretized using an explicit finite difference method and solved by a multi-stage Runge-Kutta scheme. Baldwin-Lomax model is chosen to describe turbulence. A spatially-varying time-step and an implicit residual smoothing are used to accelerate convergence. A steady mixing approach is used to pass information between stator and rotor blades. For numerical optimization, searching direction is found by the steepest decent and conjugate direction methods, and the golden section method is used to determine optimum moving distance along the searching direction. The object of present optimization is to maximize efficiency. An optimum stacking line is found to design a custom-tailored 3-dimensional blade for maximum efficiency with the other parameters fixed.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.2
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• pp.112-121
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• 2013

An approach for composing a performance optimized computational code is suggested for the latest microprocessors. The concept of the code optimization, termed localization, is maximizing the utilization of the second level cache that is common to all the latest computer systems, and minimizing the access to system main memory. In this study, the localized optimization of the LU-SGS (Lower-Upper Symmetric Gauss-Seidel) code for the solution of fluid dynamic equations was carried out in three different levels and tested for several different microprocessor architectures widely used these days. The test results of localized optimization showed a remarkable performance gain of more than two times faster solution than the baseline algorithm for producing exactly the same solution on the same computer system.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.176-184
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• 2002

The door stiffness is one of the important factors for the side impact. Generally, the researches have been conducted on the assembled door. A side impact door beam is installed in a door to protect occupants from the side impact. This research is only concentrated on the side impact beam and a side impact beam is designed. The cross section is defined to have an elliptic shape. An optimization problem is defined to find the design maximizing the intrusion stiffness within the specified weight. Design variables are the radii and the thickness of the ellipsoid. The analysis of the side impact is carried out by the nonlinear finite element method. The optimization problem is solved by two methods. One is the experimental design scheme using an orthogonal array. The other is the gradient-based optimization using the response surface method(RSM). Both methods have obtained the better designs than the current one.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.421-426
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• 2005

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes particle swarm optimization algorithm based optimal learning fuzzy-neural network (PSOA-FNN). The proposed learning scheme is the fuzzy-neural network structure which can handle linguistic knowledge as tuning membership function of fuzzy logic by particle swarm optimization algorithm. The learning algorithm of the PSOA-FNN is composed of two phases. The first phase is to find the initial membership functions of the fuzzy neural network model. In the second phase, particle swarm optimization algorithm is used for tuning of membership functions of the proposed model.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.411-418
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• 2004

Using a level set method we develop a shape optimization method applied to energy flow problems in steady state. The boundaries are implicitly represented by the level set function obtainable from the 'Hamilton-Jacobi type' equation with the 'Up-wind scheme.' The developed method defines a Lagrangian function for the constrained optimization. It minimizes a generalized compliance, satisfying the constraint of allowable volume through the variations of implicit boundary. During the optimization, the boundary velocity to integrate the Hamilton-Jacobi equation is obtained from the optimality condition for the Lagrangian function. Compared with the established topology optimization method, the developed one has no numerical instability such as checkerboard problems and easy representation of topological shape variations.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.1
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• pp.122-128
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• 2007

In this paper, a method of station keeping strategy using relative orbital motion and numerical optimization technique is presented for geostationary satellite. Relative position vector with respect to an ideal geostationary orbit is generated using high precision orbit propagation, and compressed in terms of polynomial and trigonometric function. Then, this relative orbit model is combined with optimization scheme to propose a very efficient and flexible method of station keeping planning. Proper selection of objective and constraint functions for optimization can yield a variety of station keeping methods improved over the classical ones. Nonlinear simulation results have been shown to support such concept.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.2 s.245
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• pp.128-134
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• 2006

Topology optimization is an effective scheme to obtain the initial design concept: however, it is hard to apply in case of non-linear or multi-objective problems. In this study, a modified topology optimization method is proposed to generate a structure of a swing arm type actuator satisfying maximum compliance as well. as maximum stiffness using the multi-objective optimization. approach. The multi-objective function is defined to maximize the compliance in the direction of focusing of the actuator and the second eigen-frequency of the structure. The design of experiments are performed and the response surface functions are formulated to construct the multi-objective function. The weighting factors between conflicting functions are determined by the back-error propagation neural network and the solution of multi-objective function is acquired using the genetic algorithm.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.571-575
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• 2008

An engine cradle is a quite important structural assembly for supporting the engine, suspension and steering parts of vehicle and absorbing the vibrations during the drive and the shock in the car crash. Recently, the engine cradle having structural stiffness enough to support the surrounding parts and absorbing the shock of collision has been widely used. The hydroforming technology may cause many advantages to automotive applications in terms of better structural integrity of parts, reduction of production cost, weight reduction, material saving, reduction in the number of joining processes and improvement of reliability. We focus on increasing the durability and the dynamic performance of engine cradle. For realizing this objective, several optimization design techniques such as shape, size, and topology optimization are performed. This optimization scheme based on the sensitivity can provide distinguished performance improvement in using hydroforming.