• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.2
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• pp.236-247
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• 1992

Optimization has been developed to minimize the cost function while satisfying constraints. Nonlinear Programming method is used as a tool for the optimization. Usually, cost and constraint function calculations are required in the engineering applications, but those calculations are extremely expensive. Especially, the function and sensitivity analyses cause a bottleneck in structural optimization which utilizes the Finite Element Method. Also, when the functions are quite noisy, the informations do not carry out proper role in the optimization process. An algorithm called "Second-order Approximation Method" has been proposed to overcome the difficulties recently. The cost and constraint functions are approximated by the second-order Taylor series expansion on a nominal points in the algorithm. An optimal design problem is defined with the approximated functions and the approximated problem is solved by a nonlinear programming numerical algorithm. The solution is included in a candidate point set which is evaluated for a new nominal point. Since the functions are approximated only by the function values, sensitivity informations are not needed. One-dimensional line search is unnecessary due to the fact that the nonlinear algorithm handles the approximated functions. In this research, the method is analyzed and the performance is evaluated. Several mathematical problems are created and some standard engineering problems are selected for the evaluation. Through numerical results, applicabilities of the algorithm to large scale and complex problems are presented.presented.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.42-52
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• 2006

In order to utilize hydrodynamic drag force on articulated robots moving in an underwater environment, an optimum motion planning procedure is proposed. The drag force acting on cylindrical underwater arms is modeled and a directional drag measure is defined as a quantitative measure of reaction force in a specific direction in a workspace. A repetitive trajectory planning method is formulated from the general point-to-point trajectory planning method. In order to globally optimize the parameters of repetitive trajectories under inequality constraints, a 2-level optimization scheme is proposed, which adopts the genetic algorithm (GA) as the 1st level optimization and sequential quadratic programming (SQP) as the 2nd level optimization. To verify the validity of the proposed method, optimization examples of periodic motion planning with the simple two-link planner robot are also presented in this paper.

• The KSFM Journal of Fluid Machinery
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• v.11 no.2
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• pp.38-45
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• 2008

This study presents a numerical procedure to optimize the compressor design to increase the surge margin of compressor with response surface method (RSM). The Box-Behnken design method is used to reduce the number of calculation for fitting the second-order response surface. In order to consider the increase of surge margin during numerical optimization without any calculation at the surge point, the slope of compressor characteristic curve at the design point is suggested as an objective function in the present optimization problem. Mean line performance analysis method is used to get the design and off-design characteristic curves of centrifugal compressor. The impeller exit angle, impeller exit height and impeller radius are chosen as design variables. The optimum shapes show the increase of surge margin for the surge margin optimization and increase of efficiency for the efficiency optimization in comparison with an initial shape.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.159-166
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• 2019

Due to the various engagement situations, it is very difficult to generate the optimal trajectory with several constraints. This paper investigates the sequential convex programming for the impact angle control with the additional constraint of altitude limit. Recently, the SOCP(Second-Order Cone Programming), which is one area of the convex optimization, is widely used to solve variable optimal problems because it is robust to initial values, and resolves problems quickly and reliably. The trajectory optimization problem is reconstructed as convex optimization problem using appropriate linearization and discretization. Finally, simulation results are compared with analytic result and nonlinear optimization result for verification.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.1
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• pp.72-79
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• 2017

A full treatment of damping material is not an effective method because the damping effect is not significantly increased compared to that obtained by an effective partial damping treatment. Thus, a variety of methodologies has been considered in order to achieve an optimal damping treatment. One of the widely applied approaches is topology optimization. However, the high computational expenses can be an issue in topology optimization. A new efficient convergence criterion, reducible design variable method (RDVM), is applied to reduce computational expense in topology optimization. The idea of RDVM topology optimization is to adaptively reduce the number of design variables based on the history. The iteration repeats until the number of design variables becomes zero. The aim of this research is to adopt RDVM topology optimization into obtaining an optimal damping treatment. In order to demonstrate the effectiveness and efficiency of RDVM topology optimization, optimal damping layouts and computational expenses are compared between conventional and RDVM topology optimization.

• Architectural research
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• v.14 no.1
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• pp.19-26
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• 2012

The technique of integrated design optimization is proposed to design spatial structures. Various element technologies such as topology optimization, layout editing and size optimization processes are used in an integrated manner to improve the performance of spatial structures. In order to demonstrate the present technique, a unit spatial structure is optimized and numerical results are described here.

• Journal of applied mathematics & informatics
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• v.26 no.1_2
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• pp.223-233
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• 2008

In this paper we give sufficient conditions for a point to be a solution of an optimization problem in complex space.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.20 no.3
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• pp.225-242
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• 2016

The phase-type representation is strongly connected with the positive realization in positive system. We attempt to transform phase-type representation into sparse mono-cyclic positive representation with as low order as possible. Because equivalent positive representations of a given phase-type distribution are non-unique, it is important to find a simple sparse positive representation with lower order that leads to more effective use in applications. A Hypo-Feedback-Coxian Block (HFCB) representation is a good candidate for a simple sparse representation. Our objective is to find an HFCB representation with possibly lower order, including all the eigenvalues of the original generator. We introduce an efficient nonlinear optimization method for computing an HFCB representation from a given phase-type representation. We discuss numerical problems encountered when finding efficiently a stable solution of the nonlinear constrained optimization problem. Numerical simulations are performed to show the effectiveness of the proposed algorithm.

• Transactions of Materials Processing
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• v.15 no.9 s.90
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• pp.679-685
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• 2006

New method for evaluation of heat transfer coefficient is proposed. In general, many researchers have been studied about inverse problem in order to calculate the heat transfer coefficient on three-dimensional heat conduction problem. But they can get the time-dependent heat transfer coefficient only through inverse problem. In order to acquire temperature-dependent heat transfer coefficient, it requires much time for numerous repetitive calculation and inconvenient manual modification. In order to solve these problems, we are using the SQP(Sequential Quadratic Programming) as an optimization algorithm. When the temperature history is given by experiment, the optimization algorithm can evaluate the temperature-dependent heat transfer coefficient with automatic repetitive calculation until difference between calculated temperature history and experimental ones is minimized. Finally, temperature-dependent heat transfer coefficient evaluated by developed program can used on various heat transfer problem.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.378-383
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• 2001

In order to improve automobile maneuverability and tire durability, it is very important for one to determine a suitable sidewall contour producing the ideal tension and strain-energy distributions. In order to determine such a sidewall contour, one must apply multi-objective optimization technique. The optimization problem of tire carcass contour involves several objective functions. Hence, we execute the tire contour optimization for improving the maneuverability and the tire durability using satisficing trade-off method. And, the tire optimization also requires long cup time for the sensitivity analysis. In order to resolve this numerical difficulty, we apply neural network algorithm.