• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.6
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• pp.347-353
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• 2021

In this study, we presented a novel size optimization framework to control the linear buckling temperature and several buckling modes of plates, by optimizing thickness values of composite structures for practical engineering applications. Predicting the buckling temperature and mode shape of structures is a vital research topic in engineering to achieve structural stability. However, optimizing designs of engineering structures through engineering intuition is challenging. To address this limitation, we proposed a method that combines finite element simulation and size optimization. Based on the idea that the structural buckling temperature and mode shape of a plate are affected by the thickness of the structure, the thickness values of the nodes of the target structure were set as the design variables in this optimization method; and the buckling temperature values, and buckling mode shapes were set as the objective functions. This size optimization method enabled the determination of optimal thickness distributions, to induce the desired buckling temperature values and mode shapes. The validity of the proposed method was verified in terms of their buckling temperature values and buckling mode shapes, using several numerical examples of rectangular composite structures.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.213-221
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• 2011

In this study, we discussed the weight reducing of a urban railway-car body, in particular, of the Korean EMU, by optimizing topology and size of aluminum extrusion profiles. The heaviest parts of aluminum railway-car bodies, i.e., the base plate of underframe and side panels of side frame composed of double skin structures are considered for optimization. Topology optimization process is applied to obtain get an optimized rib structure for the base plate. The thickness of ribs and plates of the topologically optimized base plate and the existing side panel are also optimized by employing the size optimization process. The results are verified by comparing the maximum von Mises stresses and maximum deformation in the case of the existing design with those in the case of the optimized design. It is shown that the weight of a base plate and side panel can be reduced by 12% and that the weight of the whole car body can be reduced by 8.5%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.2 s.257
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• pp.269-276
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• 2007

Optimal thickness and shape of the pedal arm of an automotive clutch is determined, using the numerical optimization technique, by solving the size and shape optimization problems to minimize its weight. For the optimization problems, two cases of stress and displacement constraints are considered: one from the vertical, and the other from the transverse stiffness test condition. The result of the transverse case is shown to be more conservative than that from the vertical case, being determined as the final optimum.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.183-190
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• 2011

As the number of mobile subscribers has increased recently, the demand for more number of base stations has increased. However, because of the shortage of sites for constructing base stations, a mobile communication module needs to be small in size. To minimize the size of the module, the size of the heat sink attached to the outside of the module should be minimized. Furthermore, the temperature of each electronic component of the module should be lower than the allowable temperature so that thermal stability can be maintained. A commercial PIDO (process integration and design optimization) tool PIAnO and a commercial CFD (computational fluid dynamics) tool FLOTHERM are used to minimize the size of the module while the constraints on the temperatures of the twelve electronic components are satisfied. As a result of design optimization, the volume of the heat sink is reduced by 41.9% while all the constraints on the temperature of the twelve electronic components of the module are satisfied.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.659-668
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• 2018

This paper proposes an optimization approach of a grid-connected photovoltaic and wind hybrid energy system including energy storage considering voltage fluctuation in the electricity grid. A techno-economic analysis is carried out in order to minimize the size of hybrid system by considering the benefit-cost. Lithium-ion battery type is used for both managing the electricity selling to the grid and reducing voltage fluctuation. A new technique is developed to limit the voltage perturbation caused by the solar irradiance and the wind speed through determining the state-of-charge of battery for every hour of a day. Improved particle swarm optimization (PSO) methods, referred to as FC-VACPSO which combines Fast Convergence Particle Swarm Optimization (FCPSO) method and Variable Acceleration Coefficient Based Particle Swarm Optimization (VACPSO) method are used to solve the optimization problem. A comparative study has been performed between standard PSO method and PSO based methods to extract the best size with the benefit cost. A sensitivity analysis has been studied for different kinds and costs of batteries, by considering variable and constant state-ofcharge of battery. The simulations, performed under Matlab environment, yield good results using the FC-VACPSO method regarding the convergence and the benefit cost of the hybrid system.

• Journal of Korean Association for Spatial Structures
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• v.2 no.3 s.5
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• pp.93-102
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• 2002

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.350-353
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• 1996

In this paper, based on the performance analysis of serial production lines with quality inspection machines, we develope an buffer size optimization method to maximize the production rate. The total sum of buffer sizes are given and a constant, and under this constraint, using the linear approximation method, we suggest a closed form solution for the optimization problem with an acceptable error. Also, we show that the upstream and downstream buffers of the worst performance machine have a significant effect on the production rate. Finally, the suggested methods are validated by simulations.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.403-407
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• 2012

The purpose of this study is to find the optimum skirt size for a composite pressure vessel using optimum analysis technique. The size optimization for skirt shape of a composite pressure vessel was conducted using sub-problem approximation method and batch processing codes programmed by APDL(ANSYS Parametric Design Language). The thickness and length of skirt part were selected as design variables for the optimum analysis. The objective function and constraints were chosen as weight and displacement of skirt part, respectively. The numerical results showed that the weight of skirt of a composite pressure vessel would be saved by maximum 4.38% through the size optimization analysis for the skirt shape.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.822-826
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• 2008

A linkage mechanism is a device to convert an input motion into a desired output motion. Traditional linkage mechanism designs are based on trial and error approaches so that size or shape changes of an original mechanism often result in improper results. In order to resolve these problems, an improved automatic mechanism synthesis method that determines the linkage type and dimensions by using an optimization method during the synthesis process has been proposed. For the synthesis, a planar linkage is modeled as a set of rigid blocks connected by zero-length translational springs with variable stiffness. In this study, the sizes of rigid blocks were also treated as design variables for more general linkage synthesis. The values of spring stiffness and the size of rigid block yielding a desired output motion at the end-effecter are found by using an optimization method.

• Structural Engineering and Mechanics
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• v.73 no.4
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• pp.463-479
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• 2020

This paper is aimed to address a simultaneous optimization of the size, shape, and topology of steel lattice towers through a combination of the radial basis function (RBF) neural networks and the artificial bee colony (ABC) metaheuristic algorithm to reduce the computational time because mere metaheuristic optimization algorithms require much time for calculations. To verify the results, use has been made of the CIGRE Tower and a 132 kV transmission towers as numerical examples both based on the design requirements of the ASCE10-97, and the size, shape, and topology have been optimized (in both cases) once by the RBF neural network and once by the MSTOWER analyzer. A comparison of the results shows that the neural network-based method has been able to yield acceptable results through much less computational time.