• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.6
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• pp.423-429
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• 2003

On this study. we improved the efficiency applying algorithm that is repeatedly using table of orthogonal array in discrete design space and filling a defect of gradient method in continuous design space. we showed optimal ply angle that maximized 1st natural frequency of CFRP laminated composite plate without a hole and with a hole by each aspect ratio. In the case of CFRP laminated composite plate without a hole, we confirmed the reliance and efficiency of algorithm in comparison with the result of optimization achievement repeatedly using statistical table of orthogonal array of experimental design and the BFGS optimal design method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.3
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• pp.302-307
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• 2015

The automobile is an important means of transportation. For this reason, the automotive wheel is also an important component in the automotive industry because it acts as a load support and is closely related to safety. Thus, the wheel design is a very important safety aspect. In this paper, an optimal design for minimizing automotive wheel stress and increasing wheel safety is described. To study the optimal design, a central composite design (CCD) and D-optimal design theory are applied, and the approximate function using the response surface method (RSM) is generated. The optimal solutions using the non-dominant sorting genetic algorithm (NSGA-II) are then derived. Comparing CCD and D-optimal solution accuracy and verified the CCD can deduce more accuracy optimal solutions.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1092-1097
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• 2005

In this paper, design approach of PID controller with rejection function against external disturbance in motor control system is proposed using bacterial foraging based optimal algorithm. Up to the present time, PID Controller has been used to operate for AC motor drive because of its implementational advantages in practice and simple structure. However, it is not easy to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error in the industrial system with disturbance. To design disturbance rejection tuning, disturbance rejection conditions based on $H_{\infty}$ are illustrated and the performance of response based on the bacterial foraging is computed for the designed PID controller as ITSE (Integral of time weighted squared error). Hence, parameters of PID controller are selected by bacterial foraging based optimal algorithm to obtain the required response

• Transactions of Materials Processing
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• v.9 no.6
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• pp.644-652
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• 2000

Tube hydroforming is recently drawing attention of automotive industries due to its several advantages over conventional methods. It can produce wide range of products such as subframes, engine cradles, and exhaust manifolds with cheaper production cost by reducing overall number of processes. h successful tube hydroforming depends on the reasonable combination of the internal pressure and axial load at the tube ends. This paper deals with the optimal process design of hydroforming process using the genetic algorithm and neural network. An optimization technique is used in order to minimize the tube thickness variation by determining the optimal loading path in the tube expansion forming and the tube T-shape forming process.

• Smart Structures and Systems
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• v.26 no.5
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• pp.591-603
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• 2020

Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1382-1387
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• 1999

This paper presents an optimal fuzzy power system stabilizer to damp out low frequency oscillation. So far fuzzy controllers have been applied to power system stabilizing controllers due to its excellent properties on the nonlinear systems. But the design process of fuzzy logic power system stabilizer requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This paper presents and optimal design method of the fuzzy logic stabilizer using the genetic algorithm. Non-symmetric membership functions are optimally tuned over an evaluation function. The present inputs of fuzzy stabilizer are torque angle error and the change of torque angle error without loss of generality. The coding method used in this paper is concatenated binary mapping. Each linguistic fuzzy variable, defined as the peak of a membership function, is assigned by the mapping from a minimum value to a maximum value using eight bits. The tournament selection and the elitism are used to keep the worthy individuals in the next generation. The proposed system is applied to the one-machine infinite-bus model of a power system, and the results showed a promising possibility.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.677-689
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• 2022

Generally, the goal of seismic retrofit design of an existing structure using energy dissipation devices is to determine the optimum design parameters of a retrofit device to satisfy a specified limit state with minimum cost. However, the presence of multiple parameters to be optimized and the computational complexity of performing non-linear analysis make it difficult to find the optimal design parameters in the realistic 3D structure. In this study, genetic algorithm-based optimal seismic retrofit methods for determining the required number, yield strength, and location of steel slit dampers are proposed to retrofit an asymmetric soft first-story structure. These methods use a multi-objective and single-objective evolutionary algorithms, each of which varies in computational complexity and incorporates nonlinear time-history analysis to determine seismic performance. Pareto-optimal solutions of the multi-objective optimization are found using a non-dominated sorting genetic algorithm (NSGA-II). It is demonstrated that the developed multi-objective optimization methods can determine the optimum number, yield strength, and location of dampers that satisfy the given limit state of a three-dimensional asymmetric soft first-story structure. It is also shown that the single-objective distribution method based on minimizing plan-wise stiffness eccentricity turns out to produce similar number of dampers in optimum locations without time consuming nonlinear dynamic analysis.

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.55-61
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• 2022

Along with global environmental issues, the size of the electric vehicle market has recently skyrocketed. Various efforts have been made to extend mileage, one of the biggest problems of the electric vehicles, and development of batteries with high energy densities has led to exponential growth in mileage and performance. However, proper thermal management is essential because these high-performance batteries are affected by continuous heat generation and can cause fires due to thermal runaway phenomena. Therefore, thermal management of the battery is studied through the optimal design of the guide vanes, while utilizing the existing battery casing to ensure the safety of the electric vehicles. A battery from T-company, one of a manufacturer of the electric vehicles, was used for the research, and the commercial CFD software, ANSYS CFX V20.2, was used for analysis. The guide vanes were derived through optimal design based on a genetic algorithm with flow analysis. The optimized guide vanes show improved heat removal performance.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.173-182
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• 2001

Ascent trajectory optimization and optimal explicit guidance problems for a satellite launch vehicle in a 2-dimensional pitch plane are studied. The trajectory optimization problem with boundary conditions is formulated as a nonlinear programming problem by parameterizing the pitch attitude control variable, and is solved by using the SQP algorithm. The flight constraints such as gravity-turn are imposed. An optimal explicit guidance algorithm in the exoatmospheric phase is also presented, the guidance algorithm provides steering command and time-to-go value directly using the current states of the vehicle and the desired orbit insertion conditions. To verify the optimality and accuracy of the algorithm simulations are performed.

• Design & Manufacturing
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• v.17 no.3
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• pp.41-47
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• 2023

This paper presents the development of a controller that can control the temperature of an heating system based on a thermoelectric module. Temperature controller using Peltier has various external factors such as external temperature, characteristics of an aluminum plate, installation location of temperature sensors, and combination method between the aluminum plate and heating element. Therefore, it is difficult to apply the simulation and simulation results of heating system using Peltier at control algorithm. In general, almost temperature controller is using PID algorithm that finds control gain value heuristically. In this paper, it is proposed mathematical model that explain correlate between the temperature of the heating system and input voltage. And then, optimal parameter of estimated thermal model of the aluminum plate are searched by using genetic algorithm. In addition, based on this estimated model, the optimal PID control gain are inferred using a genetic algorithm. All of the sequence are simulated and verified with proposed real system.