• Structural Engineering and Mechanics
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• v.48 no.3
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• pp.383-394
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• 2013

Cold-formed profiles have been largely used in the building industry because they can be easily produced and because they allow for a wide range of sections and thus can be utilized to meet different project requirements. Attainment of maximum performance by structural elements with low use of material is a challenge for engineering projects. This paper presents a numerical study aimed at minimizing the weight of lipped and unlipped cold-formed channel columns, following the AISI 2007 specification. Flexural, torsional and torsional-flexural buckling of columns was considered as constraints. The simulated annealing method was used for optimization. Several numerical simulations are presented and discussed to validate the proposal, in addition to an experimental example that qualifies its implementation. The ratios between lips, web width, and flange width are analyzed. Finally, it may be concluded that the optimization process yields excellent results in terms of cross-sectional area reduction.

• Computational Structural Engineering
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• v.3 no.1
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• pp.83-95
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• 1990

Many structural optimization problems are solved by numerical algorithms since these are complicated and nonlinear. To provide a wider base and popular it to structual design optimization, reliable, accurate and superlinearly convergent nonlinear programming algorithm with active-set strategy have been developed. One of these is RQP(recursive quadratic programming method). This algorithm has several parameters and its performance is influenced by variations of these key parameters. Therefore, an RQP algorithm is selected to enhance its numerical performances by choosing proper parameters. The paper persents these influences on its numerical performance. For comparison of performances, a structural design software for minimum weight of truss subjected to displacement, stress, and lower and upper bounds on design variables is also implemented.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.6
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• pp.24-30
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• 2018

Dental implants are currently widely used as artificial teeth due to their good chewing performance and long life cycle. A dental implant consists of an abutment as the upper part and a fixture as the lower part. When chewing forces are repeatedly applied to a dental implant, gap at the interface surface between the abutment and the fixture is often occurred, and results in some deteriorations such as loosening of fastening screw, dental retraction and fixture fracture. To cope with such problems, a sealing-type abutment having a number of grooves along the conical-surface circumference was previously developed, and shows better sealing performance than the conventional one. This study carries out optimization of the groove shape by genetic algorithm(GA) as well as structural analysis in consideration of external chewing force and pretension between the abutment and the fixture. The overall optimization system consists of two subsystems; the one is the genetic algorithm with MATLAB, and the other is the structural analysis with ANSYS. Two subsystems transmit and receive the relevant data with each other throughout the optimization processes. The optimization result is then compared with that of the conventional one with respect to the contact pressure and the maximum stress. The result shows that the optimized model gives better sealing performance than the conventional sealing abutment.

• Earthquakes and Structures
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• v.10 no.6
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• pp.1451-1465
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• 2016

The effectiveness of base isolation (BI) systems for mitigation of seismic vibration of bridges have been extensively studied in the past. It is well established in those studies that the performance of BI system is largely dependent on the characteristics of isolator yield strength. For optimum design of such systems, normally a standard nonlinear optimization problem is formulated to minimize the maximum response of the structure, referred as Stochastic Structural Optimization (SSO). The SSO of BI system is usually performed with reference to a problem of unconstrained optimization without imposing any restriction on the maximum isolator displacement. In this regard it is important to note that the isolator displacement should not be arbitrarily large to fulfil the serviceability requirements and to avoid the possibility of pounding to the adjacent units. The present study is intended to incorporate the effect of excessive isolator displacement in optimizing BI system to control seismic vibration effect of bridges. In doing so, the necessary stochastic response of the isolated bridge needs to be optimized is obtained in the framework of statistical linearization of the related nonlinear random vibration problem. A simply supported bridge is taken up to elucidate the effect of constraint condition on optimum design and overall performance of the isolated bridge compared to that of obtained by the conventional unconstrained optimization approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2108-2116
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• 2008

The paper concerns Fuzzy C-Means clustering based Radial Basis Function neural networks (FCM-RBFNN) and the optimization of the network is carried out by means of Particle Swarm Optimization(PSO). FCM-RBFNN is the extended architecture of Radial Basis Function Neural Network(RBFNN). In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values directly rely on the computation of the relevant distance between data points by means of FCM. Also, as the consequent part of fuzzy rules extracted by the FCM - RBFNN model, the order of four types of polynomials can be considered such as constant, linear, quadratic and modified quadratic. Weighted Least Square Estimator(WLSE) are used to estimates the coefficients of polynomial. Since the performance of FCM-RBFNN is affected by some parameters of FCM-RBFNN such as a specific subset of input variables, fuzzification coefficient of FCM, the number of rules and the order of polynomials of consequent part of fuzzy rule, we need the structural as well as parametric optimization of the network. In this study, the PSO is exploited to carry out the structural as well as parametric optimization of FCM-RBFNN. Moreover The proposed model is demonstrated with the use of numerical example and gas furnace data set.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.469-475
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• 2010

The objective of this study is to integrate reliability analysis into shape optimization problem using the evolutionary structural optimization (ESO) in the application example. Reliability-based shape optimization is formulated as volume minimization problem with probabilistic stress constraint under minimization max. von Mises stress and allow stress. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., reliability index approach (RIA), performance measure approach (PMA), single-loop singlevector (SLSV) and adaptive-loop (ADL), are used. Reliability-based shape optimization design process is conducted to obtain optimal shape satisfying max. von Mises stress and reliability index constraints with the above four methods, and then each result is compared with respect to numerical stability and computing time.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.1-8
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• 2012

Multidisciplinary design optimization (MDO) for a suspension component of the vehicle front suspension was performed in this research. Shapes and thicknesses of the subframe were optimized to satisfy multi-disciplinary design requirements; weight, fatigue, crash, noise, vibration, and harshness (NVH), and kinematic and compliance (K&C). Analyses procedures of the performance disciplines were integrated and automated by using the process integration and design optimization (PIDO) technique, and the integrated and automated analyses environments enabled various types of analytic design methodologies for solving the MDO problem. We applied an approximate optimization technique which involves sequential sampling and metamodeling. Since the design variables for thicknesses should be dealt as discrete variables. the evolutionary algorithm is selected as optimization technique. The MDO problem was formulated three types of problems according to the order of priorities among the performance disciplines, and the results of MDO provided design alternatives for various design situations.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.6
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• pp.1381-1388
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• 1993

This paper presents a method for the simultaneous optimal design of structural and control systems. Sensitivities of performance index with respect to structural design variables are analyzed. The structural design variables are optimized to minimize the performance index by use of conjugate gradient method. The method is applied to a half model of an active vehicle suspension system with elastic body moving on a randomly profiled road. The suspension control force of an optimally controlled system in the presence of measurement errors are calculated by use of linear quadratic Gaussian control theory and Kalman filter theory. The performance index contains ride comfort, road holding and working space of suspension. The structural design variables taken are stiffness, daming properties and the position of the suspension system. The random road profile considered as colored noise is shaped from white noise by use of shaping filter. The performance of an optimal simultaneous structure/control system is compared with that of an optimal controlled system.

• Steel and Composite Structures
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• v.42 no.6
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• pp.855-864
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• 2022

Due to limited resources, and increasing speed of development, the optimal use of available resources has become the most important challenge of human societies. In the last few decades, many researchers have focused their research on solving various optimization problems, providing new optimization methods, and improving the performance of existing optimization methods. Echolocation Search Algorithm (ESA) is an evolutionary optimization algorithm that is based on mimicking the mechanism of the animals such as bats, dolphins, oilbirds, etc in food finding to solve optimization problems. In this paper, the ability of ESA for solving truss size optimization problems with continuous variables is investigated. To examine the efficiency of ESA, three benchmark examples are considered. The numerical results exhibit the effectiveness of ESA for solving truss optimization problems.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.691-697
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• 2010

Reliability-based topology optimization (RBTO) is to get an optimal topology satisfying uncertainties of design variables. In this study, reliability-based topology optimization method is applied to the inner reinforcement of vehicle's hood based on BESO. A multi-objective topology optimization technique was implemented to obtain optimal topology of the inner reinforcement of the hood. considering the static stiffness of bending and torsion as well as natural frequency. Performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints. To evaluate the obtained optimal topology by RBTO, it is compared with that of DTO of the inner reinforcement of the hood. It is found that the more suitable topology is obtained through RBTO than DTO even though the final volume of RBTO is a little bit larger than that of DTO. From the result, multiobjective optimization technique based on the BESO can be applied very effectively in topology optimization for vehicle's hood reinforcement considering the static stiffness of bending and torsion as well as natural frequency.