• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.3
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• pp.82-88
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• 2003

SGA(Single Genetic Algorithm) is a heuristic global optimization method based on the natural characteristics and uses many populations and stochastic rules. Therefore SGA needs many function evaluations and takes much time for convergence. In order to solve the demerits of SGA, ${\mu}GA$(Micro-Genetic Algorithm) has recently been developed. In this study, ${\mu}GA$ which have small populations and fast convergence rate, was applied to structural optimization with discrete or integer variables such as 3, 10 and 25 bar trusses. The optimized results of ${\mu}GA$ were compared with those of SGA. Solutions of ${\mu}GA$ for structural optimization were very similar or superior to those of SGA, and faster convergence rate was obtained. From the results of examples, it is found that ${\mu}GA$ is a suitable and very efficient optimization algorithm for structural design.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.158-166
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• 2003

The paper describes the development and application of advanced evolutionary computing techniques referred to as micro genetic algorithms ($\mu$GA) in the context of engineering design optimization. The basic concept behind $\mu$GA draws from the use of small size of population irrespective of the bit string length in the representation of design variable. Such strategies also demonstrate the faster convergence capability and more savings in computational resource requirements than simple genetic algorithms (SGA). The paper first explores ten-bar truss design problems to see the optimization performance between $\mu$GA and SGA. Subsequently, $\mu$GA is applied to a realistic engineering design problem in the injection molding process optimization.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.9-14
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• 2003

SGA (Single Genetic Algorithm) is a heuristic global optimization method based on the natural characteristics and uses many populations and stochastic rules. Therefore SGA needs many function evaluations and takes much time for convergence. In order to solve the demerits of SGA, $\mu$GA(Micro-Genetic Algorithm) has recently been developed. In this study, $\mu$GA which have small populations and fast convergence rate, was applied to structural optimization with discrete or integer variables such as 3, 10 and 25 bar trusses. The optimized results of $\mu$GA were compared with those of SGA. Solutions of $\mu$GA for structural optimization were very similar or superior to those of SGA, and faster convergence rate was obtained. From the results of examples, it is found that $\mu$GA is a suitable and very efficient optimization algorithm for structural design.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.260-263
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• 1987

In this study, PC-based FEA system (Micro-STANS) running on the 16 bit microcomputer is developed. This system has powerful pre & post processing function using computer graphics, and is interfaced to AutoCAD system which is most popular PC-CAD system, making it possible to accomplish the concept of real integration between design and analysis. This system which has truss , beam plate & shell elements in the element library, can perform linear static analysis.

• Journal of the Korean Society for Advanced Composite Structures
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• v.2 no.3
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• pp.1-11
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• 2011

The typical truss-lattice material successively packed by repeated cubic symmetric unit cells consists of sub-elements (SE) proposed in this study. The representative continuum model for this truss-lattice material such as the effective strain and stress relationship can be formulated by the homogenization procedure based on the notation of averaged mechanical properties. The volume fractions of micro-scale struts have a significant influence on the effective strength as well as the relative density in the lattice plate with replicable unit cell structures. Most of the strength contribution in the lattice material is induced by axial stiffness under uniform stretching or compression responses. Therefore, continuum based constitutive models composed of homogenized member stiffness include these mechanical characteristics with respect to strength, internal stress state, material density based on the volume fraction and even failure modes. It can be also recognized that the stress state of micro-scale struts is directly associated with the continuum constitutive model. The plastic flow at the micro-scale stress can extend the envelope of the analytical stress function on the surface of macro-scale stress derived from homogenized constitutive equations. The main focus of this study is to investigate the basic topology of unit cell structures with the cubic symmetric system and to formulate the plastic models to predict pressure dependent macro-scale stress surface functions.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.161-167
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• 2008

In this paper, the optimal design of trusses using advanced analysis and genetic algorithm is performed. An advanced analysis takes into account geometric nonlinearity and material nonlinearity. The micro genetic algorithm is used as optimization technique. The weight of structures is treated as the objective function. The constraint functions are defined by load-carrying capacities and displacement requirement. The effectiveness of the proposed method is verified by comparing the results of the proposed method with those of other method.

• Steel and Composite Structures
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• v.43 no.5
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• pp.565-579
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• 2022

This study investigated the yielding capacity and performance of seismic dampers constructed with steel ring plates using numerical and analytical approaches. This study aims to provide an analytical relationship for estimating the yielding capacity and initial stiffness of steel ring dampers. Using plastic analysis and considering the mechanism of plastic hinge formation, a relation has been obtained for estimating the yielding capacity of steel ring dampers. Extensive parametric studies have been carried out using a nonlinear finite element method to examine the accuracy of the obtained analytical relationships. The parametric studies include investigating the influence of the length, thickness, and diameter of the ring of steel ring dampers. To this end, comprehensive verification studies are performed by comparing the numerical predictions with several reported experimental results to demonstrate the numerical method's reliability and accuracy. Comparison is made between the hysteresis curves, and failure modes predicted numerically or obtained/observed experimentally. Good agreement is observed between the numerical simulations and the analytical predictions for the yielding force and initial stiffness. The difference between the numerical models' ultimate tensile and compressive capacities was observed that average of about 22%, which stems from the performance of the ring-dampers in the tensile and compression zones. The results show that the steel ring-dampers are exhibited high energy dissipation capacity and ductility. The ductility parameters for steel ring-damper between values were 7.5 to 4.1.