• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.5
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• pp.37-43
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• 2002

In this paper, an integrated optimum design method for hybrid structural control system is studied. Not only the distribution and the capacity of passive devices but also those of active devices, and the controllers are treated as design variables in the proposed approach. Multi-objective optimization problem is formulated by using the preference function, which is newly defined in this study. Genetic algorithm is adopted as a numerical searching technique in order to simultaneously find the optimum solutions. The validity of the proposed method is verified through the example designs and the numerical simulations of an earthquake excited multi-degrees-of-freedom structure.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.18 no.3
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• pp.219-226
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• 2005

In this study, the problem formulation and solution technique using genetic algorithms for design optimization of laminate composite cylindrical beam section are presented. The hollow cylindrical beams we usually used in the wheel chair. If the weight of wheel chair is reduced, it will lead to huge improvement in passenger's mobility and comfort. In this context, the replacement of steel by high performance and light weight composite material along with optimal design will be a good contribution in the process of weight reduction of a wheel chair. An artificial genetics approach for the design optimization of hollow cylindrical composite beam is presented. On applying the genetic algorithm, the optimal dimensions of hollow cylindrical composite beams which have equivalent rigidities to those of corresponding hollow cylindrical steel beams are obtained. Also structural analysis is conducted on the entire wheel chair structure incorporating Tsai-Wu failure criteria. The maximum Tsai-Wu failure criteria index is $0.192\times10^{-3}$ which is moth less than value of 1.00 indicating no failure is observed under excessive loading condition. It is found that the substitution of steel by composite material could reduce the weight of wheel chair up to 45%.

• Composites Research
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• v.13 no.2
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• pp.61-71
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• 2000

Today, the use of composite materials become an essential part in the design and manufacturing process of the flight vehicles to reduce the structural weight. Since the structural properties can be varied largely due to the stacking sequence of ply angles, it is very important problem to determine the optimized ply angles under a design objective. Thus, in this study, the analysis of static aeroelastic optimization of a composite wing has been performed. An analytical system to calculate and optimize tile aero-structural equilibrium position has been developed and incorporated with the genetic algorithm. The effects of stacking sequence on the structural deformation and aerodynamic distribution have been studied and calculated with the condition of minimum structural deformation for a swept-back composite wing. For the set of practical stacking angles, the design results to maximize the performance of static aeroelasticity are also presented.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.23-27
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• 2007

To store hydrogen with high pressure is one of key technologies in developing FCVs (fuel cell vehicles). Especially, metal lined composite structure, which is called Type 3, is expected to effectively stand highly pressurized hydrogen since it has high specific strength and stiffness as well as excellent storage ability. However, it has many difficulties to design Type 3 vessels because of their complex geometry, fabrication process variables, etc. In this study, therefore, optimal design of Type 3 vessels was performed in consideration of such actual circumstances using genetic algorithm. Additionally, detailed finite element analysis was followed for the optimal result.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2269-2275
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• 2010

The performance of Genetic Algorithms (GA) is affected by various factors such as parameters, genetic operators and strategies. The traditional approach with random initial population is efficient however the whole initial population may contain many infeasible solutions. Thus it would take a long time for GA to produce a good solution. The GA have been modified in various ways to achieve faster convergence and it was particularly recognized by researchers that initial population greatly affects the performance of GA. This study proposes modified GA with sorted initial population and applies it to solving Travelling Salesman Problem (TSP). Normally, the bigger the initial the population is the more computationally expensive the calculation becomes with each generation. New approach allows reducing the size of the initial problem and thus achieve faster convergence. The proposed approach is tested on a simulator built using object-oriented approach and the test results prove the validity of the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.214-216
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• 2000

본 논문에서는 유전자 프로그래밍을 이용하여 온라인 적응 학습이 가능 진화 하드웨어의 진화 전략을 구성하였다. 유전자 프로그래밍은 특유의 트리형 개체구조가 여러 개의 프로세스의 합을 통한 복합 임무의 수행 구조로 해석될 수 있다는 이점에 비하여, 하드웨어 구현이 어렵고 crossover 연산자의 사용이 어렵다는 단점등에 의하여 진화 하드웨어의 동적 재구성 알고리즘으로 널리 사용되지 못하였다. 본 논문에서는 유전자 프로그래밍의 이러한 단점을 극복할 수 있는 개체 표현 및 하드웨어 구현 방법을 제안하였으며, 제안된 방법론에 기존의 연구 결과를 결합하여 유전자 프로그래밍의 수행 효율을 높일 수 있는 진화 전략을 구성하였다. 제안된 진화 전략은 자율 이동 로봇 실험에 적용되어 효율성을 확인하였다.

• Journal of the Korea Computer Graphics Society
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• v.15 no.4
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• pp.13-21
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• 2009

Game level design is one of the important parts in the commercial game development. Because of its complexity in combining game components, game design work could be classified into a non-linear problem. In this paper, we propose a new automated game level design system by using genetic algorithms. With our system, a game designer easily generates an optimized game level by designating the key parameters m the initial stage of game design. Our system can be useful in reducing the trial-errors in the initial game level design process.

• Composites Research
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• v.21 no.1
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• pp.1-7
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• 2008

Composite vessels for high pressure gas storage are commonly used these days because of their competitive weight reduction ability maintaining strong mechanical properties. To supplement permeability of composite under high pressure, it is usually lined by metal, which is called a Type 3 vessel. However, it has many difficulties to design the Type 3 vessel because of its complex geometry, fabrication process variables, etc. In this study, therefore, GUI (graphic user interface) optimal design code for Type 3 vessels was developed based on semi-geodesic algorithm in which various factors of geometry and fabrication variables are considered and genetic algorithm for optimization. In addition, hydrogen vessels for 350/700 bar that can be applied to FCVs(fuel cell vehicles) were designed using this code for verification.

• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.5
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• pp.93-102
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• 2003

An optimal design method for hybrid structural control system of building structures subject to earthquake excitation is presented in this paper. Designing a hybrid structural control system may be defined as a process that optimizes the capacities and configuration of passive and active control systems as well as structural members. The optimal design proceeds by formulating the optimization problem via a multi-stage goal programming technique and, then, by finding reasonable solution to the optimization problem by means of a goal-updating genetic algorithm. In the multi-stage goal programming, design targets(or goals) are at first selected too correspond too several stages and the objective function is th n defined as the sum of the normalized distances between these design goals and each of the physical values, that is, the inter-story drifts and the capacities of the control system. Finally, the goal-updating genetic algorithm searches for optimal solutions satisfying each stage of design goals and, if a solution exists, the levels of design goals are consecutively updated to approach the global optimal solution closest too the higher level of desired goals. The process of the integrated optimization design is illustrated by a numerical simulation of a nine-story building structure subject to earthquake excitation. The effectiveness of the proposed method is demonstrated by comparing the optimally designed results with those of a hybrid structural control system where structural members, passive and active control systems are uniformly distributed.

• Composites Research
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• v.35 no.1
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• pp.31-37
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• 2022

In this study, an optimal structural design framework has been developed for the structural design of composite helicopter blades. The optimal design framework is constructed using PSGA (Particle Swarm assisted Genetic Algorithm), which combines the genetic algorithm and particle swarm optimizer. The optimization process consists of a finite element (FE) modeling over the blade section, two-dimensional (2D) cross-sectional FE analysis, and 1D rotating blade analysis. In the design process, the geometric curves and surfaces are formed using the B-spline scheme while discretizing the sections via a FE mesh generation program Gmsh. The blade cross-sections are created in accordance with the design variables when performing the blade structural analysis. The proposed optimization design framework is applied to a modernization of the HART II (Higher-harmonic Aeroacoustics Rotor Test II) blades. It is demonstrated that an improved blade design is reached through the current optimization framework with the satisfaction of all design requirements set for the study.