• Journal of Korean Society of Water and Wastewater
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• v.32 no.2
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• pp.115-122
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• 2018

Direct spring loaded pressure relief valve(DSLPRV) is a safety valve to relax surge pressure of the pipeline system. DSLPRV is one of widely used safety valves for its simplicity and efficiency. However, instability of the DSLPRV can caused by various reasons such as insufficient valve volume, natural vibration of the spring, etc. In order to improve reliability of DSLPRV, proper selection of design factors of DSLPRV is important. In this study, methodology for selecting design factors for DSLPRV was proposed. Dynamics of the DSLPRV disk was integrated into conventional 1D surge pressure analysis. Multi-objective genetic algorithm was also used to search optimum design factors for DSLPRV.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.1
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• pp.69-78
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• 2011

In this study, an optimization method using multi-objective genetic algorithm(MOGA) has been proposed to develop a fuzzy control algorithm that can effectively control a smart tuned mass damper(TMD). A 76-story benchmark building subjected to wind load was selected as an example structure. The smart TMD consists of 100kN MR damper and the natural period of the smart TMD was tuned to the first mode natural period of the example structure. Damping force of MR damper is controlled to reduce the wind-induced responses of the example structure by a fuzzy logic controller. Two input variables of the fuzzy logic controller are the acceleration of 75th floor and the displacement of the smart TMD and the output variable is the command voltage sent to MR damper. Multi-objective genetic algorithm(NSGA-II) was used for optimization of the fuzzy logic controller and the acceleration of 75th story and the displacement of the smart TMD were used as objective function. After optimization, a series of fuzzy logic controllers which could appropriately reduce both wind responses of the building and smart TMD were obtained. Based on numerical results, it has been shown that the control performance of the smart TMD is much better than that of the passive TMD and it is even better than that of the sample active TMD in some cases.

• Journal of Ocean Engineering and Technology
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• v.11 no.4
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• pp.227-238
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• 1997

다목적함수 최적화를 효과적으로 수행하기 위하여 유전자 알고리즘과 직접탐색법을 결합하여 혼성형 최적화기법을 구현하였다. 이 방법은 유전자 알고리즘을 사용하여 최적점이 존재할 가능성이 높은 영역을 탐색한 후, 이 영역에서 직접탐색법을 사용하여 최종해를 찾는다. 따라서 탐색의 효율을 향상시키고 계산시간을 절약할 수 있는 장점이 있다. 그러나 최적화기법이 효율적이지만, 최적화기법을 사용하기 위해서는 전문가의 전문지식이 필요하다. 따라서 실제 최적화를 수행하기 위해서는 관련 분야의 전문지식과 최적화기법이 효율적으로 결합되는 것이 필요하다.

• Journal of Korean Association for Spatial Structures
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• v.10 no.4
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• pp.93-102
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• 2010

In this study, a smart sky-bridge composed of MR damper and FPS has been proposed and vibration control performance of a smart sky-bridge for the connected buildings was investigated. To this end, 10-story and 20-story building structures connected by a smart sky-bridge were selected as example structures and El Centro and Kobe earthquakes, which have near and far fault ground motion characteristics respectively, were used for time history analyses. In order to effectively control the smart sky-bridge, fuzzy logic controller was developed and multi-objective genetic algorithm was used to optimize fuzzy logic controllers. Based on optimization results, it has been seen that there is a trade-off between seismic responses of 10-story and 20-story buildings and a suite of Pareto optimal solutions of fuzzy logic controllers for seismic response control can be obtained by multi-objective genetic algorithm. It is shown from numerical study that seismic responses of adjacent buildings can be efficiently controlled by using a smart sky-bridge.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.677-685
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• 2007

The objective of this study is to evaluate the applicability of multi-objective genetic algorithm(MOGA) in order to calibrate the parameters of conceptual rainfall-runoff model, Tank model. NSGA-II, one of the most imitating MOGA implementations, is combined with Tank model and four multi-objective functions such as to minimize volume error, root mean square error (RMSE), high flow RMSE, and low flow RMSE are used. When NSGA-II is employed with more than three multi-objective functions, a number of Pareto-optimal solutions usually becomes too large. Therefore, selecting several preferred Pareto-optimal solutions is essential for stakeholder, and preference-ordering approach is used in this study for the sake of getting the best preferred Pareto-optimal solutions. Sensitivity analysis is performed to examine the effect of initial genetic parameters, which are generation number and Population size, to the performance of NSGA-II for searching the proper paramters for Tank model, and the result suggests that the generation number is 900 and the population size is 1000 for this study.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.5
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• pp.243-250
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• 2018

In this paper, design technique using genetic algorithms(GA) for design optimization of composite leaf springs is presented here. After the initial design has been validated by the car plate spring as a finite element model, the genetic algorithm suggests the process of optimizing the number of layers of composite materials and their angles. Through optimization process, the weight reduction process of leaf springs and the number of repetitions are compared to the existing algorithm results. The safety margin is calculated by organizing a finite element model to verify the integrity of the structure by applying an additive sequence optimized through the genetic algorithm to the structure. When GA is applied, layer thickness and layer angle of complex leaf springs have been obtained, which contributes to the achievement of minimum weight with appropriate strength and stiffness. A reduction of 65.6% original weight is reached when a leaf steel spring is replaced with a leaf composite spring under identical requirement of design parameters and optimization.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.84-92
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• 2007

Dynamic process planning requires not only more flexible capabilities of a CAPP system but also higher utility of the generated process plans. In order to meet the requirements, this paper develops an algorithm that can select machines for the machining operations by calculating the machine loads. The developed algorithm is based on the multi-objective genetic algorithm that gives rise to a set of optimal solutions (in general, known as the Pareto-optimal solutions). The objective is to satisfy both the minimization number of part movements and the maximization of machine utilization. The algorithm is characterized by a new and efficient method for nondominated sorting through K-means algorithm, which can speed up the running time, as well as a method of two stages for genetic operations, which can maintain a diverse set of solutions. The performance of the algorithm is evaluated by comparing with another multiple objective genetic algorithm, called NSGA-II and branch and bound algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.219-224
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• 2016

The vibration control performance of a semi-active damper connected to adjacent buildings subjected to seismic loads was investigated. The MR damper was used as a semi-active control device. A fuzzy logic control algorithm was used for effective control of the adjacent buildings connected to the MR damper. In the buildings control coupled with a MR damper, the response reduction of one building results in an increase in the response in another building. Because of these conflict characteristics, multi-objective optimization is required. Therefore, a fuzzy logic control algorithm for the control of a MR damper was optimized using a multi-objective genetic algorithm. Based on numerical analyses, the semi-active fuzzy control of MR damper for adjacent coupled buildings can provide good control performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.637-637
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• 2012

본 연구에서는 내수침수 저감을 위하여 효율적(effective)인 우수저류조 설치에 따른 침수저감효과 극대화 방안을 제시하고자 한다. 여기서 효율성(effectiveness)은 침수저감량의 극대화 측면과 비용의 최소화 측면 두 가지로 구분된다. 최적 방재 시설물의 설치는 단순 설치비용 대비 저감량이 가장 큰 안을 제시하는 것은 의미가 없으며 일정 기준 이상의 방재성능을 발휘하면서 주어진 예산안에서 최적안을 찾아야 하므로 비용의 최소화 측면과 침수 저감량, 즉 맨홀에서의 월류 저감량을 최대화 하는 두 가지의 목적을 동시에 달성해야 한다. 따라서 본 연구에서는 다목적 최적화 알고리즘의 적용을 통하여 우수저류조 최적 설치지점을 선정하는 기법을 제안하였다. 본 연구에 적용한 다목적 최적화 방법으로는 목적함수의 최적해 탐색 효용성 측면에서 우수하다고 평가되고 있는 유전자 알고리즘을 적용하였다. 다목적 최적화의 경우 해의 우열을 판단하기 위한 적합도 함수는 실제 각 목적함수의 적합도 값(real fitness value)이 아닌 해의 상대적인 우열(dominance or non-dominance)에 따라 부여되는 등급(rank)에 의해서 해의 우열이 결정되며 여기서는 Fonseca and Fleming(1993)이 제안한 Ranking method를 적용하여 적합도를 결정하였다. 한편 도시 우수관망의 해석 및 우수저류조 설치에 따른 월류량 분석을 위하여 미 환경청(US Environmental Protection Agency; EPA)에서 제공하고 있는 EPA-SWMM 5.0 engine을 사용하였으며 최적화 알고리즘의 구성을 위하여 Visual C++와 SWMM DLL을 연동하여 사용하였다. 연구 대상유역은 인천 청라지구(3공구)를 대상으로 기법의 적용성을 검토하였으며 저류지 설치에 따른 비용함수는 EPA(2002)에서 제안한 저류지 체적대비 공사비용을 원화로 환산한 후 청라지구의 공시지가를 고려하여 결정하였다. 최적화 기법의 적용 결과 저류지 설치비용에 따라 최대로 월류량을 저감시킬 수 있는 우수저류조 최적 설치위치의 조합(Pareto-front)을 결정할 수 있었다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.