• Smart Structures and Systems
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• 제21권5호
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• pp.669-675
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• 2018

Under braking forces of a freight train, there are great longitudinal structural responses of a large freight railway cable-stayed bridge. To alleviate such adverse reactions, viscous dampers are required, whose parametric selection is one of important and arduous researches. Based on the longitudinal dynamics vehicle model, responses of a cable-stayed bridge are investigated under various cases. It shows that there is a notable effect of initial braking speeds and locations of a freight train on the structural responses. Under the most unfavorable braking condition, the parameter sensitivity analyses of viscous dampers are systematically performed. Meanwhile, a mixing method called BPNN-NSGA-II, combining the Back Propagation neural network (BPNN) and Non-Dominated Sorting Genetic Algorithm With Elitist Strategy (NSGA-II), is employed to optimize parameters of viscous dampers. The result shows that: 1. the relationships between the parameters of viscous dampers and the key longitudinal responses of the bridge are high nonlinear, which are completely different from each other; 2. the longitudinal displacement of the bridge main girder significantly decreases by the optimized viscous dampers.

• Earthquakes and Structures
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• 제11권2호
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• pp.347-369
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• 2016

The main objective of this paper is the robust multi-objective optimization design of semi-active tuned mass damper (STMD) system using genetic algorithms and fuzzy logic. For optimal design of this system, it is required that the uncertainties which may exist in the system be taken into account. This consideration is performed through the robust design optimization (RDO) procedure. To evaluate the optimal values of the design parameters, three non-commensurable objective functions namely: normalized values of the maximum displacement, velocity, and acceleration of each story level are considered to minimize simultaneously. For this purpose, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solutions. The torsional effects due to irregularities of the building and/or unsymmetrical placements of the dampers are taken into account through the 3-D modeling of the building. Finally, the comparison of the results shows that the probabilistic robust STMD system is capable of providing a reduction of about 52%, 42.5%, and 37.24% on the maximum displacement, velocity, and acceleration of the building top story, respectively.

• 한국지능시스템학회논문지
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• 제24권1호
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• pp.46-51
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• 2014

공학적 시스템 최적설계의 가장 중요한 과정은 설계변수와 시스템 응답과의 관계를 파악하는 것이다. 시스템 최적화의 경우 반응표면법이 주로 사용되고 있다. 반응표면법의 최적화 과정은 대표적인 후보대안을 이용하여 설계공간을 구성하고, 설정된 설계 공간에서 설계 최적점을 찾는다. 설계공간의 구성에 따라 최적점이 변화되므로 합리적인 최적점을 찾기 위해서는 설계공간의 구성이 매우 중요하다. 따라서 본 연구에서는 설계변수와 시스템응답의 관계를 신경반응표면을 이용하여 설계공간을 구성하고, 구성된 설계 공간 안에서 다목적유전자 알고리즘을 이용하여 최적 형상을 예측 할 수 있는 '신경반응표면을 이용한 공학 구조물 설계 프레임워크 구축'을 시도하였다. 구축된 프레임워크의 유용성을 확인하기 위해 비선형 수학함수 문제를 적용하였다. 구축된 프레임워크를 통해 공학문제의 최적화 과정에서 시간의 제약을 해결하고, 효과적인 최적설계가 가능함을 확인할 수 있었다. 향후에는 본 연구의 결과를 바탕으로 실제 조선해양공학 최적화 문제에 적용을 시도할 것이다.

• 한국전산구조공학회논문집
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• 제29권6호
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• pp.555-562
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• 2016

본 논문에서는 Nondominated sorting genetic algorithm-II(NSGA-II)를 이용한 Zipper를 가진 역V형 중심가새골조의 다목적 최적내진설계기법을 제시한다. 부재의 단면성능을 설계변수로 사용하는 제시된 최적화기법은 내진설계를 위해 부재의 강도조건, 구조물의 층간변위조건, 부재의 변형조건 등을 만족시키면서 구조물의 물량과 구조물의 최대 층간변위율을 동시에 최소화하는 문제로 정식화된다. 구조물의 물량과 최대 층간변위율을 최소화하는 이유는 구조물의 비용과 성능을 각각 최적화하기 위해서 이다. 선형 정적해석을 통해 구조물의 강도 및 층간변위 제약 조건을 검토하며, 비선형 정적해석을 통해 구조물의 변형 조건 및 내진성능을 평가한다. 제안된 기법을 검증하기 위해 3층과 6층 Zipper를 가진 역V형 중심가새골조 예제를 사용한다. 이를 통해 얻은 설계안을 초기 설계안과 비교분석하여 제안된 기법의 적용성을 확인한다.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2125-2138
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• 2023

The printed circuit heat exchanger (PCHE) with airfoil fins has the benefits of high compactness, high efficiency and superior heat transfer performance. A novel multi-objective optimization approach is presented to design the airfoil fin PCHE in this paper. Three optimization design variables (the vertical number, the horizontal number and the staggered number) are obtained by means of dimensionless airfoil fin arrangement parameters. And the optimization objective is to maximize the Nusselt number (Nu) and minimize the Fanning friction factor (f). Firstly, in order to investigate the impact of design variables on the thermal-hydraulic performance, a parametric study via the design of experiments is proposed. Subsequently, the relationships between three optimization design variables and two objective functions (Nu and f) are characterized by an improved particle swarm optimization-backpropagation artificial neural network. Finally, a multi-objective optimization is used to construct the Pareto optimal front, in which the non-dominated sorting genetic algorithm II is used. The comprehensive performance is found to be the best when the airfoil fins are completely staggered arrangement. And the best compromise solution based on the TOPSIS method is identified as the optimal solution, which can achieve the requirement of high heat transfer performance and low flow resistance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1260-1283
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• 2019

Low earth orbit (LEO) satellite broadband network is a crucial part of the space information network. LEO satellite constellation design is a top-level design, which plays a decisive role in the overall performance of the LEO satellite network. However, the existing works on constellation design mainly focus on the coverage criterion and rarely take network performance into the design process. In this article, we develop a unified framework for constellation optimization design in LEO satellite broadband networks. Several design criteria including network performance and coverage capability are combined into the design process. Firstly, the quality of service (QoS) metrics is presented to evaluate the performance of the LEO satellite broadband network. Also, we propose a network stability model for the rapid change of the satellite network topology. Besides, a mathematical model of constellation optimization design is formulated by considering the network cost-efficiency and stability. Then, an optimization algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) is provided for the problem of constellation design. Finally, the proposed method is further evaluated through numerical simulations. Simulation results validate the proposed method and show that it is an efficient and effective approach for solving the problem of constellation design in LEO satellite broadband networks.

• 한국전산구조공학회논문집
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• 제29권3호
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• pp.253-260
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• 2016

본 연구에서는 철골모멘트골조의 보-힌지 붕괴모드를 유도하는 최적 내진설계기법을 제안한다. 이는 유전자알고리즘을 사용하며, 기둥의 소성힌지 발생을 억제하는 제약조건을 설정하여 보-힌지 붕괴모드를 유도한다. 제안하는 기법은 구조물량를 최소화하고 에너지소산능력을 최대화하는 목적함수를 사용한다. 제안하는 기법은 9층 철골모멘트골조 예제 적용을 통해 검증한다. 예제 적용을 통해 철골모멘트골조의 보-힌지 붕괴모드를 유도하기 위해 요구되는 기둥-보 강도비를 평가한다. 패널존에 대한 3가지 모델링 기법을 각각 적용하여 모델링 조건에 따른 휨강도비 영향이 추가적으로 검토된다.

• Journal of Computational Design and Engineering
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• 제1권4호
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• pp.256-265
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• 2014

Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using non-dominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

• International Journal of Naval Architecture and Ocean Engineering
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• 제10권6호
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• pp.661-669
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• 2018

Engineering system problems consist of multi-objective optimisation and the performance analysis is generally time consuming. To optimise the system concerning its performance, many researchers perform the optimisation using an approximation model. The Response Surface Method (RSM) is usually used to predict the system performance in many research fields, but it shows prediction errors for highly nonlinear problems. To create an appropriate metamodel for marine systems, Lee (2015) compares the prediction accuracy of the approximation model, and multi-objective optimal design framework is proposed based on a confirmed approximation model. The proposed framework is composed of three parts: definition of geometry, generation of approximation model, and optimisation. The major objective of this paper is to confirm the applicability/usability of the proposed optimal design framework and evaluate the prediction accuracy based on sensitivity analysis. We have evaluated the proposed framework applicability in derrick structure optimisation considering its structural performance.

• Structural Engineering and Mechanics
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• 제50권2호
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• pp.151-161
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• 2014

In this paper, fuel tank of the locomotive ER 24 has been studied. Firstly the behavior of fuel and air during the braking time has been investigated by using a two-phase model. Then, the distribution of pressure on the surface of baffles caused by sloshing has been extracted. Also, the fuel tank has been modeled and analyzed using Finite Element Method (FEM) considering loading conditions suggested by the DIN EN 12663 standard and real boundary conditions. In each loading condition, high stressed areas have been identified. By comparing the distribution of pressure caused by sloshing phenomena and suggested loading conditions, optimization of the tank has been taken into consideration. Moreover, internal baffles have been investigated and by modifying their geometric properties, search of the design space has been done to reach the optimal tank. Then, in order to reduce the mass and manufacturing cost of the fuel tank, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Artificial Neural Networks (ANNs) have been employed. It is shown that compared to the primary design, the optimized fuel tank not only provides the safety conditions, but also reduces mass and manufacturing cost by %39 and %73, respectively.