• 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 KIISE:Information Networking
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• v.37 no.6
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• pp.453-458
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• 2010

In the paper, we propose an energy efficient sensor network management scheme. In the proposed scheme, the modified game theory and ${\varepsilon}$-constraint techniques are sophisticatedly combined to establish energy efficient routing paths. Simulation results indicate that the proposed scheme can strike an appropriate performance balance between conflicting requirements while other existing schemes cannot offer such an attractive performance.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.3
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• pp.99-105
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• 2000

For multi-body dynamic problems. especially coalescent eigenvalue problems with multiobjective optimization, the design sensitivity analysis is too much complicated mathematically and numerically. Therefore, this article proposes a new technique for structural dynamic modification using a mode modification and homologous structures design method with Genetic Algorithm(GA). In this work, the homologous structure of the resiliently mounted multi-body for marine diesel generator systems is studied and the problem is treated as a combinational optimization problem using the GA. In GA formulation, fitness is defined based on penalty function approach. That include homology, allowable stress and minimum weight of common plate.

• Proceedings of the Korea Society for Simulation Conference
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• 2002.11a
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• pp.3-7
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• 2002

컴퓨터 네트워킹 기술의 발달에 힘입어 분산처리를 이용한 기법이 복잡한 구조물의 최적설계에 널리 사용되고 있다. 최적설계시 구조물이 복잡하고 설계 변수가 많아질수록 설계 변수간의 교호작용이 복잡해지고 국부최적해가 많아지는 특성이 있다. 최근의 최적 설계는 이러한 문제점을 해결하고자 다양한 전역 최적화 기법을 도입하여 적용하고 있다. 본 연구에서는 진화이론을 바탕으로 한 유전자 알고리즘과 실험계획법을 바탕으로 한 반응표면법에 분산처리 기법을 도입하여 인공위성 추진 모듈의 최적화에 적용시켰다. 그 결과 유전자 알고리즘이 조금 더 좋은 최적값을 보였으며 해석시간은 반응표면법을 적용 시켰을 경우가 훨씬 짧았다. 병렬처리 기법을 이용한 위성구조체의 최적설계에 있어 유전자 알고리즘은 해의 전역성에서 반응표면법은 시간의 효율성에서 각각 장점을 보였다.

• Journal of the Korea Society for Simulation
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• v.16 no.2
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• pp.45-54
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• 2007

In this article, we propose a different modeling approach, which aims at the simulation optimization so as to meet the design specification. Generally, Multi objective optimization problem is formulated by dependent factors as objective functions and independent factors as constraints. However, this paper presents the critical(dependent) factors as objective function and design(independent) factors as constraints for the selection of design factors directly. The objective function is normalized far the generalization of design factors while the constraints are composed of the simulation-based regression metamodels fer the critical factors and design factor's domain. Then the effective and fast solution procedure based on the pareto optimal solution set is proposed. This paper provides a comprehensive framework for the system design using the simulation and metamodels. Therefore, the method developed for this research can be adopted for other enhancements in different but comparable situations.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.5
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• pp.435-441
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• 2015

In this study, a method for optimal design of impeller and diffuser blades in the centrifugal compressor using response surface method (RSM) and multi-objective genetic algorithm (MOGA) was evaluated. A numerical simulation was conducted using ANSYS CFX with various values of impeller and diffuser parameters, which consist of leading edge (LE) angle, trailing edge (TE) angle, and blade thickness. Each of the parameters was divided into three levels. A total of 45 design points were planned using central composite design (CCD), which is one of the design of experiment (DOE) techniques. Response surfaces that were generated on the basis of the results of DOE were used to determine the optimal shape of impeller and diffuser blade. The entire process of optimization was conducted using ANSYS Design Xplorer (DX). Through the optimization, isentropic efficiency and pressure recovery coefficient, which are the main performance parameters of the centrifugal compressor, were increased by 0.3 and 5, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.17-34
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• 2022

This paper develops a model for dynamic station assignment to optimize the Demand Responsive Transit (DRT) operation. In the process of optimization, we use the bus travel time as a variable for DRT management. In addition, walking time, waiting time, and delay due to detour to take other passengers (detour time) are added as optimization variables and entered for each DRT passenger. Based on a network around Anaheim, California, reserved origins and destinations of passengers are assigned to each demand responsive bus, using K-means clustering. We create a model for selecting the dynamic station and bus route and use Non-dominated Sorting Genetic Algorithm-III to analyze seven scenarios composed combination of the variables. The result of the study concluded that if the DRT operation is optimized for the DRT management, then the bus travel time and waiting time should be considered in the optimization. Moreover, it was concluded that the bus travel time, walking time, and detour time are required for the passenger.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.893-904
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• 2013

In this paper, a Kriging metamodel-based multi-objective optimization strategy in conjunction with an NSGA-II(non-dominated sorted genetic algorithm-II) has been employed to optimize the valve-plate shape of the axial piston pump utilizing 3D CFD simulations. The optimization process for minimum pressure ripple and maximum pump efficiency is composed of two steps; (1) CFD simulation of the piston pump operation with various combination of six parameters selected based on the optimization principle, and (2) applying a multi-objective optimization approach based on the NSGA-II using the CFD data set to evaluate the Pareto front. Our exploration shows that we can choose an optimal trade-off solution combination to reach a target efficiency of the axial piston pump with minimum pressure ripple.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2017.11a
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• pp.124-127
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• 2017

선박에서 배출되는 환경오염 물질 및 온실가스에 대한 규제가 강화됨에 따라, 환경오염 물질 및 온실가스의 배출과 직접적으로 관련있는 연료 소모량을 줄이려는 다양한 연구가 진행되고 있다. 연료 소모량을 줄이기 위한 방안 중 하나는 환경 및 기상 예보를 이용하여 연료가 가장 적게 소모되는 항로를 찾는 것이다. 기존 연구에서는 연료 소모량을 주된 목적함수로 최소화 하되, 도착 시간에 대한 조건을 평가하기 위해 도착 시간의 기댓값을 계산하고 추가적인 목적함수로 고려하는 경우가 많았다. 그러나 선박 운항 예측 시 적용되는 환경 외란 정보는 상당한 불확실성을 포함하고, 이로 인해 발생하는 운항 속도 및 도착 시간에 대한 불확실성도 상당히 클 수 있기 때문에, 도착 시간의 기댓값뿐만 아니라 도착 시간에 대한 불확실성을 기반으로 제한 시간 내에 선박이 도착할 확률을 정량적으로 평가하는 것이 필요하다. 본 연구에서는 다목적 최적화 기법을 이용해 도착 시간의 기댓값과 연료 소모량에 대한 Pareto set을 구하되, 환경 외란으로부터 발생하는 도착 시간의 불확실성을 계산하여, 제한 시간 내에 선박이 도착할 확률을 계산하고 이를 항로 최적화 시 적용한다. 제안하는 방법의 유용성을 검증하기 위해 실제 환경에 가까운 맵을 기반으로 부산-도쿄 간의 항로를 최적화하고, 그 결과에 대해 논의한다.

• Computational Structural Engineering
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• v.8 no.2
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• pp.123-132
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• 1995

Genetic Algorithms(GA), which are based on the theory of natural evolution, have been evaluated highly for their robust performances. Traditional GA has mostly used binary code for representing design variable. The binary code GA has many difficulties to solve optimization problems with continuous design variables because of its large computer core memory size, inefficiency of its computing time, and its bad performance on local search. In this paper, a real code GA is proposed for dealing with the above problems. So, new crossover and mutation processes of GA are developed to use continuous design variables directly. The results of read code GA are compared with those of binary code GA for several single and multiple objective optimization problems. As a result of comparisons, it is found that the performance of the real code GA is better than that of the binary code GA, and concluded that the real code GA developed here can be used for the general optimization problem.