• Bulletin of the Society of Naval Architects of Korea
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• v.31 no.2
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• pp.25-27
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• 1994

최적설계에 대한 두번의 특집을 통해 최적설계, 다목적함수, 민감도 해석, 재설계, 지식기반시스템, 유전적 알고리듬, 신경회로망 등 새로운 방법들이 많이 소개되었다. 이들을 이론적인 배경에 의해 분류하면, 최적화 이론과 인공지능의 두 가지로 크게 나누어 볼 수 있다. 하지만 한편으로는 이들을 '어떻게 하면 더 나은 설계를 할 수 있는가\ulcorner'하는 한가지 목표를 달성하기 위해 제안되고 있는 여러가지 도구들로도 이해될 수 있다. 이글에서는 이 다양한 방법들에 대한 관련성을 설계 방법론이라는 관점에서 설명을 시도하고자 한다.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.9
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• pp.557-567
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• 2016

In this study, the optimal design of heat exchangers, including the evaporator and condenser of a solar-heating ocean thermal energy conversion (SH-OTEC), is investigated. The power output of the SH-OTEC is assumed to be 100 kW, and the SH-OTEC uses the working fluid of R134a and high-performance commercial tubes. The surface heat transfer area and the pressure drop were strongly dependent on the number of tubes, as well as the number of tube passes. To solve the reciprocal tendency between the heat transfer area and pressure drop with respect to the number of tubes, as well as the number of tube passes, a genetic algorithm (GA) with two objective functions of the heat transfer area (the capital cost) and operating cost (pressure drop) was used. Optimal results delineated the feasible regions of heat transfer area and operating cost with respect to the pertinent number of tubes and tube passes. Pareto fronts of the evaporator and condenser obtained from multi-objective GA provides designers or investors with a wide range of optimal solutions so that they can select projects suitable for their financial resources. In addition, the surface heat transfer area of the condenser took up a much higher percentage of the total heat transfer area of the SH-OTEC than that of the evaporator.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.433-441
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• 2011

The optimization of a centrifugal compressor was conducted. The ANN (Artificial Neural Network) was adopted as an optimization algorithm, and it was learned and trained with the DOE (Design of Experiment). In the DOE, it was predicted the main effect and the interaction effect of design variables to the objective function. The ANN was improved in the optimization process using the GA (Genetic Algorithm). When any output at each generation was reached a standard level, it was re-calculated by the CFD (Computational Fluid Dynamics) and it was applied to develop a new ANN. After 6th generation, the prediction difference between ANN and CFD was less than 1%. A pareto of the efficiency versus the pressure ratio was obtained through the 21th generation. Using this method, the computational time for the optimization was equivalent to the time consumed by the gradient method, and the optimized results of multi-objective function were obtained.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.641-645
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• 2002

저소음 팬의 설계는 팬 성능의 저감 없이 이루어져야 한다. 따라서 저소음 팬 설계는 기본적으로 다분야간 설계 최적화 또는 다목적 설계 최적화의 문제이다. 본 연구에서는 이러한 요구를 수행하기 위해 반응면 기법을 저소음 축류 팬 설계에 적용하여 보았다. 또한 이러한 설계 단계에서 필요한 수백가지 시험 결과를 효과적으로 구하기 위해 효율적인 유동 해석 툴과 소음 해석 툴을 개발하여 적용시켰다. 마지막으로 이렇게 설계된 팬을 실제 크기로 제작 측정 비교 분석하여 적용된 기법을 검증하며 문제점에 대해 고찰해 보았다.

• The KSFM Journal of Fluid Machinery
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• v.17 no.4
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• pp.19-29
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• 2014

In addition to the development of micro hydro turbine, the challenge in micro hydro turbine design as sustainable hydro devices is focused on the optimization of turbine runner blade which have decisive effect on the turbine performance to reach higher efficiency. A multi-objective optimization method to optimize the performance of runner blade of propeller turbine for micro turbine has been studied. For the initial design of planar blade cascade, singularity distribution method and the combination of the Bezier curve parametric technology is used. A non-dominated sorting genetic algorithm II(NSGA II) is developed based on the multi-objective optimization design method. The comparision with model test show that the blade charachteristics is optimized by NSGA-II has a good efficiency and load distribution. From model test and scale up calculation, the maximum prototype efficiency of the runner blade reaches as high as 90.87%.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.463-464
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• 2007

본 논문은 경제성 및 안정성을 유지하는 최적의 전압유지범위 설정을 위해 다양한 목적함수를 최적조류계산에 이용하였다. 경제성을 위해 융통전력 최대화와 유효전력 손실최소화를 목적함수로 하였고 안정성을 위해 무효전력예비력 최대화를 목적함수로 하였다. 또한 경제성과 안정성을 모두 반영하기 위해 다목적 함수를 구성하였다. 최적화기법을 실계통에 적용하였을 때 목적함수를 얼마나 잘 만족시킬 수 있는지 각종 지표를 통해 살펴보았다. 그리고 모니터링 모선의 전압 변동 추이를 살펴보고 이를 통해 경제성 및 안정성을 유지하는 최적의 전압유지 범위설정을 하는데 활용할 수 있도록 하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.425-425
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• 2023

상수도시스템의 지속가능한 운영을 위해서는 에너지를 효율적으로 활용하는 것이 필수적이다. 따라서, 본 연구에서는 상수도시스템에서 고압구간의 압력조절을 통해 에너지 측면의 최적 운영기법을 제안하였다. 제안된 최적 운영기법은 마이크로 터빈을 이용하여 에너지 회수를 통한 압력저하와 이로 인한 누수량 저감을 동시에 고려하였다. 본 연구에서 사용한 최적화기법으로는 Multi-objective harmony search 알고리즘을 사용하였으며, 상수도 시스템에서 마이크로 터빈을 모의하기 위해서 EPANET의 압력조절 밸브 (Pressure reduction valve)를 활용하여 압력강하에 따른 에너지 회수를 고려하였다. 제안된 최적운영 기법을 검증하기 위해 Benchmark networks (e.g., 5-nodes network, 25-nodes network)을 적용하였으며, 본 연구를 통해 마이크로 터빈의 최적 규모와 설치위치, 개수를 결정할 수 있으며, 이에 따른 에너지 회수와 누수감소 측면에서 상수도시스템의 지속가능한 운영에 효과적으로 이용될 수 있을 거라 기대된다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.12
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• pp.1793-1803
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• 2010

The weighting method and goal programming require weighting factors or target values to obtain a Pareto optimal solution. However, it is difficult to define these parameters, and a Pareto solution is not guaranteed when the choice of the parameters is incorrect. Recently, the Mahalanobis Taguchi System (MTS) has been introduced to minimize the Mahalanobis distance (MD). However, the MTS method cannot obtain a Pareto optimal solution. We propose a function called the skewed Mahalanobis distance (SMD) to obtain a Pareto optimal solution while retaining the advantages of the MD. The SMD is a new distance scale that multiplies the skewed value of a design point by the MD. The weighting factors are automatically reflected when the SMD is calculated. The SMD always gives a unique Pareto optimal solution. To verify the efficiency of the SMD, we present two numerical examples and show that the SMD can obtain a unique Pareto optimal solution without any additional information.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.217-225
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• 2009

Tone injection scheme has been known as one of peak to average power ratio (PAPR) reduction methods deployable to multi-carrier system like orthogonal frequency division multiplexing (OFDM). The basic idea in tone injection scheme is to enforce the constellation size larger so that each of original constellation points is mapped into the preassigned distinct locations. According to the tone injection scheme, it increases symbol power highly induced inherently by expanding constellation to get optimal PAPR reduction. In the other hand, to get optimal power increase, the PAPR would be reduced insufficiently with limited tone injection signal. To withstand these problems, this paper consider the reduction of the PAPR and power increase problem simultaneously, Toward this, the tone injection scheme accomplished by employing the weighted sum genetic algorithm which has been utilized to solve multi-objective optimization problem (MOOP). The simulation results verifies that the proposed scheme can control the effective PAPR performance and alleviation of power increase flexibly by the weight value at the expense of relatively low complexity.

• Journal of Navigation and Port Research
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• v.35 no.6
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• pp.501-507
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• 2011

This paper focuses on dispatching strategy for AGVs(Automated Guided Vehicle). The goal of AGV dispatching is assigning AGVs to requested job to minimizing the delay of QCs and the travel distance of AGVs. Due to the high dynamic nature of container terminal environment, the effect of dispatching is hard to predict thus it leads to frequent modification of dispatching decisions. In this situation, approaches based on a single rule are widely used due to its simplicity and small computational cost. However, these approaches have a limitation that cannot guarantee a satisfactory performance for the various performance measures. In this paper, dispatching strategy based on multicriteria heuristics is proposed. The Proposed strategy consists of multiple decision criteria. A multi-objective evolutionary algorithm is applied to optimize weights of those criteria. The result of simulation experiment shows that the proposed approach outperforms single rule-based dispatching approaches.