• International Journal of Naval Architecture and Ocean Engineering
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• 제9권1호
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• pp.11-24
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• 2017

The present work focuses multi-objective optimization of blade sweep for a Wells turbine. The blade-sweep parameters at the mid and the tip sections are selected as design variables. The peak-torque coefficient and the corresponding efficiency are the objective functions, which are maximized. The numerical analysis has been carried out by solving 3D RANS equations based on k-w SST turbulence model. Nine design points are selected within a design space and the simulations are run. Based on the computational results, surrogate-based weighted average models are constructed and the population based multi-objective evolutionary algorithm gave Pareto optimal solutions. The peak-torque coefficient and the corresponding efficiency are enhanced, and the results are analysed using CFD simulations. Two extreme designs in the Pareto solutions show that the peak-torque-coefficient is increased by 28.28% and the corresponding efficiency is decreased by 13.5%. A detailed flow analysis shows the separation phenomena change the turbine performance.

• 설비공학논문집
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• 제28권7호
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• pp.299-304
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• 2016

In recent years, heat source systems which have a principal effect on the performance of buildings are difficult to design optimally as a great number of design factors and constraints in large and complicated buildings need to be considered. On the other hand, it is necessary to design an optimum system combination and operation planning for energy efficiency considering Life Cycle Cost (LCC). This study suggests a multi-level and multi-objective optimization method to minimize both LCC and investment cost using a genetic algorithm targeting an office building which requires a large cooling load. The optimum method uses a two stage process to derive the system combination and the operation schedule by utilizing the input data of cooling and heating load profile and system performance characteristics calculated by dynamic energy simulation. The results were assessed by Pareto analysis and a number of Pareto optimal solutions were determined. Moreover, it was confirmed that the derived operation schedule was useful for operating the heat source systems efficiently against the building energy requirements. Consequently, the proposed optimization method is determined by a valid way if the design process is difficult to optimize.

• 한국전자통신학회논문지
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• 제2권4호
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• pp.199-202
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• 2007

본 논문에서는 UHF 대역(860~960 MHz의 수동 RFID 태그 안테나 제안하여 해석하였다. 제안한 안테나는 루프구조에 의한 UHF 대역 초소형 수동 RFID 태그 안테나이다. 제안한 안테나는 단일 평면 구조 형태로 인쇄 기판에 손쉽게 인쇄할 수 있어 생산비 절감을 통한 대량 생산이 용이하며, Pareto 유전자 알고리즘과 IE3D 시뮬레이션 툴로 최적화하여 안테나의 크기를 소형화 하였다. 최적화 한 RFID 태그 안테나의 성능을 검증하기 위하여 몇 개의 표본 안테나를 제작하고 반사 손실, 복사 효율, 복사 패턴 등을 측정하였다. 상용태그 와 고정형 리더 시스템을 이용하여 제작된 태그 안테나의 인식 거리를 측정하였고, 약 1~3 m의 인식거리를 가지는 것을 확인하였다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.2690-2695
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• 2007

This work presents numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis. Reynolds-averaged Navier-Stokes (RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

• International Journal of Air-Conditioning and Refrigeration
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• 제16권1호
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• pp.1-8
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• 2008

Numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm(NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis is presented in this work. Reynolds-averaged Navier-Stokes(RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.1069-1086
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• 2003

This article presents the asymptotic theory of triple sampling procedure as pertain to estimating the shape parameter of Pareto distribution. Both point and confidence interval estimation are considered within the same inference unified framework. We show that this group sampling technique possesses the efficiency of Anscome (1953), Chow and Robbins (1965) purely sequential procedure as well as reduce the number of sampling operations by utilizing Stein (1945) two stages procedure. The analysis reveals that the technique performs excellent as far as the accuracy is concerned. The present problem differs from those considered by many authors, in multistage sampling, in that the final stage sample size and the parameter's estimate become highly correlated and therefore we adopted different approach.

• Journal of Electrical Engineering and Technology
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• 제3권2호
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• pp.207-212
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• 2008

This paper presents a robust and computationally efficient optimal design algorithm for electromagnetic devices by combining an adaptive response surface approximation of the objective function and($1+{\lambda}$) evolution strategy. In the adaptive response surface approximation, the design space is successively reduced with the iteration, and Pareto-optimal sampling points are generated by using Latin hypercube design with the Max Distance and Min Distance criteria. The proposed algorithm is applied to an analytic example and TEAM problem 22, and its robustness and computational efficiency are investigated.

• 설비공학논문집
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• 제26권8호
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• pp.357-365
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• 2014

This paper proposed a multi-objective optimization method for building energy system design using primary energy consumption and initial cost. The designing of building energy systems is a complex task, because life cycle cost and efficiency of building are determined by decisions of engineer during the early stage of design. Therefore, methods such as pareto analysis that can generate various alternatives for decision making are necessary. In this study, the optimization is performed using the NSGAII and case study was carried out for feasibility of the proposed method. As a result, alternative solutions can be obtained for the optimal building energy system design.

• 한국통신학회논문지
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• 제35권7B호
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• pp.1034-1042
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• 2010

최근 녹색 IT(Green IT)에 대한 관심이 증가하면서 많은 연구자들이 적응적 전송률(Rate adaptation)을 이용한 에너지 효율적 이더넷(Energy Efficient Ethernet: EEE)에 관심을 보이고 있다. 그러나 적응적 전송률은 트래픽 패턴에 따라 다른 에너지 효율성 및 전송률 변화에 따른 지연 시간의 편차를 보일 수 있다. 따라서 본 논문에서는 적응적 전송률 기법을 이용한 이더넷에서 트래픽 패턴이 에너지 절약 및 지연 시간에 미치는 영향을 분석하였다. 이를 위하여 OPNET Modeler를 이용하여 다양한 트래픽 패턴 생성을 위한 포아송(Poisson) 프로세스 기반 및 파레토(Pareto) 분포 기반의 ON-OFF 트래픽 생성 모델과 적응적 전송률을 이용한 이더넷 노드를 구현하여 시뮬레이터를 설계하였다. 구현된 시뮬레이터를 이용하여 총 전송률 변화 횟수, 전송율 절감, 에너지 절약율, 평균 큐 지연 시간 관점에서 시뮬레이션을 수행하고 그 결과를 분석하였다. 시뮬레이션 결과 적응적 전송률은 자기유사성을 갖는 IP 트래픽 패턴이 총 전송률 변화 횟수, 전송률 절감 및 에너지 절약율에 영향을 미침을 확인할 수 있었으며 높은 전송률 변화로 인한 오버헤드의 발생을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4357-4378
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• 2017

In cooperative multi-relay networks, the relay nodes which are selected are very important to the system performance. How to choose the best cooperative relay nodes is an optimization problem. In this paper, multi-relay selection schemes which consider either single objective or multi-objective are proposed based on evolutionary algorithms. Firstly, the single objective optimization problems of multi-relay selection considering signal to noise ratio (SNR) or power efficiency maximization are solved based on the quantum bee colony optimization (QBCO). Then the multi-objective optimization problems of multi-relay selection considering SNR maximization and power consumption minimization (two contradictive objectives) or SNR maximization and power efficiency maximization (also two contradictive objectives) are solved based on non-dominated sorting quantum bee colony optimization (NSQBCO), which can obtain the Pareto front solutions considering two contradictive objectives simultaneously. Simulation results show that QBCO based multi-relay selection schemes have the ability to search global optimal solution compared with other multi-relay selection schemes in literature, while NSQBCO based multi-relay selection schemes can obtain the same Pareto front solutions as exhaustive search when the number of relays is not very large. When the number of relays is very large, exhaustive search cannot be used due to complexity but NSQBCO based multi-relay selection schemes can still be used to solve the problems. All simulation results demonstrate the effectiveness of the proposed schemes.