• 설비공학논문집
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• 제25권12호
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• pp.693-699
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• 2013

This paper describes a method for size optimization of the major design variables for solar water heating systems at the stage of concept design. The widely used RETScreen simulation tool was used for optimization. Currently, the RETScreen tool itself does not provide a function for optimization of the design parameters. In this study, an optimizer was combined with the software. A comparative study was performed to evaluate the RETScreen-based approach with the case study of a solar heating system in an office building. The optimized results using the RETScreen model were compared to previously published results with the TRNSYS model. The objective function of the optimization is the life-cycle cost of the system. The optimized design results from the RETScreen model showed good agreement with the optimized TRNSYS results for the solar collector area and storage volume, but presented a slight difference for the collector slope angle in terms of the converged direction of the solutions. The energy cost, life-cycle cost, and thermal performance regarding collector efficiency, system efficiency, and solar fraction were compared as well, and the RETScreen model showed good agreement with the TRNSYS model for the conditions of the base case and optimized design.

• Advances in aircraft and spacecraft science
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• 제10권3호
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• pp.245-256
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• 2023

In order to improve aerodynamic performance of multi-stage axial flow turbines used in aircraft engines, a one-dimensional aerodynamic design and optimization framework is constructed. In the method, flow path is generated by solving mass continuation and energy conservation with loss computed by the Craig & Cox model; Also real gas properties has been taken into consideration. To obtain an optimal result, a multi-objective genetic algorithm is used to optimize the efficiencies and determine values of various design variables; Final design can be selected from obtained Pareto optimal solution sets. A three-stage axial turbine is used to verify the effectiveness of the developed optimization framework, and designs are checked by three-dimensional CFD simulation. Results show that the aerodynamic performance of the optimized turbine has been significantly improved at design point, with the total-to-total efficiency increased by 1.17% and the total-to-static efficiency increased by 1.48%. As for the off-design performance, the optimized one is improved at all working points except those at small mass flow.

• International Journal of Computer Science & Network Security
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• 제21권11호
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• pp.312-320
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• 2021

Increase in computational cost and exhaustive search can lead to more complexity and computational energy. Thus, there is need for effective and efficient scheme to reduce the complexity to achieve optimal energy utilization. This will improve the energy efficiency and enhance the proficiency in terms of the resources needed to achieve convergence. This paper primarily focuses on the development of hybrid swarm intelligence scheme for reducing the computational complexity in binary optimization. In order to reduce the complexity, both artificial bee colony (ABC) and particle swarm optimization (PSO) have been employed to effectively minimize the exhaustive search and increase convergence. First, a new approach using ABC and PSO has been proposed and developed to solve the binary optimization problem. Second, the scout for good quality food sources is accomplished through the deployment of PSO in order to optimally search and explore the best source. Extensive experimental simulations conducted have demonstrate that the proposed scheme outperforms the ABC approaches for reducing complexity and energy consumption in terms of convergence, search and error minimization performance measures.

• 한국산학기술학회논문지
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• 제17권11호
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• pp.395-402
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• 2016

이 논문은 직렬형 머니퓰레이터의 관성 성질을 고려하여 에너지 효율을 향상 시키기 위한 설계 방법에 대해 논하였다. 이 방법은 운동방정식에 가장 많은 영향을 끼치는 관성 행렬을 분석하여 최적화 문제의 구속 조건에 대입하는 방식이다. 이를 위해, 첫 번째로 초기에 설계된 머니퓰레이터에 대한 동적 모델링을 도출하고 여기서 표현되는 관성 행렬의 특성을 분석한다. 두 번째로 분석된 관성 행렬의 변화 정도를 정량화하는 지표를 정의하여 구속 조건과 설계 파라미터의 경계조건을 설정하였다. 마지막으로 토크를 목적 함수로 정하고 앞서 정의된 구속 조건과 경계조건을 통하여 최적화를 수행한다. 또한, 목적 함수 외에 관성, 에너지 및 질량에 관련된 보조 지표를 정의하고 최적화된 파라미터가 요구성능을 만족하는지 다시 한번 확인하는 과정을 거치는 설계 알고리즘을 제안하였다. 제안한 설계 알고리즘의 수행 결과로 토크 최소화를 통하여 에너지 효율이 향상되었으며, 제안된 방법을 공간상의3 자유도 직렬 머니퓰레이터에 시뮬레이션 테스트 하였다. 이 설계 알고리즘은 일반적으로n 자유도를 가지는 머니퓰레이터에도 적용이 가능하다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 추계학술대회 논문집
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• pp.55-56
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• 2010

• ETRI Journal
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• 제36권4호
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• pp.686-689
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• 2014

This paper studies energy-efficiency (EE) power allocation for cognitive radio MIMO-OFDM systems. Our aim is to minimize energy efficiency, measured by "Joule per bit" metric, while maintaining the minimal rate requirement of a secondary user under a total power constraint and mutual interference power constraints. However, since the formulated EE problem in this paper is non-convex, it is difficult to solve directly in general. To make it solvable, firstly we transform the original problem into an equivalent convex optimization problem via fractional programming. Then, the equivalent convex optimization problem is solved by a sequential quadratic programming algorithm. Finally, a new iterative energy-efficiency power allocation algorithm is presented. Numerical results show that the proposed method can obtain better EE performance than the maximizing capacity algorithm.

• 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.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제51권12호
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• pp.697-703
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• 2002

Interior permanent magnet synchronous motor(IPMSM) is widely used in many applications such as an electric vehicle, compressor drives of air conditioner and machine tool spindle drives. In order to maximize the efficiency in such applications, this paper is proposed the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM The optimal current can be decided according to the operating speed and the load conditions. The proposed control algorithm is applied to IPMSM drive system, the operating characteristics controlled by efficiency optimization control are examined in detail by simulation.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권5호
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• pp.1912-1931
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• 2018

In future wireless network, user experience and energy efficiency will play more and more important roles in the communication systems compared to their roles at present. Quality of experience (QoE) and Energy Efficiency (EE) become the widely used metrics. In this paper, we study a combinatorial problem of QoE and EE and investigate a fair power allocation in heterogeneous networks. We first design a new metric, QoE-aware EE (QEE) to reflect the relationship of QoE and energy. Then, the concept of Utopia QEE is introduced, which is defined as the achievable maximum QEE in ideal conditions, for each user. Finally, we transform the power allocation process to an optimization of ratio of QEE and Utopia QEE and use invasive weed optimization (IWO) algorithm to solve the optimization problem. Numerical simulation results indicate that the proposed algorithm can get converged and efficiently improve the system energy efficiency and the QoE for each user.