• Title/Summary/Keyword: performance-based optimization

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Analysis of HVDC Inverter and Application of Objective Functions for the Optimal Filter Design (직류송전 인버터의 필터 최적설계를 위한 해석 및 목적함수의 선정)

  • 오성철;정교범
    • The Transactions of the Korean Institute of Power Electronics
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    • v.6 no.1
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    • pp.82-89
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    • 2001
  • This paper proposes several methods to analyze dynamic and static characteristics of HVDC inverter system. The characteristic analysis is essential of the controller and filter design of the HVDC inverter system. Dynamic characteristic can be analyzed with EMTP simulation and static characteristic can be obtained by solving newly proposed load flow equation which includes the filter and load characteristic. New simple per-phase-equivalent circuit is also proposed. In this circuit, HVDC inverter is considered as a current source depending on the on-off status of switch. Dynamic and static characteristic can be analyzed by the proposed per-phase-equivalent circuit. For the optimal filter design, various performance criteria are proposed. The performance index, based on the per-phase-equivalent circuit, is calculated. Voltage harmonics and filter power loss are selected as criteria. Optimization procedure is explained to find optimal passive filter parameters.

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Performance Optimization of High Specific Speed Pump-Turbines by Means of Numerical Flow Simulation (CFD) and Model Testing

  • Kerschberger, Peter;Gehrer, Arno
    • International Journal of Fluid Machinery and Systems
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    • v.3 no.4
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    • pp.352-359
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    • 2010
  • In recent years, the market has shown increasing interest in pump-turbines. The prompt availability of pumped storage plants and the benefits to the power system achieved by peak lopping, providing reserve capacity, and rapid response in frequency control are providing a growing advantage. In this context, there is a need to develop pumpturbines that can reliably withstand dynamic operation modes, fast changes of discharge rate by adjusting the variable diffuser vanes, as well as fast changes from pumping to turbine operation. In the first part of the present study, various flow patterns linked to operation of a pump-turbine system are discussed. In this context, pump and turbine modes are presented separately and different load cases are shown in each operating mode. In order to create modern, competitive pump-turbine designs, this study further explains what design challenges should be considered in defining the geometry of a pump-turbine impeller. The second part of the paper describes an innovative, staggered approach to impeller development, applied to a low head pump-turbine project. The first level of the process consists of optimization strategies based on evolutionary algorithms together with 3D in-viscid flow analysis. In the next stage, the hydraulic behavior of both pump mode and turbine mode is evaluated by solving the full 3D Navier-Stokes equations in combination with a robust turbulence model. Finally, the progress in hydraulic design is demonstrated by model test results that show a significant improvement in hydraulic performance compared to an existing reference design.

Multibeam Satellite Frequency/Time Duality Study and Capacity Optimization

  • Lei, Jiang;Vazquez-Castro, Maria Angeles
    • Journal of Communications and Networks
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    • v.13 no.5
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    • pp.472-480
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    • 2011
  • In this paper, we investigate two new candidate transmission schemes, non-orthogonal frequency reuse (NOFR) and beam-hopping (BH). They operate in different domains (frequency and time/space, respectively), and we want to know which domain shows overall best performance. We propose a novel formulation of the signal-to-interference plus noise ratio (SINR) which allows us to prove the frequency/time duality of these schemes. Further, we propose two novel capacity optimization approaches assuming per-beam SINR constraints in order to use the satellite resources (e.g., power and bandwidth) more efficiently. Moreover, we develop a general methodology to include technological constraints due to realistic implementations, and obtain the main factors that prevent the two technologies dual of each other in practice, and formulate the technological gap between them. The Shannon capacity (upper bound) and current state-of-the-art coding and modulations are analyzed in order to quantify the gap and to evaluate the performance of the two candidate schemes. Simulation results show significant improvements in terms of power gain, spectral efficiency and traffic matching ratio when comparing with conventional systems, which are designed based on uniform bandwidth and power allocation. The results also show that BH system turns out to show a less complex design and performs better than NOFR system specially for non-real time services.

Hybrid Optimization Techniques Using Genetec Algorithms for Auto-Tuning Fuzzy Logic Controllers (유전 알고리듬을 이용한 자동 동조 퍼지 제어기의 하이브리드 최적화 기법)

  • Ryoo, Dong-Wan;Lee, Young-Seog;Park, Youn-Ho;Seo, Bo-Hyeok
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.1
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    • pp.36-43
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    • 1999
  • This paper proposes a new hybrid genetic algorithm for auto-tuning fuzzy controllers improving the performance. In general, fuzzy controllers use pre-determined moderate membership functions, fuzzy rules, and scaling factors, by trial and error. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a hybrid genetic algorithm. The object of the proposed algorithm is to promote search efficiency by the hybrid optimization technique. The proposed hybrid genetic algorithm is based on both the standard genetic algorithm and a modified gradient method. If a maximum point is not be changed around an optimal value at the end of performance during given generation, the hybrid genetic algorithm searches for an optimal value using the the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algoritms. Simulation results verify the validity of the presented method.

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Online Turn-Off Angle Contro1 for Performance Optimization of the Switched Reluctance Motor (온라인 턴 오프각제어를 통한 SRM의 성능최적화)

  • Jeong, Byeong-Ho;Choi, Youn-Ok;Lee, Kang-Yeon;Cho, Geum-Bae;Chung, Soo-Bok
    • The Transactions of the Korean Institute of Power Electronics
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    • v.12 no.1
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    • pp.98-106
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    • 2007
  • This paper represent improved on-line turn off angle control schemes for switched reluctance motors based on current control. For the purpose of finding the optimal commutation switching angle point with improved controller, it is utilized turn on and turn off position calculation with inductance vs. current vs. not linkage analysis method. The goal of proposed paper is the maximization of the energy conversion per stroke and torque ripple reduction and obtaining approximately flat-topped current waveform. The proposed control scheme is demonstrated simulation and on a prototype experimental system.

CoMP Transmission for Safeguarding Dense Heterogeneous Networks with Imperfect CSI

  • XU, Yunjia;HUANG, Kaizhi;HU, Xin;ZOU, Yi;CHEN, Yajun;JIANG, Wenyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.110-132
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    • 2019
  • To ensure reliable and secure communication in heterogeneous cellular network (HCN) with imperfect channel state information (CSI), we proposed a coordinated multipoint (CoMP) transmission scheme based on dual-threshold optimization, in which only base stations (BSs) with good channel conditions are selected for transmission. First, we present a candidate BSs formation policy to increase access efficiency, which provides a candidate region of serving BSs. Then, we design a CoMP networking strategy to select serving BSs from the set of candidate BSs, which degrades the influence of channel estimation errors and guarantees qualities of communication links. Finally, we analyze the performance of the proposed scheme, and present a dual-threshold optimization model to further support the performance. Numerical results are presented to verify our theoretical analysis, which draw a conclusion that the CoMP transmission scheme can ensure reliable and secure communication in dense HCNs with imperfect CSI.

Dynamic analysis and performance optimization of permendur cantilevered energy harvester

  • Ghodsi, Mojtaba;Ziaiefar, Hamidreza;Mohammadzaheri, Morteza;Omar, Farag K.;Bahadur, Issam
    • Smart Structures and Systems
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    • v.23 no.5
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    • pp.421-428
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    • 2019
  • The development of the low power application such as wireless sensors and health monitoring systems, attract a great attention to low power vibration energy harvesters. The recent vibration energy harvesters use smart materials in their structures to convert ambient mechanical energy into electricity. The frequent model of this harvesters is cantilevered beam. In the literature, the base excitation cantilevered harvesters are mainly investigated, and the related models are presented. This paper investigates a tip excitation cantilevered beam energy harvester with permendur. In the first section, the mechanical model of the harvester and magneto-mechanical model of the permendur are presented. Later, to find the maximum output of the harvester, based on the response surface method (RSM), some experiments are done, and the results are analyzed. Finally, to verify the results of RSM, a harvester with optimum design variables is made, and its output power is compared. The last comparison verifies the estimation of the RSM method which was about $381{\mu}W/cm^3$.

A Study on Optimum Design of an Axial Cylcone structure using Response Surface Method (반응표면법을 활용한 축류형 사이클론 구조 최적화 설계에 관한 연구)

  • Cho, Jinill;Yun, Junho;Cho, Yeongkwang;Seok, Hyunho;Kim, Taesung
    • Particle and aerosol research
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    • v.17 no.3
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    • pp.71-79
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    • 2021
  • Ultrafine dust, which is emitted from industrial factories or all kinds of vehicles, threatens the human's respiratory system and our environment. In this regard, separating airborne particles is essential to mitigate the severe problem. In this work, an axial cyclone for the effective technology of eliminating harmful dust is investigated by numerical simulation using Ansys 2020, Fluent R2. In addition, the optimized structure of the cyclone is constructed by means of multi objective optimization based on the response surface method which is a representative method to analyze the effect of design parameter on response variables. Among several design parameters, the modified length of the vortex finder and dust collector is a main point in promoting the performance of the axial cyclone. As a result, the optimized cyclone exhibits remarkable performance when compared to the original model, resulting in pressure drop of 307 Pa and separator efficiency of 98.5%.

Comparing automated and non-automated machine learning for autism spectrum disorders classification using facial images

  • Elshoky, Basma Ramdan Gamal;Younis, Eman M.G.;Ali, Abdelmgeid Amin;Ibrahim, Osman Ali Sadek
    • ETRI Journal
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    • v.44 no.4
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    • pp.613-623
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    • 2022
  • Autism spectrum disorder (ASD) is a developmental disorder associated with cognitive and neurobehavioral disorders. It affects the person's behavior and performance. Autism affects verbal and non-verbal communication in social interactions. Early screening and diagnosis of ASD are essential and helpful for early educational planning and treatment, the provision of family support, and for providing appropriate medical support for the child on time. Thus, developing automated methods for diagnosing ASD is becoming an essential need. Herein, we investigate using various machine learning methods to build predictive models for diagnosing ASD in children using facial images. To achieve this, we used an autistic children dataset containing 2936 facial images of children with autism and typical children. In application, we used classical machine learning methods, such as support vector machine and random forest. In addition to using deep-learning methods, we used a state-of-the-art method, that is, automated machine learning (AutoML). We compared the results obtained from the existing techniques. Consequently, we obtained that AutoML achieved the highest performance of approximately 96% accuracy via the Hyperpot and tree-based pipeline optimization tool optimization. Furthermore, AutoML methods enabled us to easily find the best parameter settings without any human efforts for feature engineering.

Optimal Design of the Monolithic Flexure Mount for Optical Mirror Using Response Surface Method (반응표면법을 이용한 광학미러용 일체형 유연힌지 마운트 최적설계)

  • Kyoungho Lee;Byounguk Nam;Sungsik Nam
    • Journal of the Korea Institute of Military Science and Technology
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    • v.26 no.3
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    • pp.205-213
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    • 2023
  • An optimal design of a simple beam-shaped flexure hinge mount supporting an optical mirror is presented. An optical mirror assembly is an opto-mechanically coupled system as the optical and mechanical behaviors interact. This side-supporting mount is flexible in the radial direction and rigid for the remaining degrees of freedom to support the mirror without transferring thermal load. Through thermo-elastic, optical and eigenvalue analysis, opto-mechanical performance was predicted to establish the objective functions for optimization. The key design parameters for this flexure are the thickness and length. To find the optimal values of design parameters, response surface analysis was performed using the design of experiment based on nested FCD. Optimal design candidates were derived from the response surface analysis, and the optimal design shape was confirmed through Opto-mechanical performance validation analysis.