• Title/Summary/Keyword: Input Optimization

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A Minimization Study of Consuming Current and Torque Ripple of Low Voltage BLDC Motor (저전압용 BLDC 전동기의 소비전류 및 토크리플 최소화 연구)

  • Kim, Han-Deul;Shin, Pan Seok
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.12
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    • pp.1721-1724
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    • 2017
  • This paper presents a numerical optimization technique to reduce input current and torque ripple of the low voltage BLDC motor using core, coil and switching angle optimization. The optimization technique is employed using the generalized response surface method(RSM) and sampling minimization technique with FEM. A 50W 24V BLDC motor is used to verify the proposed algorithm. As optimizing results, the input current is reduced from 2.46 to 2.11[A], and the input power is reduced from 59 [W] to 51 [W] at the speed of 1000 [rpm]. Also, applied the same optimization algorithm, the torque ripple is reduced about 7.4 %. It is confirmed that the proposed technique is a reasonably useful tool to reduce the consuming current and torque ripple of the low voltage BLDC motor for a compact and efficient design.

Optimization of Fuzzy Set Fuzzy Model by Means of Hierarchical Fair Competition-based Parallel Genetic Algorithms (계층적 경쟁기반 병렬 유전자 알고리즘을 이용한 퍼지집합 퍼지모델의 최적화)

  • Choi, Jeoung-Nae;Oh, Sung-Kwun;Hwang, Hyung-Soo
    • Proceedings of the KIEE Conference
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    • 2006.07d
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    • pp.2097-2098
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    • 2006
  • In this study, we introduce the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA). HFCGA is a kind of multi-populations of Parallel Genetic Algorithms(PGA), and it is used for structure optimization and parameter identification of fuzzy set model. It concerns the fuzzy model-related parameters as the number of input variables, a collection of specific subset of input variables, the number of membership functions, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. The structural optimization is realized via HFCGA method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.

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Optimization of input carrier powers considering satellite link environment in the multi-level SCPC systems (Multi-level SCPC 시스템에서 링크환경을 고려한 중계기 입력반송파 전력의 최적화)

  • 김병균;최형진
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.5
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    • pp.1240-1255
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    • 1996
  • This paper suggests power optimization technique in multi-level SCPC system as a method for efficient utilization of limited satellite power. The power optimization is realized by optimal assignment of satellite input carrier powers considering interference and noise generated in up-link and down-link. The Fletcher-Powell algorithm searching minimum(or maximum) point using gradient information is used to detemine the optimal input carrier powers. To apply Flectcher-Powell algorithm mathematical descriptions and their partial derivatives to interference and nose are presented. Because a target, which should be optimized, is satellite input carrier power, amplitude of each carrier group will be assumed to be an independent variable. The performance criterion for optimal power assignmentis classified into 4 categories with respect to CNR of destination receiver earth station to meet the requirement for various satellite link environment. Simulation results for two-level, four-level and six-level SCPC system are presented.

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Dynamic mix design optimization of high-performance concrete

  • Ziaei-Nia, Ali;Shariati, Mahdi;Salehabadi, Elnaz
    • Steel and Composite Structures
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    • v.29 no.1
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    • pp.67-75
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    • 2018
  • High performance concrete (HPC) depends on various parameters such as the type of cement, aggregate and water reducer amount. Generally, the ready concrete company in various regions according to the requirements and costs, mix design of concrete as well as type of cement, aggregates, and, amount of other components will vary as a result of moment decisions or dynamic optimization, though the ideal conditions will be more applicable for the design of mix proportion of concrete. This study aimed to apply dynamic optimization for mix design of HPC; consequently, the objective function, decision variables, input and output variables and constraints are defined and also the proposed dynamic optimization model is validated by experimental results. Results indicate that dynamic optimization objective function can be defined in such a way that the compressive strength or performance of all constraints is simultaneously examined, so changing any of the variables at each step of the process input and output data changes the dynamic of the process which makes concrete mix design formidable.

Reliability Based Topology Optimization of Compliant Mechanisms (컴플라이언트 메커니즘의 신뢰성 기반 위상최적설계)

  • Im, Min-Gyu;Park, Jae-Yong;Han, Seog-Young
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.6
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    • pp.826-833
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    • 2010
  • Electric-thermal-structural actuated compliant mechanisms are mechanisms onto which electric voltage drop is applied as input instead of force. This mechanism is based on thermal expansion of material while being heated. Compliant mechanisms are designed subjected to electric charge input using BESO(bi-directional evolutionary structural optimization) method. Reliability-based topology optimization (RBTO) is applied to the topology design of actuators. performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints. In this study, BESO method is used to obtain optimal topology of compliant mechanisms from initial design domain. PMA approach is used to evaluate reliability index. The procedure has been tested in numerical applications and compared with the results obtained by other methods to validate these approaches.

Design optimization and vibratory loads analysis of active twist rotor blades incorporating single crystal piezoelectric fiber composites (단결정 압전섬유작동기를 사용한 능동 비틀림 로터 블레이드의 최적 설계 및 진동하중 해석)

  • Park, Jae-Sang;Shin, Sang-Joon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.05a
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    • pp.85-92
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    • 2007
  • This paper presents a design optimization of a new Advanced Active Blade Twist (AATR-II) blade incorporating single crystal Macro Fiber Composites (MFC) and conducts vibratory loads reduction analysis using an obtained optimal blade configuration. Due to the high actuation performance of the single crystal MFC, the AATR blade may reduce the helicopter vibration more efficiently even with a lower input-voltage as compared with the previous ATR blades. The design optimization provides the optimal cross-sectional configuration to maximize the tip twist actuation when a certain input-voltage is given. In order to maintain the properties of the original ATR blade, various constraints and bounds are considered for the design variables selected. After the design optimization is completed successfully, vibratory load reduction analysis of the optimized AATR-II blade in forward flight condition is conducted. The numerical result shows that the hub vibratory loads are reduced significantly although 20% input-voltage of the original ATR blade is used.

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An Interactive Approach to Multiple Response Optimization (다중반응최적화를 위한 상호교호적 접근법)

  • Lee, Pyoungsoo;Park, K. Sam
    • Journal of the Korean Operations Research and Management Science Society
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    • v.40 no.3
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    • pp.49-61
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    • 2015
  • We study the problem of multiple response optimization (MRO) and focus on the selection of input levels which will produce desirable output quality. We propose an interactive multiple objective optimization approach to the input design. The earlier interactive methods utilized for MRO communicate with the decision maker only using the response variable values, in order to improve the current response values, thereby resulting in the corresponding design solution automatically. In their interaction steps of preference articulation, no account is taken of any active changes in design variable values. On the contrary, our approach permits the decision maker to change the design variable values in its interaction stage, which makes possible the consideration of the preference or economics of the design variable side. Using some typical value functions, we also demonstrate that our method converges reasonably well to the known optimal solutions.

A V­Groove $CO_2$ Gas Metal Arc Welding Process with Root Face Height Using Genetic Algorithm

  • Ahn, S.;Rhee, S.
    • International Journal of Korean Welding Society
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    • v.3 no.2
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    • pp.15-23
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    • 2003
  • A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

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Determination on Optima Condition for a Gas Metal Arc Welding Process Using Genetic Algorithm (유전 알고리즘을 이용한 가스 메탈 아크 용접 공정의 최적 조건 설정에 관한 연구)

  • 김동철;이세헌
    • Journal of Welding and Joining
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    • v.18 no.5
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    • pp.63-69
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    • 2000
  • A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

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