• Journal of KSNVE
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• v.8 no.4
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• pp.632-642
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• 1998

A method based on finite element discretization is developed for optimizing the polarization profile of PVDF film to create the modal transducer for specific modes. Using this concept, one can design the modal transducer in two-dimensional structure having arbitrary geometry and boundary conditions. As a practical means for implementing this polarization profile without repoling the PVDF film the polarization profile is approximated by optimizing electrode patterns, lamination angles, and poling directions of the multi-layered PVDF transducer. This corresponds to the approximation of a continuous function using discrete values. The electrode pattern of each PVDF layer is optimized by deciding the electrode of each finite element to be used or not. Genetic algorithm, suitable for discrete problems, is used as an optimization scheme. For the optimization of each layers lamination angle, the continuous lamination angle is encoded into discrete value using binary 5 bit string. For the experimental demonstration, a modal sensor for first and second modes of cantilevered composite plate is designed using two layers of PVDF films. The actuator is designed based on the criterion of minimizing the system energy in the control modes under a given initial condition. Experimental results show that the signals from residual modes are successfully reduced using the optimized multi-layered PVDF sensor. Using discrete LQG control law, the modal peaks of first and second modes are reduced in the amount of 12 dB and 4 dB, resepctively.

• 한국태양에너지학회:학술대회논문집
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• 2009.11a
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• pp.388-393
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• 2009

It is important to know character about efficiency of converters before manufacturing it. Recently, various techniques are developed for solar array system. Converters can be used for control of solar array's condition. So, solar array with converter structures are very useful. If we want to measure converter's efficiency after manufacturing it. It's not difficult if we have measuring equipment. But we need to measure efficiency before realization converters for development of optimized efficiency and simulations. This research offers an efficiency calculation of single phase hard switching boost converter. And it is the most basic type of converters. In fact, it can be used techniques for getting higher efficiency like soft-switching and more. But the cost is an important issue in compact solar array system. One way to escape from the cost problem is finding optimized efficiency of basic types of convener.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5904-5927
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• 2019

Many artificial intelligence (AI) techniques have been embedded into various engineering technologies to assist them in achieving different goals. The integration of modern technologies with energy consumption management system and occupant's comfort inside buildings results in the introduction of intelligent building concept. The major aim of this integration is to manage the energy consumption effectively and keeping the occupant satisfied with the internal environment of the building. The last few couple of years have seen many applications of AI techniques for optimizing the energy consumption with maximizing the user comfort in smart buildings but still there is much room for improvement in this area. In this paper, a hybrid of two AI algorithms called firefly algorithm (FA) and genetic algorithm (GA) has been used for user comfort maximization with minimum energy consumption inside smart building. A complete user friendly system with data from various sensors, user, processes, power control system and different actuators is developed in this work for reducing power consumption and increase the user comfort. The inputs of optimization algorithms are illumination, temperature and air quality sensors' data and the user set parameters whereas the outputs of the optimization algorithms are optimized parameters. These optimized parameters are the inputs of different fuzzy controllers which change the status of different actuators according to user satisfaction.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.1
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• pp.63-71
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• 2000

A shift control algorithm of a newly developed two-speed gear shift system is proposed for electric vehicle applications. The algorithm is formulated according to the motor torque map and optimized to obtain the adequate propulsion characteristics for vehicle. Two speed gear system with shift control algorithm has proved greater efficiencies in terms of energy economy with its simplified hardware and software structures. The gear shifting is designed to be carried out by an actuator and the control signal from a vehicle control unit equipped with $\mu$-processor. The results of performances and efficiency of the algorithm by simulation and vehicle test are described.

• Journal of Magnetics
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• v.21 no.4
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• pp.586-592
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• 2016

The magnetic-jack type CRDM withdraws or inserts a control rod assembly from/to the reactor core to control the core reactivity. The CRDM housings form not only the path of the electromagnetic field but also the pressure boundary of a nuclear reactor, and a periodic in-service inspection should be carried out if there are welded or flange jointed parts on the pressure boundary. The in-service inspection is a time-consuming process during the reactor refueling, and moreover it is difficult to perform the inspection over the reactor head. A magnetic motor housing is applied for the current SMART CRDM and has several welding joints, however a nonmagnetic motor housing with fewer or no welding joints may improve the operational efficiency of the nuclear reactor by avoiding or simplifying the in-service inspection process. Prior to the development, the magnetic field transfer efficiency of the nonmagnetic housing was required to be assessed. It was verified and optimized by the electromagnetic analysis of the lifting force estimation. Magnetic flux rings were adopted to improve the efficiency. In this paper, the design and optimization process of a nonmagnetic motor housing with the magnetic flux rings for the SMART CRDM are introduced and the analyses results are discussed.

• Journal of Magnetics
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• v.18 no.2
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• pp.95-104
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• 2013

This paper presents a general analytical method for predicting the magnetic fields of different Halbach magnet arrays with or without back iron mounted on slotless permanent magnet (PM) linear machines. By using Fourier decomposition, the magnetization components of four typical Halbach magnet arrays are determined. By applying special synthetic boundary conditions on the PM surfaces, the expressions of their magnetic field distributions are derived based on the magnetic scalar potential (MSP), which are simpler than those based on the magnetic vector potential (MVP). The correctness of the method is validated by finite element analysis. The harmonics of airgap flux density waveforms of these Halbach magnet arrays with or without back iron are also compared and optimized.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1571-1589
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• 2016

Nodes in MANETs are battery powered which makes energy an invaluable resource. In OLSR, MPRs are special nodes that are selected by other nodes to relay their data/control traffic which may lead to high energy consumption of MPR nodes. Therefore, employing energy efficient MPR selection mechanism is imperative to ensure prolonged network lifetime. However, misbehaving MPR nodes tend to preserve their energy by dropping packets of other nodes instead of forwarding them. This leads to huge energy loss and performance degradation of existing energy efficient MPR selection schemes. This paper proposes an energy efficient secure MPR selection (ES-MPR) technique that takes into account both energy and security metrics for MPR selection. It introduces the concept of 'Composite Eligibility Index' (CEI) to examine the eligibility of a node for being selected as an MPR. CEI is used in conjunction with willingness to provide distinct selection parameters for Flooding and Routing MPRs. Simulation studies reveal the efficiency of ES-MPR in selection of energy efficient secure and stable MPRs, in turn, prolonging the network operational lifetime.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.4
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• pp.287-296
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• 2006

In this paper, optimal control strategy of the air-conditioning system with slab thermal storage was investigated based on the optimal control theory. An optimal heat output to the plenum chamber and the air-conditioned room was determined based on two kinds of criterion functions. The first one requires small deviation in room air temperature from a set-point value and low energy consumption. It is shown that the optimized control is to store heat through the whole storage time and to increase storage rate gradually with time. As the second case, a criterion that both a deviation of operative temperature from a set-point temperature and the energy consumption should be minimized was adopted. The room air temperature was a little high and the cooling load during storage time was reduced, compared with the results when a criterion function considering only the room air temperature is used.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.127-133
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• 2020

As the usages of artificial intelligence is increased, the demand to algorithms for small portable devices increases. Also as the embedded system becomes high-performance, it is possible to implement algorithms for high-speed computation and machine learning as well as operating systems. As the machine learning algorithms process repetitive calculations, it depend on the cloud environment by network connection. For an stand alone system, low power consumption and fast execution by optimized algorithm are required. In this study, for the purpose of smart control, an energy measurement sensor is connected to an embedded system, and a real-time monitoring system is implemented to store measurement information as a database. Continuously measured and stored data is applied to a learning algorithm, which can be utilized for optimal power control, and a system interfacing various sensors required for energy measurement was constructed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.9
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• pp.1065-1071
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• 2012

Wind energy is becoming one of the most preferable alternatives to conventional sources of electric power that rely on fossil fuels. For stable electric power generation, constant rotating speed control of a wind turbine is performed through pitch control and stall control of the turbine blades. Recently, variable pitch control has been implemented in modern wind turbines to harvest more energy at variable wind speeds that are even lower than the rated one. Although wind turbine pitch controllers are currently optimized using a step response via the Ziegler-Nichols auto-tuning process, this approach does not satisfy the requirements of variable pitch control. In this study, the variable pitch controller was optimized by a genetic algorithm using a neural network model that was constructed by the Latin Hypercube sampling method to improve the Ziegler-Nichols auto-tuning process. The optimized solution shows that the root mean square error, rise time, and settle time are respectively improved by more than 7.64%, 15.8%, and 15.3% compared with the corresponding initial solutions obtained by the Ziegler-Nichols auto-tuning process.