• Structural Engineering and Mechanics
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• v.75 no.6
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• pp.659-674
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• 2020

The present paper employs nonlocal strain gradient theory (NSGT) to study buckling behavior of functionally graded magneto-electro-thermo-elastic (FG-METE) nanoshells under various physical fields. NSGT modeling of the nanoshell contains two size parameters, one related to nonlocal stress field and another related to strain gradients. It is considered that mechanical, thermal, electrical and magnetic loads are exerted to the nanoshell. Temperature field has uniform and linear variation in nanoshell thickness. According to a power-law function, piezo-magnetic, thermal and mechanical properties of the nanoshell are considered to be graded in thickness direction. Five coupled governing equations have been obtained by using Hamilton's principle and then solved implementing Galerkin's method. Influences of temperature field, electric voltage, magnetic potential, nonlocality, strain gradient parameter and FG material exponent on buckling loads of the FG-METE nanoshell have been studied in detail.

• Structural Engineering and Mechanics
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• v.67 no.2
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• pp.175-183
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• 2018

This research deals with the wave dispersion analysis of functionally graded double-layered nanobeam systems (FG-DNBSs) considering the piezoelectric effect based on nonlocal strain gradient theory. The nanobeam is modeled via Euler-Bernoulli beam theory. Material properties are considered to change gradually along the nanobeams' thickness on the basis of the rule of mixture. By implementing a Hamiltonian approach, the Euler-Lagrange equations of piezoelectric FG-DNBSs are obtained. Furthermore, applying an analytical solution, the dispersion relations of smart FG-DNBSs are derived by solving an eigenvalue problem. The effects of various parameters such as nonlocality, length scale parameter, interlayer stiffness, applied electric voltage, relative motions and gradient index on the wave dispersion characteristics of nanoscale beam have been investigated. Also, validity of reported results is proven in the framework of a diagram showing the convergence of this model's curve with that of a previous published attempt.

• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.374-379
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• 2018

The piezocomposite transducer is widely used because it is highly efficient in transforming electric energy into mechanical energy, and its frequency range is broader than that of other types of ultrasound transducers. A general piezocomposite transducer is composed of an acoustic lens, impedance matching layers, piezoelectric materials, and backing layers. When an input voltage is applied to a piezoelectric material as an active material, it generates sound waves while vibrating. At that time, an impedance matching layer helps the sound waves to propagate forward while reducing the impedance mismatch that may occur at the interface between the active material and its front material. The impedance mismatch has a negative effect on the signal of an ultrasound transducer; thus, it is important to design a matching layer to overcome the issue. In this study, an optimized feature of a matching layer with gradient properties is studied. An objective function is defined to minimize both the average and the deviation of the reflection coefficients that are functions of the frequencies. As a result, an improvement in the signal characteristics with respect to the sensitivity and bandwidth is reported.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2001.04a
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• pp.202-205
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• 2001

In this study, the electrokinetic remediation test for the kaolin contaminated by lead was performed and voltage, zeta potential, pH distribution, current, contamination transport in soil sample were studied and finite differential numerical analysis program(HERP) for a contaminated soil were compared with those of test. From the result of HERP, in the anode it was represented that the rest concentration was decreased with the voltage. Hence, if treatment time was continued for a long in the constant voltage, comparing with sample having no change in the rest concentration, it is considered that the voltage gradient is the control factor of the rest concentration.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.1374-1377
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• 2006

The voltage distribution of an external electrode fluorescent lamp(EEFL) having a gas pressure of 50 torr and a gas composition of Ne:Ar with a ratio of 90:10 has been estimated by varying the distance between the two external electrodes and monitoring the change of the lamp voltage. The estimated voltage gradient, which represents the electric field in the positive column of the EEFL, was very sensitive to the electrode area of EEFL and was in the range of $13\;{\sim}\;27\;V/cm$ at the electrode length of $15\;{\sim}\;31\;mm$. Changing the lamp current in the range $3\;{\sim}\;5\;mA$ did not make noticeable difference in the electric field of the positive column. Theses results may serve as basic data for the optimization of electric and optic characteristics of EEFL.

• Transactions on Electrical and Electronic Materials
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• v.16 no.4
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• pp.173-178
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• 2015

In lieu of the excellent radio frequency (RF) performance of microelectromechanical system ( MEMS) switches, these micro switches need higher actuation voltage for their operation. This requirement is secondary to concerns over the swtiches’ reliability. This paper reports high reliability operation of RF MEMS switches with low voltage requirements. The proposed switch is optimised to perform in the Q-band, which results in actuation voltage of just 16.4 V. The mechanical stress gradient in the thin micro membrane is computed by simulating von Mises stress in a multi-physics environment that results in 90.4 MPa stress. The computed spring constant for the membrane is 3.02 N/m. The switch results in excellent RF performance with simulated isolation of above 38 dB, insertion loss of less than 0.35 dB and return loss of above 30 dB in the Q-band.

• Journal of IKEEE
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• v.21 no.1
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• pp.66-69
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• 2017

In recent year, energy harvesting technologies from the ambient environments such as light, motion, wireless waves, and temperature again a lot of attraction form research community [1-5] due to its efficient solution in order to substitute for conventional power delivery methods, especially in wearable together with on-body applications. The drawbacks of battery-powered characteristic used in commodity applications lead to self-powered, long-lifetime circuit design. Thermoelectric generator, a solid-state sensor, is useful compared to the harvesting devices in order to enable self-sustained low-power applications. TEG based on the Seebeck effect is utilized to transfer thermal energy which is available with a temperature gradient into useful electrical energy. Depending on the temperature difference between two sides, amount of output power will be proportionally delivered. In this work, we illustrated a low-input voltage energy harvesting circuit applied discontinuous conduction mode (DCM) method for getting an adequate amount of energy from thermoelectric generator (TEG) for a specific wearable application. With a small temperature gradient harvested from human skin, the input voltage from the transducer is as low as 60mV, the proposed circuit, fabricated in a $0.6{\mu}m$ CMOS process, is capable of generating a regulated output voltage of 4.2V with an output power reaching to $40{\mu}W$. The proposed circuit is useful for powering energy to battery-less systems, such as wearable application devices.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1042-1047
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• 2004

Voltage control is an essential part of the electric energy transmission and distribution system to maintain proper voltage limit at the consumer's terminal. Besides the generating units that provide the basic voltage control, there are many additional voltage-controlling agents e.g., shunt capacitors, shunt reactors, static VAr compensators, regulating transformers mentioned in [1], [2]. The most popular one, among all those agents for controlling voltage levels at the distribution and transmission system, is the on-load tap changer transformer. It serves two functions-energy transformation in different voltage levels and the voltage control. Artificial Neural Network (ANN) has been realized as a convenient tool that can be used in controlling the on load tap changer in the distribution transformers. Usage of the ANN in this area needs suitable training and testing data for performance analysis before the practical application. This paper briefly describes a procedure of processing the data to train an Artificial Neural Network (ANN) to control the tap changer operating decision of parallel transformers for a closed primary bus. The data set are used to train a two layer ANN using three different neural net learning algorithms, namely, Standard Backpropagation [3], Bayesian Regularization [4] and Scaled Conjugate Gradient [5]. The experimental results are presented including performance analysis.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.877-887
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• 2015

Rapid development of cities with constant increasing load and deregulation in electricity market had forced the transmission lines to operate near their threshold capacity and can easily lead to voltage instability and caused system breakdown. To prevent such catastrophe from happening, accurate readings of voltage stability condition is required so that preventive equipment and operators can execute security procedures to restore system condition to normal. This paper introduced Enhanced Hybrid Particle Swarm Optimization algorithm to estimate the voltage stability condition which utilized Fast Voltage Stability Index (FVSI) to indicate how far or close is the power system network to the collapse point when the reactive load in the system increases because reactive load gives the highest impact to the stability of the system as it varies. Particle Swarm Optimization (PSO) had been combined with the ANN to form the Enhanced Hybrid PSO-ANN (EHPSO-ANN) algorithm that worked accurately as a prediction algorithm. The proposed algorithm reduced serious local minima convergence of ANN but also maintaining the fast convergence speed of PSO. The results show that the hybrid algorithm has greater prediction accuracy than those comparing algorithms. High generalization ability was found in the proposed algorithm.

• 한국가스학회:학술대회논문집
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• 2001.10a
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• pp.98-102
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• 2001