• 한국재료학회지
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• 제33권10호
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• pp.422-429
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• 2023

High-strength low-alloy steel is one of the widely used materials in onshore and offshore plant engineering. We investigated the alloying effect of solute atoms in α-Fe based alloy using ab initio calculations. Empirical equations were used to establish the effect of alloying on the Vicker's hardness, screw energy coefficient, and edge dislocation energy coefficient of the steel. Screw and edge energy coefficients were improved by the addition of V and Cr solute atoms. In addition, the addition of trace quantities of V, Cr, and Mn enhanced abrasion resistance. Solute atoms and contents with excellent mechanical properties were selected and their thermal conductivity and thermal expansion behavior were investigated. The addition of Cr atom is expected to form alloys with low thermal conductivity and thermal expansion coefficient. This study provides a better understanding of the state-of-the-art research in low-alloy steel and can be used to guide researchers to explore and develop α-Fe based alloys with improved properties, that can be fabricated in smart and cost-effective manners.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2015년도 추계 학술논문 발표대회
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• pp.170-171
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• 2015

Resource procurement and material handling are considered as a significant part of construction project especially in large or tall building construction site. There are multiple variables that must be considered in a construction site during finishing work such as movement of materials, equipments, and workers. Therefore, it is difficult for construction workers to find the material handling path solely by intuition. The aim of this study is to propose a real-time path finding model suitable for complicated logistics flow in the field. The model explores the optimal transport path of finishing material with its basis on optimization algorithm, and it determines the direction of the Smart Sign. The proposed model is expected to be utilized for planning of efficient finishing material handling.

• Transactions on Electrical and Electronic Materials
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• 제18권2호
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• pp.59-61
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• 2017

This research was analyzed thermal characteristics that was appointed disadvantage when smart LED driver ICs was packaged and we applied extracted thermal characteristics for optimal layout design. We confirmed reliability of smart LED driver ICs package without additional heat sink. If the package is not heat sink, we are possible to minimize package. For extracting thermal loss due to overshoot current, we increased driver current by two and three times. As a result of experiment, we obtained 22 mW and 49.5 mW thermal loss. And we obtained optimal data of 350 mA driver current. It is important to distance between power MOSFET and driver ICs. If the distance was increased, the temperature of package was decreased. And so we obtained optimal data of 3.7 mm distance between power MOSFET and driver ICs. Finally, we fabricated real package and we analyzed the electrical characteristics. We obtained constant 35 V output voltage and 80% efficiency.

• Transactions on Electrical and Electronic Materials
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• 제18권2호
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• pp.111-118
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• 2017

The increased diversity of different types of energy sources requires moving towards smart distribution networks. This paper proposes a probabilistic DG (distributed generation) units planning model to determine technology type, capacity and location of DG units while simultaneously allocating ESS (energy storage systems) based on pre-determined capacities. This problem is studied in a wind integrated power system considering loads, prices and wind power generation uncertainties. A suitable method for DG unit planning will reduce costs and improve reliability concerns. Objective function is a cost function that minimizes DG investment and operational cost, purchased energy costs from upstream networks, the defined cost to reliability index, energy losses and the investment and degradation costs of ESS. Electrical load is a time variable and the model simulates a typical radial network successfully. The proposed model was solved using the DICOPT solver under GAMS optimization software.

• Smart Structures and Systems
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• 제20권4호
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• pp.499-508
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• 2017

The ionic polymer-metal composite (IPMC) is an electroactive polymer material and has a promising potential as actuators for propulsion and locomotion in underwater systems. In this paper a physics based model is used to analyse the actuation dynamics of the IPMC propulsor. Moreover, proportional-integral (PI) controller is used for position control of the tip displacement of IPMC propulsor. PI parameter tuning is performed using particle swarm optimization (PSO) algorithm. Several performance indices have been used as an objective function to optimize the error of the system. Finally, the best tuning method is found out by comparing the results under various performance indices.

• Communications for Statistical Applications and Methods
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• 제18권3호
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• pp.333-342
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• 2011

전통적인 강의실의 기초통계학 수업에서 많은 학생들이 수업에 집중하지 못하고 있다. 수업 시간에 졸거나, 잡담하거나, 휴대폰을 만지작거리면서 다른 생각에 잠겨 있다. 인터넷이 가능한 컴퓨터실에서의 강의와 실습은 인터넷이 제공하는 콘텐츠와 부단히 경쟁을 해야 한다. 이러한 문제를 조금이나마 해결해 보려고 시도한 방안이 교수와 학생을 하나의 유무선 네트워크로 묶는 교육용 디지털 신경시스템 하에서 기초통계학을 가르치고 학생들이 공부하게 하자는 것이다.

• Smart Structures and Systems
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• 제4권4호
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• pp.439-448
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• 2008

Optical fiber sensors are by now broadly accepted as an innovative and reliable device for structural health monitoring, to be used either embedded into or bonded on structures. The accuracy of the strain measurement achievable by optical fiber sensors is critically dependent on the characteristics of the bonding of the various interface layers involved in the sensor bonding/embedding (structure material and gluing agent, fiber coating and gluing agent, fiber coating and fiber core). In fact, the signal of the bonded/embedded optical fiber sensor must correspond to the strain experienced by the monitored structure, but the quality of each involved interface can affect the strain transfer. This paper faces the characterization, carried on by both mechanical tests and morphological analysis, of the strain transfer function resulting with epoxidic and vinylester gluing agent on polyimide and acrylate coated optical fibers.

• Smart Structures and Systems
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• 제26권1호
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• pp.77-87
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• 2020

By employing a quasi-3D plate formulation, the present research studies static stability of magneto-electro-thermo-elastic functional grading (METE-FG) nano-sized plates. Accordingly, influences of shear deformations as well as thickness stretching have been incorporated. The gradation of piezo-magnetic and elastic properties of the nano-sized plate have been described based on power-law functions. The size-dependent formulation for the nano-sized plate is provided in the context of nonlocal elasticity theory. The governing equations are established with the usage of Hamilton's rule and then analytically solved for diverse magnetic-electric intensities. Obtained findings demonstrate that buckling behavior of considered nanoplate relies on the variation of material exponent, electro-magnetic field, nonlocal coefficient and boundary conditions.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.437-444
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• 2006

Recently, as large structures become lighter and more flexible, the necessity of structural control for reducing excessive displacement and acceleration due to seismic excitation is increased. As a means to minimize seismic damages, various base isolation systems are adopted or considered for adoption. In this study, a base isolation system using Magneto-Sensitive(MS) rubbers is proposed and shown to effectively protect structures against earthquakes. The MS Rubber is a class of smart controllable materials whose mechanical properties change instantly by the application of a magnetic field To demonstrate the advantages of this approach, the MS Rubber isolation system is compared to Lead-Rubber Bearing(LRB) isolation systems and judged based on computed responses to several historical earthquakes. The MS Rubber isolation system is shown to achieve notable decreases in base drifts over comparable passive systems with no accompanying increase in base shears or in accelerations imparted to the superstructure.

• Journal of electromagnetic engineering and science
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• 제17권4호
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• pp.186-190
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• 2017

Visible-near-infrared (VIS-NIR) spectroscopy is a fast and non-destructive method for analyzing materials. However, most commercial VIS-NIR spectrometers are inappropriate for use in various locations such as in homes or offices because of their size and cost. In this paper, we classified eight food powders using a portable VIS-NIR spectrometer with a wavelength range of 450-1,000 nm. We developed three machine learning models using the spectral data for the eight food powders. The proposed three machine learning models (random forest, k-nearest neighbors, and support vector machine) achieved an accuracy of 87%, 98%, and 100%, respectively. Our experimental results showed that the support vector machine model is the most suitable for classifying non-linear spectral data. We demonstrated the potential of material analysis using a portable VIS-NIR spectrometer.