• The Journal of Korean Physical Therapy
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• 제13권3호
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• pp.777-789
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• 2001

The purpose of this study was to investigate the possibility of using surface electromyographic signals as a measure of muscle fatigue during the wheelchair propulsion. Subjects performed wheelchair exercise tests on a motor-driven treadmill with a constant-velocity of 1.25 m/sec. During each test, the raw EMC signals were acquired from the surface electrodes attached on the belly of five muscle groups: biceps brachii, pectoralis major. deltoid, triceps brachii, and trapezius. The median power frequency(MPF), and the root mean square(RMS) amplitude were calculated for each cyclic contraction in order to quantify muscle fatigue. During the wheelchair propulsion, the MPF decreased and the RMS increased in the trapezius and deltoid. However, the decreasing MPF and the increasing RMS also fluctuated severly during dynamic muscle contractions. Therefore, the MPF and RMS values should be estimated with well-designed methods and used with caution to quantify muscle fatigue during wheelchair propulsion.

• 비파괴검사학회지
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• 제31권3호
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• pp.246-259
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• 2011

This study presents a structural health monitoring (SHM) method for bolted connections by using multi-channel wireless impedance sensor nodes and multiple PZT-interfaces. To achieve the objective, the following approaches are implemented. Firstly, a PZT-interface is designed to monitor bolt loosening in bolted connection based on variation of electro-mechanical(EM) impedance signatures. Secondly, a wireless impedance sensor node is designed for autonomous, cost-efficient and multi-channel monitoring. For the sensor platform, Imote2 is selected on the basis of its high operating speed, low power requirement and large storage memory. Finally, the performance of the wireless sensor node and the PZT-interfaces is experimentally evaluated for a bolt-connection model Damage monitoring method using root mean square deviation(RMSD) index of EM impedance signatures is utilized to estimate the strength of the bolted joint.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 추계학술발표회논문집(1)
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• pp.19-24
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• 1997

In this study, we extend the application of the interface-matrix(IM) method for reflector modeling to Analytic Flux Expansion Nodal (AFEN) method. This include the modifications of the surface-averaged net current continuity and the net leakage balance conditions for IM method in accordance with AFEN fomular. AFEN-interface matrix (AFEN-IM) method has been tested against ZION-1 benchmark problem. The numerical result AFEN-IM method shows 1.24% of maximum error and 0.42% of root-mean square error in assembly power distribution, and 0.006%Δk of neutron multiplication factor. This result proves that the interface-matrix method for reflector modeling can be useful in AFEN method.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2019년도 추계학술대회
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• pp.79-81
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• 2019

전기자동차(EV)뿐만 아니라 ESS(Energy Storage System) 등의 사용량이 증가하면서 리튬이온배터리의 중요성은 점점 커지고 있다. 리튬 이온 배터리의 정확한 상태를 추정하는 것은 배터리의 안전하고 신뢰성 있는 작동을 위해 매우 중요하다. 본 논문에서는 AEKF(Adaptive Extended Kalman Filter)를 이용한 배터리 파라미터와 충전상태(SOC, State of Charge)를 추정하고, 이를 활용하여 배터리의 건강상태(SOH, State of Health)를 추정하는 간단한 알고리즘을 제시한다. AEKF에 파라미터 값을 적용하여 SOC를 추정하고, 추정된 SOC값과 전류 적산을 이용하여 SOH를 추정한다. SOC 오차에 따른 SOH 추정 값의 편차는 SOC 연산 간격을 늘리고 가중치 필터를 적용하여 최소화시킴으로써 결과의 정확성을 향상했다. 다양한 자동차의 표준 주행 패턴을 적용한 실험을 통해 제안된 방법을 이용하여 얻어진 SOH 추정 결과는 RMSE(Root Mean Square Error) 1.428% 이내임을 검증하였다.

• Journal of Power Electronics
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• 제15권4호
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• pp.1139-1147
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• 2015

In this paper, an algorithm based on a model analysis of the online calculation of the root-mean-square (RMS) value of welding current for single-phase AC resistance spot welding (RSW) was developed. The current is highly nonlinear and typically non-sinusoidal, which makes the measuring and controlling actions difficult. Though some previous methods focused on this issue, they were so complex that they could not be effectively used in general cases. The electrical model of a single-phase AC RSW was analyzed, and then an algorithm for online calculation of the RMS value of the welding current was presented. The description includes two parts, a model-dependent part and a model-independent part. Using a previous work about online measurement of the power factor angle, the first part can be solved. For the second part, although the solution of the governing equation can be directly obtained, a lot of CPU time must be consumed due to the fact that it involves a lot of complex calculations. Therefore, a neural network was employed to simplify the calculations. Finally, experimental results and a corresponding analysis showed that the proposed algorithm can obtain the RMS values with a high precision while consuming less time when compared to directly solving the equations.

• Journal of Power Electronics
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• 제6권4호
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• pp.290-297
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• 2006

Various methods have been discussed to reduce detent force in a tubular permanent magnet type linear single phase AC generator. In particular, the proposed methods depend on variations of the permanent magnet construction. These methods include two approaches in the form of sloped magnets, and conical magnets in addition to the conventional method of optimizing the magnet length. The undesired detent force ripples were calculated by a two dimensional Finite Element Method (FEM). Moreover, the generated electromotive force in the stator coils was calculated for each configuration of the permanent magnet. The experimental results agreed well with those obtained from the FEM-based simulations. Sufficient reduction in the detent force was achieved over the range of 40% while the root mean square of the output voltage was maintained. It was found that sloping the permanent magnet decreased the detent force and at the same time increased the generated rms voltage of the AC generator. The performance of the designed linear AC generator was evaluated in terms of its efficiency, total weight, losses, and power to weight ratio.

• Advances in Energy Research
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• 제6권2호
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• pp.131-143
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• 2019

Global Solar Radiation (GSR) is the key element for performance estimation of any Solar Power Plant (SPP). Its forecasting may help in estimation of power production from a SPP well in advance, and may also render help in optimal use of this power. Seasonal Auto-Regressive Moving Average (SARMA) and Artificial Neural Network (ANN) models are combined in order to develop a hybrid model (SARMA-ANN) conceiving the characteristics of both linear and non-linear prediction models. This developed model has been used for prediction of GSR at Gorakhpur, situated in the northern region of India. The proposed model is beneficial for the univariate forecasting. Along with this model, we have also used Auto-Regressive Moving Average (ARMA), SARMA, ANN based models for 1 - 6 day-ahead forecasting of GSR on hourly basis. It has been found that the proposed model presents least RMSE (Root Mean Square Error) and produces best forecasting results among all the models considered in the present study. As an application, the comparison between the forecasted one and the energy produced by the grid connected PV plant installed on the parking stands of the University shows the superiority of the proposed model.

• Nuclear Engineering and Technology
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• 제53권9호
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• pp.2788-2802
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• 2021

Multigroup cross section (MG XS) generation by the UNIST in-house Monte Carlo (MC) code MCS for fast reactor analysis using nodal diffusion codes is reported. The feasibility of the approach is quantified for two sodium fast reactors (SFRs) specified in the OECD/NEA SFR benchmark: a 1000 MW_th metal-fueled SFR (MET-1000) and a 3600 MW_th oxide-fueled SFR (MOX-3600). The accuracy of a few-group XSs generated by MCS is verified using another MC code, Serpent 2. The neutronic steady-state whole-core problem is analyzed using MCS/RAST-K with a 24-group XS set. Various core parameters of interest (core k_eff, power profiles, and reactivity feedback coefficients) are obtained using both MCS/RAST-K and MCS. A code-to-code comparison indicates excellent agreement between the nodal diffusion solution and stochastic solution; the error in the core k_eff is less than 110 pcm, the root-mean-square error of the power profiles is within 1.0%, and the error of the reactivity feedback coefficients is within three standard deviations. Furthermore, using the super-homogenization-corrected XSs improves the prediction accuracy of the control rod worth and power profiles with all rods in. Therefore, the results demonstrate that employing the MCS MG XSs for the nodal diffusion code is feasible for high-fidelity analyses of fast reactors.

• 전력전자학회논문지
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• 제27권3호
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• pp.214-220
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• 2022

This paper proposes a test device designed for developing a high-voltage multilayer ceramic capacitor (MLCC). The proposed topology consists of an energy recovery circuit for charging/discharging capacitor, a flyback converter, and a boost converter for supplying power and a bias voltage application to the energy recovery circuit. The energy recovery circuit designed with a half-bridge converter has auxiliary switches operating before the main switches to prevent excessive current from flowing to the main switches. A prototype has been designed to verify the reliability of target capacitors following the voltage fluctuation with a frequency range below 65 kHz. To conduct high root mean square (RMS) current to the capacitor as a load, the MLCC test was conducted after the topology verification was completed through the film capacitor as a load. Through the agreement between the RMS current formula proposed in this paper and the MLCC test results, the possibility of its use was demonstrated for high-voltage MLCC development in the future.

• 한국농공학회논문집
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• 제52권6호
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• pp.1-7
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• 2010

This study was carried out to investigate the effect of hydro power factors (e.g., irrigation area, watershed area, active storage, gross head) on annual generation capacity and operation ratio for agricultural reservoirs in Chungbuk Province with active storage of over 1 million $m^3$. The annual generation capacity and operation ratio were estimated using HOMWRS (Hydrological Operation Model for Water Resources System) from last 10-year daily hydrological data. The correlation coefficients between annual generation capacity and the hydro power factors except gross head were high (over 0.87), but the correlation coefficients between operational rate and the factors were low (below 0.28). The optimum multiple regression equations of the annual generation capacity were expressed as the functions of watershed area, active storage, and gross head. Also, the simple regression equation of annual generation capacity was expressed as a function of watershed area. The average relative root-mean-square-error (RRMSE) between observed and estimated values by the optimum multiple regression equations was smaller than that by the simple regression equation, suggesting that the former has more accuracy than the latter.