• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.12
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• pp.691-700
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• 1999

This paper proposes a novel switching strategy of 1Mvar STATCON using cascade multilevel H-bridge inverter(HBI) for FACTS application. To control the reactive power instantaneously, the d-q dynamic system model is described and analyzed. A single pulse pattern based on the SHEM(Selective Harmonic Elimination Method) technique is determined from the look-up table to reduce the line current harmonics and a rotating fundamental frequency switching scheme is presented to adjust the DC voltage of each inverter capacitor at the same value. So the voltage unbalance problem between separately DC bus voltage is improved by using the proposed switching scheme. As a result, the presented inverter configuration not only reduces the system complexity by eliminating the isolation at the AC input side transformer but also improves the dynamic response to the step change of reactive power.

• Earthquakes and Structures
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• v.17 no.3
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• pp.271-282
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• 2019

Knowing the response of buildings to earthquakes is very important in order to ensure that a structure is able to withstand a given level of ground shaking. Thus, nonlinear dynamic earthquake engineering analyses are unavoidable and are preferable procedure in the seismic assessment of buildings. In order to estimate seismic performance on the basis of the hazard at the site where the structure is located, the selection of appropriate seismic input is known to be a critical step while performing this kind of analysis. In this paper, seismic analysis is performed for a four-story reinforced concrete ISPRA frame structure which is designed according to Eurocode 8 (EC8). A total of 90 different earthquake scenarios were selected, 30 for each of three target spectrums, EC8 spectrum, Uniform Hazard Spectrum (UHS), and Conditional Mean Spectrum (CMS). The aim of this analysis was to evaluate the average maximum Inter-story Drift Ratio (IDR) for each target spectrum. Time history analysis for every earthquake record was obtained and, as a result, IDR as the main measure of damage were presented in order to compare with defined performance levels of reinforced concrete bare frames.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.393-405
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• 2023

Accurate prediction of wind speed and power is vital for enhancing the efficiency of wind energy systems. Numerous solutions have been implemented to date, demonstrating their potential to improve forecasting. Among these, deep learning is perceived as a revolutionary approach in the field. However, despite their effectiveness, the noise present in the collected data remains a significant challenge. This noise has the potential to diminish the performance of these algorithms, leading to inaccurate predictions. In response to this, this study explores a novel feature engineering approach. This approach involves altering the data input shape in both Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) and Autoregressive models for various forecasting horizons. The results reveal substantial enhancements in model resilience against noise resulting from step increases in data. The approach could achieve an impressive 83% accuracy in predicting unseen data up to the 24th steps. Furthermore, this method consistently provides high accuracy for short, mid, and long-term forecasts, outperforming the performance of individual models. These findings pave the way for further research on noise reduction strategies at different forecasting horizons through shape-wise feature engineering.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.1
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• pp.61-70
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• 2024

In response to the continuously increasing demand for air travel, various studies are being conducted. This research focuses on the design of a simulation model for improving airport slot allocation in the strategic phase. It addresses three aspects of model design, introducing considerations such as the objective function. Additionally, it explains the conceptual procedures for the overall simulation operation and detailed processes within the model including input and output data. Emphasizing the SAL, this study excludes policy and qualitative judgments from its scope. The target airport for application will be confirmed in future research. This study marks a crucial first step toward optimizing air traffic flow, with expectations of contributing to the enhancement of operational efficiency at airports.

• International Journal of Automotive Technology
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• v.4 no.4
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• pp.181-191
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• 2003

Since the nonlinearity and uncertainties which inherently exist in vehicle system need to be considered in active suspension control law design, this paper proposes a new control strategy for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a genetic algorithm (GA) based self-tuning PID controller and a fuzzy logic controller in two loops. In the control scheme, the PID controller is used to minimize vehicle body vertical acceleration, the fuzzy logic controller is to minimize pitch acceleration and meanwhile to attenuate vehicle body vertical acceleration further by tuning weighting factors. In order to improve the adaptability to the changes of plant parameters, based on the defined objectives, a genetic algorithm is introduced to tune the parameters of PID controller, the scaling factors, the gain values and the membership functions of fuzzy logic controller on-line. Taking a four degree-of-freedom nonlinear vehicle model as example, the proposed control scheme is applied and the simulations are carried out in different road disturbance input conditions. Simulation results show that the present control scheme is very effective in reducing peak values of vehicle body accelerations, especially within the most sensitive frequency range of human response, and in attenuating the excessive dynamic tire load to enhance road holding performance. The stability and adaptability are also showed even when the system is subject to severe road conditions, such as a pothole, an obstacle or a step input. Compared with conventional passive suspensions and the active vehicle suspension systems by using, e.g., linear fuzzy logic control, the combined PID and fuzzy control without parameters self-tuning, the new proposed control system with GA-based self-learning ability can improve vehicle ride comfort performance significantly and offer better system robustness.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.6
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• pp.490-495
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• 2016

Pulsed eddy current (PEC) testing signals have typically been obtained from the electromotive force induced in a sensor coil. However, an increasing number of studies have elected to incorporate the Hall plate as a sensor. Thus, accurate numerical modeling of the Hall sensor signal is necessary. In this study, a PEC probe is designed and a numerical modeling program is written so that Hall sensor signals and coil sensor signals can be calculated simultaneously. First, a step current is used as the input current. The predicted Hall sensor signals show similar characteristics to those of the experimental signals reported by other researchers. The characteristics of the two types of signals are then analyzed and compared as the thickness of test object changes. The results show that the Hall sensor signal provides less information for evaluating the thickness of the test object than the coil sensor signal. The response signals from a pulsed input current are also calculated, and it is confirmed that an equivalent reversed signal pattern appeared after the pulse width at both signals.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.4
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• pp.393-401
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• 1995

In this paper, vector analysis on the novel quick torque control of Induction Motors(I.M) based on voltage-controlled type is conducted. It was very difficult to get a step response of torque when the primary voltage was selected as control input of induction motors in conventional quick torque control methods. To solve this problem, the new control method was developed using a new concept of pulse addition which can realize the stepwise torque response of a specified settling time of $\Delta$. The new method was successfully confirmed through DSP(Digital Signal Processor) system-based experiments. However, it was a little difficult to understand the control mechanism intutionally. The purpose of this paper is to provide more understanding about the quick torque control mechanism using the vector analysis.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1626-1637
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• 2020

This work covers an important point of the benchmark released by the expert group on Uncertainty Analysis in Modeling of Light Water Reactors. This ambitious benchmark aims to determine the uncertainty in light water reactors systems and processes in all stages of calculation, with emphasis on multi-physics (coupled) and multi-scale simulations. The Gesellschaft für Anlagen und Reaktorsicherheit methodology is used to propagate the thermal-hydraulic uncertainty of macroscopic parameters through TRACE5.0p3/PARCSv3.0 coupled code. The main innovative points achieved in this work are i) a new thermal-hydraulic model is developed with a highly-accurate 3D core discretization plus an iterative process is presented to adjust the 3D bypass flow, ii) a control rod insertion occurrence -which data is obtained from a real PWR test- is used as a transient simulation, iii) two approaches are used for the propagation process: maximum response where the uncertainty and sensitivity analysis is performed for the maximum absolute response and index dependent where the uncertainty and sensitivity analysis is performed at each time step, and iv) RESTING MATLAB code is developed to automate the model generation process and, then, propagate the thermal-hydraulic uncertainty. The input uncertainty information is found in related literature or, if not found, defined based on expert judgment. This paper, first, presents the Gesellschaft für Anlagen und Reaktorsicherheit methodology to propagate the uncertainty in thermal-hydraulic macroscopic parameters and, then, shows the results when the methodology is applied to a PWR reactor.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.585-594
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• 2007

The back propagation algorithm took a long time to learn the input patterns and was difficult to train the additional or repeated learning patterns. So Aleksander proposed the binary neural network which could overcome the disadvantages of BP Network. But it had the limitation of repeated learning and was impossible to extract a generalized pattern. In this paper, we proposed a dynamic 3 dimensional Neuro System which was consisted of a learning network which was based on weightless neural network and a feedback module which could accumulate the characteristic. The proposed system was enable to train additional and repeated patterns. Also it could be produced a generalized pattern by putting a proper threshold into each learning-net's discriminator which was resulted from learning procedures. And then we reused the generalized pattern to elevate the recognition rate. In the last processing step to decide right category, we used maximum response detector. We experimented using the MNIST database of NIST and got 99.3% of right recognition rate for training data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.619-628
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• 2010

Shape Memory Alloy (SMA) has recently received attention in developing implantable surgical equipments and it is expected to lead the future medical device market by adequately imitating surgeons' flexible and delicate hand movement. However, SMA actuators have not been used widely because of their nonlinear behavior called hysteresis, which makes their control difficult. Hence, we propose a parameter, $t_1$, which is necessary for temperature control, by analyzing the open-loop step response between current and temperature and by comparing it with the values of linear differential equations. $t_1$ is a pole of the transfer function in the invariant linear model in which the input and output are current and temperature, respectively; hence, $t_1$ is found to be related to the state variable used for temperature control. When considering the parameter under heat treatment conditions, $T_{max}$ was found to assume the lowest value, and $t_1$ was irrelevant to the heat treatment.