• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.4
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• pp.165-170
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• 2005

A series of inorganic-organic hybrid membranes were prepared with a systematic variation of titanium dioxide nanoparticle content. Their water uptake, methanol permeability and proton conductivity as a function of temperature were investigated. The results obtained show that the inorganic oxide network decreases the proton conductivity and water swelling. It is also found that increase in inorganic oxide content leads to decrease of methanol permeability. In terms of the morphology, membranes are homogeneous and exhibit good adhesion between inorganic domains and the polymer matrix. The properties of the composite membranes are compared with the standard nafion membrane.

• Journal of the Korean Society of Costume
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• v.57 no.8
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• pp.114-124
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• 2007

Contemporary fashion design has been represented as intermedia transcended value and spatiotemporal notion and also had a tendency to concentrate on serial process that materials are transfigured through time rather than existence. These forms related to interaction with time, space and performance as well as compositive genres, hybrid culture, compound gender define as 'serial expression' in this study. The serial expression ran be characterized that system, process, series, enumeration of sequences, depiction of performance, repetition of action in fashion collections and exhibitions of designers. The concept and circumstances made by author as a creator of fashion broaden perceptions of audiences and arouse spectators to participate in the situation as needing immediate attention. The forms of fashion and Conceptual Art in serial expression are analogous and even identical situations represent in fashion collection. Therefore analysis serial forms of art derives formative features: Narrative process, Imitation and Appropriation, Virtual reality and High technology, Hybridism and Convergence. This study suggest a framework to analyze conceptual fashion that give salience to megatrend in contemporary fashion culture on artistic point of view.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.6_spc
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• pp.687-696
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• 2016

A series of process to design an acoustic lens for underwater imaging is reviewed and the method to evaluate characteristics of the lens is investigated. If the target specification of lens is given, the design process consists of the material selection, evaluation of its properties, lens geometry design, prediction of lens characteristics, manufacturing, and evaluation by measurement. In this study, an actual acoustical lens is made by cutting polymethylpentene block. The characteristics of lens are predicted by the hybrid method, combination of ray tracing and Rayleigh integral. For the direct comparison between the prediction and measurement results, a simulation method based on the equivalent source method is suggested to reflect the actual radiation pattern of transducer used for measurements. Finally, the measurement is conducted in a small water tank to observe the actual characteristics of the manufactured lens.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.127-136
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• 2005

In this paper, a new architecture and comprehensive design methodology of genetically optimized Rule-based Fuzzy Polynomial Neural Networks(gRFPNN) are introduced and a series of numeric experiments are carried out. The architecture of the resulting gRFPNN results from asynergistic usage of the hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks (PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the gRFPNN. The consequence part of the gRFPNN is designed using PNNs. At the premise part of the gRFPNN, FNN exploits fuzzy set based approach designed by using space partitioning in terms of individual variables and comes in two fuzzy inference forms: simplified and linear. As the consequence part of the gRFPNN, the development of the genetically optimized PNN dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gRFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed gRFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.6
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• pp.408-414
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• 2018

Given that lithium-ion batteries are expected to be used as power sources for electric and hybrid vehicles, thermodynamics experimentation and prediction based on experimental data were performed. Thermal, electrochemical, and electrochemical/electrical-thermal models were used for accurate battery modeling. Various applications of different battery packs were demonstrated, and thermal analysis was performed using the same experimental conditions for square and rectangular battery packs. Accurate thermal analysis for a single cell should be prioritized to determine the thermal behavior of the battery pack. The energy balance equation, which contains heat generation and heat transfer factors, defines the thermal behavior of the battery pack. By comparing battery packs of different shapes tested under the same condition, this study revealed that the rectangular battery pack is superior to the square battery pack in terms of the maximum temperature of inner cells and temperature variation between cells.

• Journal of the Korean institute of surface engineering
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• v.52 no.3
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• pp.123-129
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• 2019

With recent demand for the renewable energy resources, we conducted a research on the energy conversion and storage device of supercapacitor. The hybrid graphene-zinc oxide(GZO) electrodes for the supercapacitors (SCs) were fabricated and investigated. To increase the electrical conductivity of the GZO electrode, the rapid thermal annealing(RTA) in $Ar/H_2$(10%) atmosphere was applied and the effect was examined by comparing it with RTA at Ar atmosphere. In Raman spectroscopy, the electrodes annealed at 400? in $Ar/H_2$ atmosphere showed a lower ratio of D/G peak than that of annealed at Ar atmosphere, and had a larger specific capacitance(Sc) in the cyclic voltammetry(CV), and a lower the equivalent series resistance(ESR) in the electrochemical impedance spectroscopy(EIS). The reason seems to come from the better mixing of the graphene and zinc oxide by the RTA in $Ar/H_2$(10%).

• New & Renewable Energy
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• v.17 no.3
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• pp.1-7
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• 2021

The Korean government announced various energy policies, such as the to reduce 37% of the business-as-usual (BAU) greenhouse gas emissions by 2030. The policies aim to increase the renewable electricity generation ratio to 20% by 2030. PVT is a hybrid technology, which combines photovoltaic (PV) and solar collectors. It is capable of generating electricity and thermal energy simultaneously. It has a great potential to be used as a renewable and clean solar energy. However, there exists a shortage of space for the installation of PVT systems in Korea. To overcome this, in this paper proposes four types of soundproof wall PVT air channels, which were designed and optimized, based on the CFD (Computation Fluid Dynamic) analysis results. The thermal energy generation for multiple PVT units connected in series and pressure drop sensitivity were analyzed, depending on inlet velocity.

• Earthquakes and Structures
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• v.25 no.5
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• pp.343-358
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• 2023

The superelastic viscous damper (SVD) is a hybrid passive control device comprising a viscoelastic damper and shape memory alloy (SMA) cables connected in series. The SVD is an innovative damper through which a large amount of seismic energy can dissipate. The current study assessed the seismic collapse induced by steel moment-resisting frames (SMRFs) equipped with SVDs and compared them with the performance of special MRFs and buckling restrained brace frames (BRBFs). For this purpose, nonlinear dynamic and incremental dynamic analysis (IDA) were conducted in OpenSees software. Both 5- and 9-story special MRFs, BRBFs, and MRFs equipped with the SVDs were examined. The results indicated that the annual exceedance rate for maximum residual drifts of 0.2% and 0.5% for the BRBFs and MRFs with SVDs, respectively, were considerably less than for SMRFs with reduced-beam section (RBS) connections and that the seismic performances of these structures were enhanced with the use of the BRB and SVD. The probability of collapse due to residual drift in the SVD, BRB, and RBS frames in the 9-story structure was 1.45, 1.75, and 1.05 times greater than for the 5-story frame.

• Structural Monitoring and Maintenance
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• v.10 no.3
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• pp.261-281
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• 2023

Magnetic flux sensors are commonly used in monitoring the cable force, but the application of the sensors in large diameter non-closed Galfan cables, as those adopted in Yueqing Gymnasium which is located in Yueqing City, Zhejiang Province, China and is the largest span hybrid space structure in the world, is seldom done in engineering. Based on the construction of Yueqing Gymnasium, this paper studies the cable tension monitoring using the magnetic flux method across two stages, namely, the pre-calibration stage before the cable leaves the rigging factory and the field tension formation stage of the cable system. In the pre-calibration stage in the cable factory, a series of 1:1 full-scale comparative tests were carried out to study the feasibility and relability of this kind of monitoring method, and the influence on the monitoring results of charging and discharging voltage, sensor location, cable diameter and fitting method were also studied. Some meaningful conclusions were obtained. On this basis, the real-time cable tension monitoring system of the structure based on the magnetic flux method is established. During the construction process, the monitoring results of the cables are in good agreement with the data of the on-site pressure gauge.The work of this paper will provide a useful reference for cable force monitoring in the construction process of long-span spatial structures.

• 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.