• Macromolecular Research
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• v.8 no.3
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• pp.103-115
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• 2000

The structural changes viewed from the molecular level have been investigated for the isothermal crystallization phenomena of polyethylene (PE) and the solvent-induced crystallization phenomenon of syndiotactic polystyrene (sPS) glassy sample. The data, which were collected by the time-resolved measurements of Fourier-transform infrared spectra, Raman spectra, synchrotron-sourced small-angle X-ray scattering, wide-angle X-ray scattering, and so on, were combined together to extract the detailed structural information in these phase transition phenomena. In the case of PE, the isothermal crystallization from the melt to the orthorhombic form was found to occur via the conformationally-disordered trans chain form, followed by the formation of the lamellar stacking structure of regular orthorhombic-type crystals. In the case of sPS, the amorphous chains in the glassy sample were found to enhance the mobility through the interaction with the injected solvent molecules, which act as a trigger to cause the conformational ordering from the random coil to the regular T$_2$G$_2$-type helical form. The thus created short helical segments were found to grow into longer helices, which gathered together to form the crystallites, as revealed by the organized coupling of the infrared, Raman and X-ray scattering data.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.27-39
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• 2016

This paper derives and analyzes a novel block fast Fourier transform (FFT) based joint detection algorithm. The paper compares the performance and complexity of the novel block-FFT based joint detector to that of the Cholesky based joint detector and single user detection algorithms. The novel algorithm can operate at chip rate sampling, as well as higher sampling rates. For the performance/complexity analysis, the time division duplex (TDD) mode of a wideband code division multiplex access (WCDMA) is considered. The results indicate that the performance of the fast FFT based joint detector is comparable to that of the Cholesky based joint detector, and much superior to that of single user detection algorithms. On the other hand, the complexity of the fast FFT based joint detector is significantly lower than that of the Cholesky based joint detector and less than that of the single user detection algorithms. For the Cholesky based joint detector, the approximate Cholesky decomposition is applied. Moreover, the novel method can also be applied to any generic multiple-input-multiple-output (MIMO) system.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2009.04a
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• pp.358-364
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• 2009

본 연구에서는 우리나라 주요 침엽수종인 소나무(Pinus densiflora)와 활엽수종인 굴참나무(Quercus variabilis)의 낙엽에 대해 FTIR(Fourier Transform Infrared) 분광계를 이용하여 배출 연소가스 종류 및 농도를 측정하였다. 실험결과 소나무와 굴참나무 낙엽에서 Carbon monoxide, Carbon dioxide, Acetic acid, Butyl acetate, Ethylene, Methane, Methanol, Nitrogen dioxide, Ammonia, Hydrogen Fluoride, Sulfur dioxide, Hydrogen bromide 등 13개 연소가스가 검출되었고 굴참나무 낙엽에서는 Nitrogen monoxide가 추가로 검출되었다. 방출된 연소가스의 전체 농도는 소나무 낙엽이 굴참나무 낙엽에 비해 4.5배 많이 검출되었다. 특히, 시간가중평균가스농도(TWA : Time-weighted average, ppm) 기준을 초과하는 연소가스는 Carbon monoxide, Carbon dioxide, Butyl acetate가 검출되었고 단시간노출기준(STEL : Short Term Exposure Limit, ppm) 기준을 초과하는 연소가스는 Carbon monoxide, Carbon dioxide로 소나무 및 굴참나무 모두에서 나타났다. 이에 산불에서의 낙엽층 지표화 연소시 전체 가스 방출량의 99% 이상을 차지하고 있는 Carbon monoxide, Carbon dioxide의 건강 위험성이 높은 것으로 나타났다. 하지만, 검출된 다른 건강 위험성 가스의 경우에도 연소물질의 양이 증가할수록 연소가스의 농도가 높아져 건강안정성에 해가 있을 것으로 판단되며 또한 검출된 연소가스 중 나무의 주요구성 원소가 아닌 Bromide, Fluoride 화합물에 대해서는 토양으로부터의 오염 또는 분석과정에서의 노이즈로 인한 검출 등에 대한 보다 면밀한 검토가 필요할 것으로 판단된다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.5
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• pp.765-771
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• 2001

Elastic-plastic fracture toughness JIC can be used a s an effective design criterion in elastic-plastic fracture mechanics. Among the JIC test methods approved by ASTM, unloading compliance method was used in this study. In order to examine the relationship between fracture behavior of JIC test and AE signals, the post processing of AE signals has been carried out by Short Time Fourier Transform(STFT), one of the time-frequency analysis methods. The objective of this study is to evaluate the application of characterization of AE signals for unloading compliance method of JIC test. As a result of time-frequency analysis, we could extract the AE from the raw signal and analyze the frequencies in AE signal at the same time. AE signal generated by elastic-plastic fracture of material has some different aspects at elastic and plastic ranges, or the first portion of crack growth by fracture. First of all, increased energy recorded and detected by using AE count method increase rapidly from the start of ductile fracture. The variation of main frequency range with time-frequency analysis method could be confirmed. We could know fracture behavior of interior material by examination AE characteristics generated in real-time when elastic-plastic fracture occurred in material under loading.

• Composites Research
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• v.18 no.6
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• pp.26-33
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• 2005

The mechanical properties of composite materials may severely degrade in the presence of damage. Especially, the high-velocity impact such as bird strike, a hailstorm, and a small piece of tire or stone during high taxing, can cause considerable damage to the structures and sub-system in spite of a very small mass. However, it is not easy to detect the damage in composite plates using a single technique or any conventional methods. In this paper, the PVDF(polyvinylidene fluoride) film sensors were used for monitoring high-velocity impact damage initiation and propagation in composite laminates. The WT(wavelet transform) and STFT(short time Fourier transform) are used to decompose the sensor signals. A ultrasonic C-scan and a digital microscope are also used to examine the extent of the damage in each case. This research shows how various sensing techniques, PVDF sensor in particular, can be used to characterize high-velocity impact damage in advanced composite.

• Smart Structures and Systems
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• v.13 no.2
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• pp.177-201
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• 2014

With the increased size and flexibility of the tower and blades, structural vibrations are becoming a limiting factor towards the design of even larger and more powerful wind turbines. Research into the use of vibration mitigation devices in the turbine tower has been carried out but the use of dampers in the blades has yet to be investigated in detail. Mitigating vibrations will increase the design life and hence economic viability of the turbine blades and allow for continual operation with decreased downtime. The aim of this paper is to investigate the effectiveness of Semi-Active Tuned Mass Dampers (STMDs) in reducing the edgewise vibrations in the turbine blades. A frequency tracking algorithm based on the Short Time Fourier Transform (STFT) technique is used to tune the damper. A theoretical model has been developed to capture the dynamic behaviour of the blades including the coupling with the tower to accurately model the dynamics of the entire turbine structure. The resulting model consists of time dependent equations of motion and negative damping terms due to the coupling present in the system. The performances of the STMDs based vibration controller have been tested under different loading and operating conditions. Numerical analysis has shown that variation in certain parameters of the system, along with the time varying nature of the system matrices has led to the need for STMDs to allow for real-time tuning to the resonant frequencies of the system.

• Smart Structures and Systems
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• v.13 no.2
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• pp.203-217
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• 2014

Due to the shift in paradigm from passive control to adaptive control, smart tuned mass dampers (STMDs) have received considerable attention for vibration control in tall buildings and bridges. STMDs are superior to tuned mass dampers (TMDs) in reducing the response of the primary structure. Unlike TMDs, STMDs are capable of accommodating the changes in primary structure properties, due to damage or deterioration, by tuning in real time based on a local feedback. In this paper, a novel adaptive-length pendulum (ALP) damper is developed and experimentally verified. Length of the pendulum is adjusted in real time using a shape memory alloy (SMA) wire actuator. This can be achieved in two ways i) by changing the amount of current in the SMA wire actuator or ii) by changing the effective length of current carrying SMA wire. Using an instantaneous frequency tracking algorithm, the dominant frequency of the structure can be tracked from a local feedback signal, then the length of pendulum is adjusted to match the dominant frequency. Effectiveness of the proposed ALP-STMD mechanism, combined with the STFT frequency tracking control algorithm, is verified experimentally on a prototype two-storey shear frame. It has been observed through experimental studies that the ALP-STMD absorbs most of the input energy associated in the vicinity of tuned frequency of the pendulum damper. The reduction of storey displacements up to 80 % when subjected to forced excitation (harmonic and chirp-signal) and a faster decay rate during free vibration is observed in the experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2187-2193
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• 2010

A specific radar system can be implemented more easily using the frequency modulated continuous wave comparing with the pulse Doppler radar. It also has the advantage of LPI (low probability of interception) because of the low power and wide bandwidth characteristics. These radars are usually used to cover the short range area and to obtain the high resolution measurements of the target range and velocity information. The transmitted waveform is used in the mixer to demodulate the received echo signal and the resulting beat signal can be obtained. This beat signal is analyzed using the FFT method for the purpose of clutter removal, detection of a target, extraction of velocity and range information, etc. However, for the case of short signal acquisition time, this FFT method can cause the serious leakage effect which disables the detection of weaker echo signals masked by strong side lobes of the clutter. Therefore, in this paper, the weighting window method is analyzed to suppress the strong side lobes while maintaining the proper main lobe width. Also, the results of FFT beat spectrum analysis are shown under various environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1752-1758
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• 2010

A FM-CW radar is used for the various purposes as a remote sensing device since it has the advantages of the relatively simple implementation and the low probability of signal interception. A FM-CW radar uses the same frequency modulated continuous wave for both transmission and demodulation. Therefore, the received beat frequency represents the range and Doppler information of targets. However, using the conventional FFT method, the degree of accuracy and resolution in the spectrum estimation can be seriously degraded in the detection and tracking of fast moving targets because of the short dwell time. Therefore, in this paper, the model parameter estimation methods called as an autoregressive method is applied to overcome these problems and showed that the improved accuracy and resolution can be obtained for the target range and velocity estimation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.315-321
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• 2023

Long-span bridges are flexible structures with low natural frequencies and damping ratios, making them susceptible to vibrational serviceability problems. However, the current design guideline of South Korea assumes a uniform threshold of wind speed or vibrational amplitude to assess the occurrence of harmful vibrations, potentially overlooking the complex vibrational patterns observed in long-span bridges. In this study, we propose a pointwise vortex-induced vibration (VIV) detection method using a deep-learning-based signalsegmentation model. Departing from conventional supervised methods of data acquisition and manual labeling, we synthesize training data by generating sinusoidal waves with an envelope to accurately represent VIV. A Fourier synchrosqueezed transform is leveraged to extract time-frequency features, which serve as input data for training a bidirectional long short-term memory model. The effectiveness of the model trained on synthetic VIV data is demonstrated through a comparison with its counterpart trained on manually labeled real datasets from an actual cable-supported bridge.