• 한국광학회지
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• 제23권6호
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• pp.246-250
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• 2012

We derive analytical expressions for the output spectral density and the noise power $P_{\beta}$ in noise loading analysis using Volterra kernels to characterize fiber nonlinearities. The bandwidth of the input noise source has little effect on $P_{\beta}$, but the power of the input noise source and the dispersion parameter value of the fiber have a significant effect on $P_{\beta}$. The Volterra method predicts ${\Delta}P_{\beta}[dB]$ = 30 dB/decade, which agrees very accurately over a wide range of fiber parameters compared with the numerical results by the split-step Fourier method. Therefore the Volterra method could be useful to predict the performance of a dense WDM system when we plan to upgrade fiber or increase signal power.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2000년도 춘계학술발표대회 논문집
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• pp.97-100
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• 2000

A FEA(finite element analysis) model was proposed to study stress and strain distributions in thick composites with various types of fiber waviness under tensile and compressive loadings. Three types of model were considered in this study: uniform fiber waviness, graded fiber waviness and localized fiber waviness models. In the analysis, both material and geometrical nonlinearities due to fiber waviness were incorporated into the model utilizing energy density and incremental method. The strain distributions of uniform fiber waviness model were strongly influenced whereas the stress distributions were little influenced by fiber waviness. The stress and strain distributions of graded and localized fiber waviness models showed more complex distributions than those of uniform fiber waviness model due to the variation of fiber waviness along the thickness and length directions. It was concluded that the stress and strain distributions of composites with fiber waviness were significantly affected by types of fiber waviness.

• Journal of the Optical Society of Korea
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• 제17권4호
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• pp.312-316
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• 2013

A novel fiber-optic sensor system is suggested in which fiber Bragg grating sensors are demodulated by a wavelength-sweeping fiber laser source and a spectrometer. The spectrometer consists of a diffraction grating and a 512-pixel photo-diode array. The reflected Bragg wavelength information is transformed into spatial intensity distribution on the photo-diode array. The peak locations linearly correspond to the Bragg wavelengths, regardless of the nonlinearities in the wavelength tuning mechanism of the fiber laser. The high power density of the fiber laser enables obtaining high signal-to-noise ratio outputs. The improved demodulation characteristics were experimentally demonstrated with a fiber Bragg grating sensor array with 5 gratings. The sensor outputs were in much more linear fashion compared with the conventional tunable band-pass filter demodulation. Also it showed advantages in signal processing, due to the high level of photo-diode array signals, over the broadband light source system, especially in measurement of fast varying dynamic physical quantities.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2001년도 추계학술발표대회 논문집
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• pp.129-132
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• 2001

Fiber waviness is one of manufacturing defects encountered frequently in thick composite structures. It affects significantly on the behavior as well as strength of thick composites. The effects of fiber waviness on tensile/compressive nonlinear elastic behavior and strength of thick composite with fiber waviness are studied theoretically and experimentally. FEA(Finite Element Analysis) models are proposed to predict tensile/compressive nonlinear behavior and strength of thick composites. In the FEA models, both material and geometric nonlinearities were incorporated into the model using energy density, iterative mapping and incremental method. Also Tsai-Wu criteria was adopted to predict the strength of thick composites with fiber waviness. Tensile and compressive tests were conducted on the specimens with uniform fiber waviness. It was observed that the degree of fiber waviness in composites significantly affected the nonlinear behavior and strength of the composites

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.819-822
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• 2001

Fiber waviness is one of manufacturing defects encountered frequently in thick composite structures. It affects significantly on the behavior as well as strength of thick composites. Thick composites with fiber waviness have two kinds of nonliearity. One is material nonlinearity, and the other is geometrical nonliearity due to fiber waviness. There are only a few studies that have considered both material and geometrical nonlinearities. In this paper, a FEA model was proposed to predict nonlinear behavior and strength of thick composites with fiber waviness.

• Journal of the Optical Society of Korea
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• 제8권2호
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• pp.59-64
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• 2004

The response of a single-mode fiber to a sinusoidally modulated input has been studied to see its utility in measuring system performance in the presence of fiber nonlinearities. The sinusoidally modulated signal models an alternating bit sequence of ones and zeros in on-off keying. The sinusoidal response of normally dispersive fiber shows a strong correlation with eye-opening penalty (EOP) over a wide range of the nonlinearity parameter N (0.1 ＜ N$^2$＜ 100). This result implies that the measurement of the sinusoidal response can be an alternate way of measuring EOP without having a long sequence of randomly modulated input bits. But in the anomalous dispersion region, the sinusoidal response has a much more limited range of application to estimate system performance.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 1999년도 추계학술발표대회 논문집
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• pp.95-100
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• 1999

A FEA(finite element analysis model) was proposed to study stress and strain distributions in thick composites with fiber waviness and initial curvature under flexural loading. Three types of model with initial curvature were considered in this study: flat, concave and concave models. In the analysis, both material and geometrical nonlinearities were incorporated. Four point flexural tests were conducted on the flat specimens to obtain the flexural behavior of thick composites experimentally. It was concluded that the predictions from the models were in good agreement with the experimental results. It was shown that the stress and strain distributions as well as nonlinear flexural behaviors of thick composites were significantly affected by the fiber waviness and initial curvature.

• 대한전자공학회논문지TC
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• 제41권12호
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• pp.23-32
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• 2004

본 논문에서는 SSB 변조를 이용한 광전송 시스템의 주파수 효율성 및 비선형성에 대한 저항성 등을 규명하였다. 이상적인 SSB 신호를 사용하여 도달할 수 있는 성능의 한계를 확인하는 한편, 실제 제작이 가능한 SSB 변조기가 생성할 수 있는 신호에서 얻을 수 있는 성능을 컴퓨터 시뮬레이션을 통하여 살펴보았다. 이를 통해 SSB 변조된 신호는 일반적으로 DSB 변조된 신호에 비해서 광섬유의 비선형성에 취약하나 본 연구에서 목표로 삼고 있는 전송거리가 500～1000 km 미만인 12.5 GHz 채널 간격의 WDM 시스템에서는 SSB 신호가 DSB 신호에 비해 우수한 성능을 보일 수 있음을 확인하였다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 가을 학술발표회 논문집
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• pp.281-287
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• 2004

In this paper, the refined plastic-hinge analysis accounting for gradual yielding with fibers on a section is developed. Geometric nonlinearities of member(P-δ) and frame(P-Δ) are accounted for by using stability functions. Residual stresses are considered by assigning initial stresses to the fiber on the section. The elastic core in a section is investigated at every loading step to determine the axial and bending stiffness reduction. The strain reversal effect is captured by investigating the stress change of each fiber. The proposed analysis proves to be useful in applying for practical analysis and design of three-dimensional steel frames.

• Journal of information and communication convergence engineering
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• 제16권1호
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• pp.1-5
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• 2018

In radio-over-fiber (RoF) systems, nonlinear compensation is very important to meet the error vector magnitude (EVM) requirement of the mobile network standards. In this study, a nonlinear compensation technique based on an artificial neural network (ANN) is proposed for RoF systems. This technique is based on a backpropagation neural network (BPNN) with one hidden layer and three neuron units in this study. The BPNN obtains the inverse response of the system to compensate for nonlinearities. The EVM of the signal is measured by changing the number of neurons and the hidden layers in a RoF system modeled by a measured data. Based on our simulation results, it is concluded that one hidden layer and three neuron units are adequate for the RoF system. Our results showed that the EVMs were improved from 4.027% to 2.605% by using the proposed ANN compensator.