• Composites Research
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• v.14 no.2
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• pp.50-59
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• 2001

The predictions of residual strength evolution and fatigue life of full scale composite rotor blade for multipurpose helicopter were studied using a strength degradation model. Flight-by-flight load spectrum was developed on the basis of FELIX standard spectrum data. The laminated structural analysis was also performed to obtain corresponding local stress and/or strain spectra for each ply of laminate skin and glass roving spar structures around the blade root where fatigue damage was severely anticipated.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.11a
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• pp.238-244
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• 2000

FBGs have been extensively used as strain sensors or temperature sensors in a variety of applications related to composites because of embedding ability, small size and multiplexing capability. We inspected embedding environments inside composites with optical fiber by microscope analysis and birefringence characteristics of FBG embedded into textile composite laminate by cure monitoring using a high power WSFL. The cure monitoring of the cases with the striped FBG and the recoated FBG provided comprehensive understandings about the birefringence effect induced by the transverse stress. And these results allowed to consider a recoating method as an important tool to relieve birefringence.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.75-78
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• 2002

A simplified methodology is presented to predict fatigue life and residual strength of composite structures. To avoid excessive amount of tests that are required for model characterization, strength degradation parameter is assumed as function of fatigue life. S-N curve is used to extract fatigue life that is required to characterize the stress levels comprising a randomly-ordered load spectrum. And different stress ratios are handled with Goodman correction approach(fatigue envelope). It is assumed that the residual strength is a function of the number of loading cycles and applied fatigue stress amplitude. And the residual strength distribution after an arbitrary load cycles is represented by two parameter Weibull functions.

• Composites Research
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• v.16 no.1
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• pp.13-18
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• 2003

Prediction of composite fatigue life is not a straightforward matter, depending on various failure modes and their interactions. In this paper, a methodology is presented to predict fatigue life and residual strength of composite materials based on Phenomenological Model(non-linear fatigue damage model). It is assumed that the residual strength is a monotonically decreasing function of the number of loading cycles and applied fatigue stress ratio and the model parameters(strength degradation parameter and fatigue shape parameter) are assumed as function of fatigue life. Then S-N curve is used to extract model parameters that are required to characterize the stress levels comprising a randomly-ordered load spectrum. Different stress ratios (${\sigma}_{min}/{\;}{\sigma}_{max}$) are handled with Goodman correction approach(fatigue envelope) and the residual strength after an arbitrary load cycles is represented by two parameter weibull functions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4C
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• pp.232-240
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• 2011

While the water-filling algorithm is an efficient power allocation method that maximizes the ergodic capacity of adaptive MIMO systems, its excessive residual power causes spectrum loss in real systems employing discrete modulation indices. In this paper we propose new power allocation algorithms that improve the spectral efficiency of MIMO systems by efficiently reallocating the residual power of the water-filling algorithm. We apply the proposed algorithms to the adaptive turbo-coded MIMO system to verify their performance through computer simulation in various environments. Simulation results show that the spectral efficiency of the proposed algorithms is better than that of the water-filling algorithm by about 8.9% at SNR of 20dB in Rayleigh fading environments.

• Journal of the Korean Ceramic Society
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• v.40 no.8
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• pp.770-776
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• 2003

#140 mesh and #600 mesh wheels were adopted to grind (111) and (100) oriented single crystalline silicon wafer and the grinding induced change of the surface integrity was investigated. For this purpose, microroughness, residual stress and phase transformation were analyzed for the ground surface. Microroughness was analyzed using AFM (Atomic Force Microscope) and crystal structure was analyzed using micro-Raman spectroscopy. The residual stress and phase transformation were also analyzed after thermal annealing in the air. As a result, microroughness of (111) wafer was larger than that of (100) wafer after grinding. It was observed using Raman spectrum that the silicon was transformed from diamond cubic Si-I to Si-III(body centered tetragonal) or Si-XII(rhombohedral). Residual stress relaxation was also shown in cavities which were produced after grinding. The thermal annealing was effective for the recovery of the silicon phase to the original phase and the residual stress relaxation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.11
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• pp.1056-1063
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• 2007

Recently, there has been a growing consumer interest in the amount of noise produced by household electrical appliances. The designer of the product must identify the source of the noise, in order to reduce the noise. In the case of a household electric appliance such as the washing machine, there is consumer's complaint about the noise that is generated during the dehydrating condition. Because of several noise sources combined each other. It is difficult to identify the noise sources that contribute to the noise output. Multi-Dimensional Spectral Analysis (MDSA) is a method that can remove the correlation between different noise sources, and it expresses the key contributing factor as a unique output. This study utilized MDSA to analyze the contribution of each input in the noise output during the dehydrating condition.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.3199-3209
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• 2024

During the decommissioning of nuclear and particle accelerator facilities, a considerable amount of large-scale radioactive waste may be generated. Accurately defining the activation level of the waste is crucial for proper disposal. However, directly measuring the internal radioactivity distribution poses challenges. This study introduced a novel technology employing machine learning to assess the internal radioactivity distribution based on external measurements. Random radioactivity distribution within a structure were established, and the photon spectrum measured by detectors from outside the structure was simulated using the FLUKA Monte-Carlo code. Through training with spectrum data corresponding to various radioactivity distributions, an evaluation model for radioactivity using simulated data was developed by above Monte-Carlo simulation. Convolutional Neural Network and Transformer methods were utilized to establish the evaluation model. The machine learning construction involves 5425 simulation datasets, and 603 datasets, which were used to obtain the evaluated results. Preprocessing was applied to the datasets, but the evaluation model using raw spectrum data showed the best evaluation results. The estimation of the intensity and shape of the radioactivity distribution inside the structure was achieved with a relative error of 10%. Additionally, the evaluation based on the constructed model takes only a few seconds to complete the process.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.233-238
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• 2005

In general CELP(Code Excited Linear Prediction) type vocoders provide good speech qualify around 4.8kbps. Among them, G.723.1 developed for Internet Phone and video-conferencing includes two vocoders, 5.3kbps ACELP(Algebraic-CELP) and 6.3kbps MP-MLQ(Multi-Pulse Maximum Likelihood Quantization) In order to improve the speech qualify in CELP vocoder, in this paper. we proposed a new spectrum analysis algorithm with variable window In CELP vocoder, the spectrum of the synthesised speech signal is distorted because the fixed size windows is used for spectrum analysis. So we have measured the spectral leakage and in order to minimize the spectral leakage have adjusted the window size. Applying this method G.723.1 ACELP, we can got SD(Spectral Distortion) reduction 0.084(dB), residual energy reduction 6.3$\%$ and MOS(Mean Opinion Score) improvement 0.1.

• Journal of Food Hygiene and Safety
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• v.8 no.1
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• pp.9-15
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• 1993

In an attempt to quantitate and qualitate residual antibiotics and antibacterial agents in meat simultaneously, we studied a gas chromatography-mass spectrometry(GC/M8) analysis. For a simultaneous analysis of penicillin G, chloramphenicol and thiamphenicol in meat, a simple and rapid clean-up procedure including extraction with 0.01 M EDTA-2Na Mcilvaine buffer (pH 4.0), defatting with n-hexane, and elution with 0.01M-methanolic oxalic acid from Bond Elute $C_{18}$ cartridge, and quantitation by selected ion monitoring (SIM) mode after derivatization was performed. The recoveries (%) of penicillin G, chloramphenicol and thiamphenicol (CV, %) at 1 ppm fortification level were 63.5 (7.6), 76.3 (8.1) and 84.7 (2.0), and the detection limits of those were 0.6, 0.085 and $0.084\;\mu\textrm{g}$ beef, respectively. This method using 81M mode allows excellent detection and quantitation of residual antibiotics and antibacterial agents in meat. Moreover, confirmation by a full scan electron impact mass spectrum is possible if residual level in the sample in above 1 ppm.