• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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• pp.99-109
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• 1999

This paper is concerned with instability of flow fields which are dominated by the entropy mode with the presence of usual acoustic and vortical modes. These combined modes lead to nonlinear unstable waves which may occur in automobile, aircraft, or rocket engines. In this study instability in a side-burning rocket is investigated. It is shown that the energy growth rate parameters increase with an increase of the energy growth factor. The energy growth rate parameters for turbulent flows are larger than those for laminar flows. It is further shown that unstable wave motions for the high-temperature side-burning rocket are dictated mostly by the entropy mode, somewhat by the vortical mode, and least by the acoustic mode.

• Korean Journal of Materials Research
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• v.21 no.11
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• pp.623-627
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• 2011

This is a study on the distribution of acoustic emission parameters during a burst test for a type-II CNG vehicle fuel tank. A resonant AE sensor with a central frequency of 150 kHz was attached to the composite materials in the center of the fuel tank. The pressure was increased from 30 to 100% of the expected burst pressure and was maintained for 10 minutes at each level. Damage at 70% of expected burst pressure occurred by various damage mechanisms including fiber breakage and delamination, while that of below 60% only occurred by matrix crack initiation and growth. The count, duration and rise time of the AE signal at 60% of the expected burst pressure are distributed below 500, 5000 ${\mu}s$ and 300 ${\mu}s$, respectively. Then, at above 70% they increased with pressure by superimposing of individual AE signal generated at a nearby place. These results confirmed that the analysis of the distribution of AE parameters is an effective tool for estimating damage of a CNG fuel tank.

• Smart Structures and Systems
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• v.18 no.3
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• pp.525-540
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• 2016

The CFRP-confined circular concrete-filled steel tubular column is composed of concrete, steel, and CFRP. Its failure mechanics are complex. The most important difficulties are lack of an available method to establish a relationship between a specific damage mechanism and its acoustic emission (AE) characteristic parameter. In this study, AE technique was used to monitor the evolution of damage in CFRP-confined circular concrete-filled steel tubular columns. A fuzzy c-means method was developed to determine the relationship between the AE signal and failure mechanisms. Cluster analysis results indicate that the main AE sources include five types: matrix cracking, debonding, fiber fracture, steel buckling, and concrete crushing. This technology can not only totally separate five types of damage sources, but also make it easier to judge the damage evolution process. Furthermore, typical damage waveforms were analyzed through wavelet analysis based on the cluster results, and the damage modes were determined according to the frequency distribution of AE signals.

• Smart Structures and Systems
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• v.16 no.1
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• pp.67-79
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• 2015

Acoustic emission analysis is an effective technique for monitoring the evolution of damage in a structure. An experimental analysis on a set of reinforced concrete beams under flexural loading was carried out. A mixed AE analysis method which used both parameter-based and signal-based techniques was presented to characterize and identify different failure mechanisms of damage, where the signal-based analysis was performed by using the Hilbert-Huang transform. The maximum instantaneous energy of typical damage events and the corresponding frequency characteristics were established, which provided a quantitative assessment of reinforced concrete beam using AE technique. In the bending tests, a "pitch-catch" system was mounted on a steel bar to assess bonding state of the steel bar in concrete. To better understand the AE behavior of bond-slip damage between steel bar and concrete, a special bond-slip test called pullout test was also performed. The results provided the basis of quantitative AE to identify both failure mechanisms and level of damages of civil engineering structures.

• Journal of the Korean earth science society
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• v.40 no.4
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• pp.428-435
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• 2019

In the shallow coastal area, located off the northwestern Taean Peninsula of the eastern Yellow Sea, geoacoustic models with two layers were reconstructed for underwater acoustic experimentation and modeling. The Yellow Sea experienced glacio-eustasy sea-level fluctuations during Quaternary period. Coastal sedimentation in the Yellow Sea was characterized by alternating terrestrial and shallow marine deposits that reflected the fluctuating sea levels. The coastal geoacoustic models were based on data from piston, grab cores and the high-resolution 3.5 kHz, chirp seismic profiles (about 70 line-kilometers, respectively). Geoacoustic data of the cores were extrapolated down to 3 m in depth for geoacoustic models. The geoacoustic property of seafloor sediments is considered a key parameter for modeling underwater acoustic environments. For simulating actual underwater environments, the P-wave speed of the models was adjusted to in-situ depth below the sea floor using the Hamilton method. The proposed geoacoustic models could be used for submarine acoustic inversion and modeling in shallow-water environments of the study area.

• ETRI Journal
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• v.41 no.2
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• pp.235-241
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• 2019

In this paper, we propose a rank-weighted reconstruction feature to improve the robustness of a feed-forward deep neural network (FFDNN)-based acoustic model. In the FFDNN-based acoustic model, an input feature is constructed by vectorizing a submatrix that is created by slicing the feature vectors of frames within a context window. In this type of feature construction, the appropriate context window size is important because it determines the amount of trivial or discriminative information, such as redundancy, or temporal context of the input features. However, we ascertained whether a single parameter is sufficiently able to control the quantity of information. Therefore, we investigated the input feature construction from the perspectives of rank and nullity, and proposed a rank-weighted reconstruction feature herein, that allows for the retention of speech information components and the reduction in trivial components. The proposed method was evaluated in the TIMIT phone recognition and Wall Street Journal (WSJ) domains. The proposed method reduced the phone error rate of the TIMIT domain from 18.4% to 18.0%, and the word error rate of the WSJ domain from 4.70% to 4.43%.

• Journal of the Korean Society of Safety
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• v.38 no.2
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• pp.36-43
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• 2023

In this study, a four-point bending test was conducted to assess and detect the damage to reinforced concrete structures using the acoustic emission (AE) technique. Based on the crack investigation results, flexural failure was classified into four stages and compared with the characteristic analysis results of AE parameters. The parametric characterization indicated that the activity of the primary AE signal was high in the early stage, and that of the second signal increased after the flexural cracks stabilized. Because the secondary AE signal included noise generated by friction, parameter-based analysis for damage assessment was performed using the primary signal; the secondary signal was used as complement. The activity analyses of the primary and secondary signals effectively classified crack propagation; however, determining the macrocracks and yielding of reinforcing bars had certain limitations. Nevertheless, applying the damage index with cumulative AE energy is a complementary technique for detecting and assessing structure damage that well detects the occurrence of macrocracks.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.22 no.2
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• pp.143-150
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• 2011

Background and Objectives : Clinically, as a tool for voice assessment before and after the operation or the voice treatment, acoustic analysis is widely used. However, in clinical situations, acoustic parameters vary according to how the assessment is made. Thus, with voice disease patients as subjects, we are to investigate what influence intensity increase exerts on acoustic parameters and how to reduce variation according to the way of assessing. Material and Method : At the voice clinic of the department of otorhinolaryngology in Gangnam Severance Hospital, with 30 female voice-disease patients (40.6 years old on the average) and 23 male voice-disease patients (40.1 years old on the average) as subjects, using the Dr Speech vocal-assessment program, we statistically tested the significance of the difference in each of acoustic parameters between when the "Ah" vowel is produced with a normal voice and when the "Ah" vowel is produced with a loud voice. Results : Acoustic parameters that showed a statistically significant difference according to intensity increase were Jitter, SD F0, and NNE for females, and Jitter, SD F0, HNR, SNR, and NNE for males. Voice quality estimates showed a statistically significant difference according to intensity increase in female hoarse voice, female breathy voice, and male breathy voice. Conclusion : In this research, acoustic analysis, which is generally used for voice assessment before and after the operation or the voice treatment, showed a tendency that acoustic parameters became better under the influence of intensity increase except for the cases where a voice disease was severe. Thus, to raise the reliability of voice assessment, the range of intensity needs to be set up. This should be the topic for the future research.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.2
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• pp.214-219
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• 2001

In this paper, the nonlinear behavior of ultrasonic wave in partially degraded material is considered. For this aim, FDM(finite difference method) model for the nonlinear wave equation was developed with the restriction to the 1-D longitudinal wave motion and how the partial degradation in material contributes to the detected nonlinear parameter was analyzed quantitatively. In order to verify the rightness of this simulation method, the relation between the detected nonlinear parameter and the continuous distribution of degradation obtained from simulation was compared with experiment results and the simulation and experiment results showed similar tendency. It can be known from simulation result that the degree of degradation, the range of degradation and the continuous distribution of degradation have strong correlation with the detected nonlinear parameter. As it was possible in these simulations that only special part is assumed as degraded one, the quantitative evaluation of partially degraded material may be obtained by using this method.

• Geomechanics and Engineering
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• v.20 no.2
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• pp.113-120
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• 2020

Rock damage is the main cause of accidents in underground engineering. It is difficult to predict rock damage accurately by using only one parameter. In this study, a rock failure prediction model was established by using stress, energy, and damage. The prediction level was divided into three levels according to the ratio of the damage threshold stress to the peak stress. A classification predicting model was established, including the stress, energy, damage and AE impact rate using Bayesian method. Results show that the model is good practicability and effectiveness in predicting the degree of rock failure. On the basis of this, a multi-parameter classification predicting deterioration model of rock failure was established. The results provide a new idea for classifying and predicting rockburst.