• International Journal of Aeronautical and Space Sciences
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• v.16 no.2
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• pp.165-176
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• 2015

A numerical analysis was conducted to investigate the inlet buzz and combustion oscillation in an axisymmetric ramjet engine with wedge-type flame holders. The physical model of concern includes the entire engine flow path, extending from the leading edge of the inlet center-body through the exhaust nozzle. The theoretical formulation is based on the Farve-averaged conservation equations of mass, momentum, energy, and species concentration, and accommodates finite-rate chemical kinetics and variable thermo-physical properties. Turbulence closure is achieved using a combined scheme comprising of a low-Reynolds number k-${\varepsilon}$ two-equation model and Sarkar's compressible turbulence model. Detailed flow phenomena such as inlet flow aerodynamics, flame evolution, and acoustic excitation as well as their interactions, are investigated. Mechanisms responsible for driving the inlet buzz are identified and quantified for the engine operating at subcritical conditions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.675-679
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• 2006

Today, the interior noise perceived by the occupants is an important factor in the design of automotive interior assemblies. Buzz, Squeak and Rattle Noises in a Seats are one of the major concerns mentioned above. In this study, the terms 'Buzz, squeak and rattle' were defined as the noise originating from structural vibrations in an assembly. And, the BSR noise of vehicle seat was investigated and the improvement of BSR noise level was confirmed though the structural treatment based on the structural analysis results from the modal and sound intensity of seat.

• Advances in aircraft and spacecraft science
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• v.4 no.2
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• pp.203-218
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• 2017

This paper focuses on the computational study of nonlinear effects of unsteady aerodynamics for non-classical aileron buzz. It aims at a comprehensive investigation of the aileron buzz phenomenon under varying flow parameters using the describing function technique with multiple inputs. The limit cycle oscillatory behavior of an asymmetrical airfoil is studied initially using a CFD-based numerical model and direct time marching. Sharp increases in limit cycle amplitude for varying Mach numbers and angles of attack are investigated. An aerodynamic describing function is developed in order to estimate the variation of limit cycle amplitude and frequency with Mach number and angle of attack directly, without time marching. The describing function results are compared to the amplitudes and frequencies predicted by the CFD calculations for validation purposes. Furthermore, a limited sensitivity analysis is presented to demonstrate the potential of the approach for aeroelastic design.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.3
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• pp.296-306
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• 2012

A series of numerical simulations are carried out to analyze a supersonic inlet buzz, which is an unsteady pressure oscillation phenomenon around a supersonic inlet. A simple but efficient geometry, experimentally adopted by Nagashima, is chosen for the analysis of unsteady flow physics. Among the two sets of simulations considered in this study, the effects of various throttling conditions are firstly examined. It is seen that the major physical characteristic of the inlet buzz can be obtained by inviscid computations only and the computed flow patterns inside and around the inlet are qualitatively consistent with the experimental observations. The dominant frequency of the inlet buzz increases as throttle area decreases, and the computed frequency is approximately 60Hz or 15% lower than the experimental data, but interestingly, this gap is constant for all the test cases and shock structures are similar. Secondly, inviscid calculations are performed to examine the effect regarding angle of attack. It is found that patterns of pressure oscillation histories and distortion due to asymmetric (or three-dimensional) shock structures are substantially affected by angle of attack. The dominant frequency of the inlet buzz, however, does not change noticeably even in regards to a wide range of angle of attacks.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2009.05a
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• pp.88-92
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• 2009

Total pressure recovery ratio in intake is crucial factor to the operational characteristics of supersonic propulsion system because it does not compress inlet air mechanically by compressor, but does compress inlet air by ram compression. As the result of that the dynamic characteristic analysis of engine was performed before the controller was designed, it could be ascertained when the AoA of flight vehicle increases, the buzz margin decreases so that the shock wave produced outside intake in the specified area according to flight operation's characteristics. Therefore the PID control algorithm was designed to be controlled buzz margin that the characteristic of shock wave could meet the requirement of performance in intake. The PID controller was designed that the buzz margin value is being positive number using the control variables; fuel flow and nozzle throat area.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.256-261
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• 2018

There are three types of noise generated inside the vehicle: BSR (Buzz, Squeak, Rattle). In this paper, we propose a classifier that automatically classifies automotive BSR noise by using features extracted from deep convolutional neural networks. In the preprocessing process, the features of above three noises are represented as noise-map using STFT (Short-time Fourier Transform) algorithm. In order to cope with the problem that the position of the actual noise is unknown in the part of the generated noise map, the noise map is divided using the sliding window method. In this paper, internal parameter of the deep convolutional neural networks is visualized using the t-SNE (t-Stochastic Neighbor Embedding) algorithm, and the misclassified data is analyzed in a qualitative way. In order to analyze the classified data, the similarity of the noise type was quantified by SSIM (Structural Similarity Index) value, and it was found that the retractor tremble sound is most similar to the normal travel sound. The classifier of the proposed method compared with other classifiers of machine learning method recorded the highest classification accuracy (99.15 %).

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.334-339
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• 2019

In this study, the vibration test method to nondestructively evaluate the possibility of vehicle BSR (Buzz, Squeak, Rattle) noise generation in spot-welded structures was proposed. The weld quality was predicted by analyzing the local vibration transmission characteristics for the beam-shaped structure attached to testing spots. The bending stiffness was evaluated from the identified vibration properties. From the change in the stiffness, the weld quality was evaluated. For verification of the proposed method, the welded specimens were fabricated with partial changes in welding parameters. The local vibration transfers were measured. The frequency bands affected by the weld quality was identified. The capability of evaluating the welding parameters including defect position and quality variations was investigated. The proposed method enables fast quality evaluation to minimize the possibility of BSR noise generation in the manufactured vehicle.

• Journal of Digital Contents Society
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• v.15 no.2
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• pp.219-225
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• 2014

Competition between corporations is getting more intense, so they need customer feedback in order to fulfill an effective management. Recently, SNS (Social Network Service) such as Twitter and Facebook has grown dramatically because of smart phones. Social media like Twitter and Facebook let customers to express their needs, and using big data such as data on SNS is a very effective method for getting customer's feedback. Collecting and analyzing social big data are operated by Buzz monitoring system. This research suggests how to utilize big data for getting customer's feedback on hotel CRM(Customer Relationship Management), which considers customer itself as asset of business. This paper demonstrates the research of buzz monitoring system that analyzes big data, and presents results of hotel customer reputation using buzz monitoring system. It would analyze the result from the hotel customer reputation, and research the implication in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2439-2446
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• 2013

Recently, SNS (Social Network Service) such as Twitter and Facebook has grown dramatically because of smart phones. Since development of IT has created massive information, social big data extremely increased. Competition between corporations is getting more intense, so they need customer feedback in order to fulfill an effective management. Because social big data plays an important role for getting customer feedback, a lot of corporations are interested in analyzing and applying of social big data. Collecting and analyzing social big data is operated by Buzz monitoring system. This paper demonstrates the research of buzz monitoring system that analyzes big data, and presents examples of customer reputation using buzz monitoring. In the paper, after all, it would analyze the result from the customer reputation, and research the implication.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.8
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• pp.29-36
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• 2004

Supersonic inlet buzz can be defined as unstable subcritical operation associated with fluctuating internal pressures and a shock pattern oscillating about the inlet entrance. The flow pulsations could result in flameout in the combustor or even structural damage to the engine. An experimental study was conducted to investigate the phenomenon of supersonic inlet buzz on axisymmetric, external-compression inlet. An inlet model with a cowl lip diameter of 30mm was tested at a free stream Mach number of 2.0. Subcritical instability was investigated by considering the frequency of pressure pulsation and shock wave structure at the inlet entrance. The results obtained show that total pressure recovery ratios were varied from 0.42 to 0.78, and capture area ratio from 0.34 to 0.98. The frequency of the subcritical flow increased with decrease in capture area ratios. Frequency was measured at $224{\sim}240Hz$.