• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.2
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• pp.109-117
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• 2015

Aircraft needs an inlet duct to supply the airflow to engine face. A fighter aircraft that requires low radar observability has to hide the engine face in the fuselage to reduce the Radar Cross Section(RCS). Therefore, the flow path of the inlet duct is changed into S-shape. The performance of the aircraft engine is known to be influenced by the shape and the centerline curvature of the S-Duct. In this study, CFD analysis of the RAE M 2129 S-Duct has been performed to investigate the influence of aspect ratio of inlet geometry. The performance of the S-Duct is evaluated in terms of the distortion coefficient. To simulate the flow under adverse pressure gradient better, $k-{\omega}SST$ turbulence model is employed. The computational results are validated with the ARA experimental data. The secondary flow and the flow separation are observed for all computational cases, while the semi-circular geometry has been found to produce the best results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.7
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• pp.586-603
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• 2004

One of the subtle problems that make noise control difficult for engineers is “the invisibility of noise or sound.” The visual image of noise often helps to determine an appropriate means for noise control. There have been many attempts to fulfill this rather challenging objective. Theoretical or numerical means to visualize the sound field have been attempted and as a result, a great deal of progress has been accomplished, for example in the field of visualization of turbulent noise. However, most of the numerical methods are not quite ready to be applied practically to noise control issues. In the meantime, fast progress has made it possible instrumentally by using multiple microphones and fast signal processing systems, although these systems are not perfect but are useful. The state of the art system is recently available but still has many problematic issues : for example, how we can implement the visualized noise field. The constructed noise or sound picture always consists of bias and random errors, and consequently it is often difficult to determine the origin of the noise and the spatial shape of noise, as highlighted in the title. The first part of this paper introduces a brief history, which is associated with “sound visualization,” from Leonardo da Vinci's famous drawing on vortex street (Fig. 1) to modern acoustic holography and what has been accomplished by a line or surface array. The second part introduces the difficulties and the recent studies. These include de-Dopplerization and do-reverberation methods. The former is essential for visualizing a moving noise source, such as cars or trains. The latter relates to what produces noise in a room or closed space. Another mar issue associated this sound/noise visualization is whether or not Ivecan distinguish mutual dependence of noise in space : for example, we are asked to answer the question, “Can we see two birds singing or one bird with two beaks?"

• Journal of dental hygiene science
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• v.16 no.4
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• pp.284-292
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• 2016

Water supplied through dental unit waterlines (DUWLs) has been shown to contain high number of bacteria. To reduce the contamination of DUWLs, it is essential to develop effective disinfectants. It is, however, difficulty to obtain proper DUWL samples for studies. The purpose of this study was to establish a simple laboratory model for reproducing DUWL biofilms. The bacteria obtained from DUWLs were cultured in R2A liquid medium for 10 days, and then stored at $-70^{\circ}C$. This stock was inoculated into R2A liquid medium and incubated in batch mode. After 5 days of culturing, it was inoculated into the biofilm formation model developed in this study. Our biofilm formation model comprised of a beaker containing R2A liquid medium and five glass rods attached to DUWL polyurethane tubing. Biofilm was allowed to form on the stir plate and the medium was replaced every 2 days. After 4 days of biofilm formation in the laboratory model, biofilm thickness, morphological characteristics and distribution of the composing bacteria were examined by confocal laser microscopy and scanning electron microscopy. The mean of biofilm accumulation was $4.68{\times}10^4$ colony forming unit/$cm^2$ and its thickness was $10{\sim}14{\mu}m$. In our laboratory model, thick bacterial lumps were observed in some parts of the tubing. To test the suitability of this biofilm model system, the effectiveness of disinfectants such as sodium hypochlorite, hydrogen peroxide, and chlorhexidine, was examined by their application to the biofilm formed in our model. Lower concentrations of disinfectants were less effective in reducing the count of bacteria constituting the biofilm. These results showed that our DUWL biofilm laboratory model was appropriate for comparison of disinfectant effects. Our laboratory model is expected to be useful for various other purposes in further studies.