• The Journal of the Acoustical Society of Korea
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• v.42 no.3
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• pp.189-202
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• 2023

In this study, the acoustic performance was analyzed by architectural shapes of the hall. There are four architectural shapes of halls. They are rectangular, horseshoe, surround, and fan-shape. Eight acoustic parameters were used to determine the acoustic performance. These are RT₆₀, EDT, C₈₀, BQI, LF, G_mid, G₁₂₅ and ITDG. First, measurement data of famous concert halls around the world were analyzed. The correlation coefficient R was obtained by regression analysis of the relationship between the subjective ranking of the halls and the acoustic parameters. It was found that BQI, G, and ITDG have higher correlation coefficients R. Also the average of acoustic parameters for each architectural shape were obtained. The total acoustic performance for each shape was calculated by using the correlation coefficient R as a weight for each acoustic parameters. As a result, rectangular halls and horseshoe halls showed good acoustical performances. Second, 3D models of each architectural shape were created and acoustic simulation had been performed. The simulation was performed by creating 3D models of each four shapes of concert halls with the same volume and sound absorption coefficient. Listening test was carried out using the sound source which is created from impulse responses of 3D model. As a result, rectangular hall and horseshoe hall showed the best performance however surround hall and fan-shaped hall showed relatively poor performance.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.18 no.2
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• pp.61-67
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• 1982

Optical properties of sea water were studied in the southern sea of Korea, based on ten oceanographic stations in July, 1980. Submarine daylight intensity was measured at intervals of 5m depth in the upper 70m layer by using the underwater irradiameter (Kahlsico # 268 WA 360). The mean absorption coefficients of the sea water were shown as 0.102 (0.066~0.137), 0.119 (0.069~0.154), 0.091 (0.054~.0123), and 0.095 (0.056~0.129) for clear, red, green, and blue color respectively. The transparency ranged from 13 to 25 meters (mean 17.1 m). The mean water color in this area was 3.9 (3-5) in Forel scales. The relation between absorption coefficient (k) and transparency (D) was k=1.17/D, k=2.01/D, k=1.52/D, and k=1.60/D for clear, red, green, and blue color respectively. The rates of light penetration for clear, red, green, and blue color in four different depths were computed with reference to the surface light intensity respectively. The mean rates of light penetration in proportion to depths were as follows; clear : 57.3%(5m), 20.82%(15m), 5.16%(30m), 0.94%(50m). red : 52.2%(5m), 15.99%(15m), 2.99%(30m), 0.39%(50m). green : 60.9%(5m), 24.51%(15m), 7.11%(30m), 1.56%(50m). blue : 59.4%(5m), 22.92%(15m), 6.09%(30m), 1.29%(50m).

• Journal of Environmental Impact Assessment
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• v.26 no.1
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• pp.11-26
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• 2017

Approximate empirical equations obtained by measuring overall noise levels at different distances have been used to evaluate environmental influence of the railway noise though the accurate prediction of noise levels is important. In this paper, a noise prediction model considering the frequency characteristics of noise sources and propagation was suggested to improve the accuracy of noise prediction. The railway noise source was assorted into track, wheel, traction and aerodynamic components and they were characterized with the source strength and speed coefficient at each octave-band frequency. Correction terms for the acoustic roughness and the track/bridge condition were introduced. The sound attenuation from a source to a receiver was calculated taking account of the geometrical divergence, atmospheric absorption, ground effect, diffraction at obstacles and directivity of source by applying ISO 9613-2. For obtaining the source strength and speed coefficients, the results of rolling noise model, numerical analysis and measurements of pass-by noise were analyzed. We compared the predicted and measured noise levels in various vehicles and tracks, and verified the accuracy of the present model. It is found that the present model gives less error than the conventional one, so that it can be applied to make the accurate prediction of railway noise effect and establish its countermeasures efficiently.