• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.754-758
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• 2006

The purpose of this study is to propose calculation and application method of a common factor from different noise source unit such as $L_{eq}$ and WECPNL, A calculation was conducted by method that propose TNO-PG. Also, An applied example is a noise environmental standard of Korea and Japan. After %HA of two country are calculated, noise standards of two countries were compared by using %HA. The result by a equation of %HA is to convert a noise level($L_{dn}$) into a %HA. To calculate a %HA, First $L_{eq}$ is converted into $L_{dn}$. Then, $L_{dn}$, has inputted into and %HA has deduced from a %HA equation of TNO-PG. If the same area is applied the same %HA value according to area categories, it can be applied the same %HA to different noise sources. As a results. a noise levels have computed different values because responses of human change in accordance with a noise sources. This results can be applied to the noise environmental assessment for a domestic railway and aircraft noise.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.51-57
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• 2010

In this study, damages due to the aircraft noise were examined in more than 190 elementary, middle and high schools near the airports in Korea, and the persecutory idea forecast model was established using the quantification theory type II. Via the survey of 1,012 teachers in the schools, a class interference forecast model was established, and the noise characteristics of five areas, four military/civil common-use airports and one shooting range, were examined. The following conclusions were made from the study. WECPNL values in the five military/civil common-use airports showed that all of them were Class 1 or 2 affected areas, which indicated that they had serious aircraft noise problems to be addressed. The most influential factor in the aircraft noise persecutory idea model was the distance between the airport and the school. It showed a positive relationship at a distance of less than 5 km, and a negative relationship at a distance of 10 km or more. The number and time of aircraft noise exposure as well as the types of airports and window structures had strong influences. The forecast model had a correlation ratio of 0.56, which indicates that it is highly appropriate. In the class interference factor analysis, the time and number of aircraft noise exposure were strong influential factors, and the results varied according to the service duration and sex of teachers. This model had a correlation ratio of 0.61, which indicates it is highly appropriate.