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Study Of Traffic Noise Prediction Model And Traffic Noise Attenuation By Tree Belts

Posted on:2006-11-04Degree:MasterType:Thesis
Country:ChinaCandidate:Y C DingFull Text:PDF
GTID:2121360182471649Subject:Environmental Engineering
Abstract/Summary:PDF Full Text Request
The expressway construction brings about many environmental problems such as gas, water, ecological and noise. Traffic seriously destroyed noise environment around the expressway. So how to effectively control and improve noise environment along the road becomes an important task. Based on the two noise prediction models of FHWA and Prediction Model from Transportation Ministry, a noise prediction program was compiled. Noise barrier insertion loss was discussed. By inputting barrier parameters, road parameters, detection points' parameters and traffic volume, ground condition, then noise sound level in detection points can be predicted. We can optimize barrier parameter and predict the barrier's effect on noise reduction by using this program, can discover the sound field distribution character on the side of the expressway after noise barrier was built. Result of many experiments indicates that the error of the program is within 3dB(A), which indicates that the program is versatile and accurate. This thesis outlines the results of noise attenuation investigation at many plantation sites in Wuhan. Based on characterization of the plantation sites and measured noise attenuation effect, relationship between noise attenuation and green belt characterization or parameters such as light penetration, width was discussed. And frequency spectrum was analysed for all the eight plantation sites. The total attenuation for all the sites increased with the width of the green belt in most of the frequencies. Relationship between the growth time and noise attenuation was discussed. Bring forward a proposal for road green belt design for reducing noise.
Keywords/Search Tags:Traffic Noise, Prediction Model, Prediction Program, Green Belts, Noise Attenuation
PDF Full Text Request
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