scholarly journals Analysis of Influencing Factors on Noise Reduction Effect of High-Speed Railway Sound Barrier

2019 ◽  
Vol 493 ◽  
pp. 012042
Author(s):  
Wenjuan Sun ◽  
Qiaoping Su ◽  
Hongli Yuan
Keyword(s):  
Noise Reduction ◽  
Influencing Factors ◽  
High Speed ◽  
High Speed Railway ◽  
Sound Barrier ◽  
Reduction Effect

Test and Analysis of Noise Reduction Effect for Different Heights and Distances of Sound Barrier

2011 ◽  
Vol 243-249 ◽  
pp. 4447-4450 ◽  
Author(s):  
Yan Liu ◽  
Bing Yang ◽  
Xiao Pai Zhang ◽  
Zhi Fang Zhong ◽  
Hua Xin Dong ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Sound Pressure Level ◽  
High Frequency ◽  
Sound Pressure ◽  
Pressure Level ◽  
High Frequency Range ◽  
Frequency Range ◽  
Sound Barrier ◽  
Test Points ◽  
Reduction Effect

Based on the comparative analysis on the low-noise road surface, noise reduction green belts, noise barriers and other noise reduction methods, the sound barrier is put forward as an important method for reducing the city road traffic noise. The noise reduction effects for different heights and different distances of the sound barrier are tested and analyzed through noise and vibration test and analysis system, the following conclusions can be drawn. At the same heights from the ground, the father the test points away from the noise barrier, the higher the sound pressure level will be; At the same distances from the sound barrier, the nearer the test points from the ground, the smaller the sound pressure level will be; All of the sound pressure level curves have basically the same variation trend and the main noise frequency band is from 160 to 1600Hz; In the high frequency range which is greater than 1600Hz, the sound pressure level decrease significantly, indicating that the sound barrier has better noise reduction effect for high frequency range. The results provide the basis for the design of the sound barriers.

Prediction for Percentage of Vehicle Entering Expressway Rest Area Based on BP Neural Network

2012 ◽  
Vol 178-181 ◽  
pp. 1956-1960
Author(s):  
Xiao Yan Shen ◽  
Hao Xue Liu ◽  
Jia Liu
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Influencing Factors ◽  
High Precision ◽  
Bp Neural Network ◽  
High Speed ◽  
High Speed Railway ◽  
Neural Network Prediction ◽  
Network Prediction ◽  
Influence Degree

In order to scientifically decide the percentage of vehicle entering expressway rest area, based on analyzing the influencing factors relating to the percent of mainline traffic stopping, a BP neural network prediction model for it was put forward. Finally, The Xinzheng Rest Area (XRA) was taken as an example for verifying the feasibility of the prediction model and determining the influence degree of the Shijiazhuang-Wuhan high-speed railway on the percentage of mainline vehicles entering XRA. The result shows that the model had a high precision and reliability.

scholarly journals Negative External Cost Computing Model for Noise of China’s High-speed Railway and its Verification and Trend Analysis

2021 ◽  
Vol 261 ◽  
pp. 03029
Author(s):  
Xiaomei Xuan
Keyword(s):  
Noise Reduction ◽  
High Speed ◽  
Early Stage ◽  
Rapid Development ◽  
Density Ratio ◽  
External Noise ◽  
Future Trend ◽  
Cost Calculation ◽  
External Cost ◽  
High Speed Railway

The purpose of this paper is to calculate the external noise cost of China’s high-speed railway and forecast its future trend. Firstly, the unit value transfer method after correction is selected as a method of calculation. Secondly, the noise cost calculation model of China’s high-speed railway is established by introducing the correction factors such as GDP-PPP, population density ratio and CPI ratio. At last, the external noise cost since the opening of high-speed railway is calculated. The model validation results show that although the average external noise cost of high-speed railway increases year by year, it does not increase significantly. This is not only related to economic growth and improvement of noise reduction technology, but also related to the increase of investment in noise reduction facilities in the early stage. Compared with it, the total external cost of high-speed railway noise increases obviously, which is positively related to the rapid development of high-speed railway. With the increase of high-speed railway mileage and passenger turnover, the total noise cost increases significantly. It can be predicted that with the implementation of high-speed railway planning in the future, the negative external cost of noise will continue to increase.

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