Urban Traffic Noise Maps under 3D Complex Building Environments on a Supercomputer

Cai, Ming; Yao, Yifan; Wang, Haibo

doi:10.1155/2018/7031418

Cited by 17 publications

(6 citation statements)

References 29 publications

(35 reference statements)

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“…As the basic data of acoustical environment evaluation, the precise noise levels are usually derived from noise predictions in urban building areas because monitoring the noise in a large area is time-consuming and expensive [21]. However, modeling the sound field in a building area is difficult due to the complicated reflection and diffraction caused by buildings [22]. The current studies to calculate simulated noise focus primarily on the empirical method and the geometric acoustic method.…”

Section: Introductionmentioning

confidence: 99%

Simulation and Analysis of Road Traffic Noise among Urban Buildings Using Spatial Subdivision-Based Beam Tracing Method

Wang

Cai

Cui

2019

IJERPH

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In order to realize the simulation and evaluation of road traffic noise among urban buildings, a spatial subdivision-based beam-tracing method is proposed in this study. First, the road traffic source is divided into sets of point sources and described with the help of vehicle emission model. Next, for each pair of source and receiver, spatial subdivision-based beam-tracing method is used in noise paths generation. At last, noise distribution can be got by noise calculation of all receivers considering the complex transmission among urban buildings. A measurement experiment with a point source is carried out to validate the accuracy of the method; the 0.8 m height and 2.5-m height average errors are about 0.9 dB and 1.2 dB, respectively. Moreover, traffic noise analysis under different building layouts and heights are presented by case applications and conclusions can be reached: (1) Different patterns result in different noise distributions and patterns designed as self-protective can lead to an obvious noise abatement for rear buildings. Noise differences between the front and rear buildings are about 7–12 dB with different patterns. (2) Noise value might not show a linear variation along with the height as shielding of different layers is various in reality.

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Section: Introductionmentioning

confidence: 99%

Simulation and Analysis of Road Traffic Noise among Urban Buildings Using Spatial Subdivision-Based Beam Tracing Method

Wang

Cai

Cui

2019

IJERPH

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“…Asphalt roads are likely to produce more noise than other types due to their rigid nature and lack of sound absorption capacity (Ali & Tamura, 2003;Medinas et al, 2019). The urban conditions and building shapes on the sides of the road could also affect the noise level (Cai et al, 2018). The impact of the surrounding urban and building characteristics on the road noise depends on several factors.…”

Section: Road Characteristicsmentioning

confidence: 99%

Studying the factors that affect urban road noise – Case study: El-Tahrir Street, Al-Dokki Cairo, Egypt

Alyeldin¹,

Seddiq,

Nour

et al. 2024

Preprint

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Expanding road networks to accommodate various activities has increased urban noise pollution, adversely affecting human health and quality of life. Numerous factors, including road characteristics, traffic characteristics, surrounding buildings, and weather conditions. This study aims to monitor and analyse the effect of these factors on the noise level. Cairo is one of the most densely populated cities in the world, which has led to a high level of noise in its different areas. One of the most crowded areas in the city is El-Tahrir Street in Al-Dokki, which was selected as a case study in this research. This area is distinct by a wide range of services and activities, and it experiences high traffic volume, with up to 1,700 vehicles passing through within a 15-minute interval. This significant traffic volume is the primary driver of the elevated noise levels in the area. Traffic and noise level monitoring has been conducted using reliable equipment to study this issue. Consequently, a statistical analysis has been conducted to investigate the correlation between different factors and the noise level to determine the most influential factors that could help draw future intervention plans.

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“…In their research, Murphy and King (2011) used a noise prediction model to estimate the population exposure to daytime and night-time traffic noise. Nowadays, the calculation of traffic noise has developed into noise mapping (Wang et al 2018); large-scale urban traffic noise maps can be drawn based on certain parameters, such as traffic volume and vehicle speed of the road network (Cai et al 2018). According to Cai et al (2017a) research, the convenience of traffic flow parameter acquisition makes it possible to draw the dynamic traffic noise maps or make a quick update to the noise maps according to the changes of traffic flow in urban area.…”

Section: Review Of the Related Researchesmentioning

confidence: 99%

Research on the Noise Pollution From Different Vehicle Categories in the Urban Area

2023

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The noise pollution inside urban areas is one of the common problems for the inhabitants. The different levels of a noise are generated from the large amount of sources, including traffic flow on a road of urban areas. Therefore, it is essential to measure and evaluate the road traffic noise in urban areas and its population exposure in order to obtain models of a traffic noise as well as the noise mapping. The current research includes establishing a traffic noise from the different types of vehicles caused by the speed in urban areas and different road pavements (dry, wet and covered with a snow) with generalising the obtained data for more accurate using in future traffic noise models and the noise mapping. The study region is Vilnius (Lithuania), the speed range for different categories of the vehicles in the collected data is 40…130 km/h, with wide ranges of a noise level 20…180 dB. The approach presented in this research of experimental measurements is based on Statistical Pass-By (SPB) method with data proceeding upon implementation of Pearson correlation coefficient. In course of the analysis of the obtained results, it was found that the level of the curves of noise depends on the vehicles’ speed what corresponds to the best-measured values and can be used in the traffic noise models and the noise mapping.

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Urban Traffic Noise Maps under 3D Complex Building Environments on a Supercomputer

Cited by 17 publications

References 29 publications

Simulation and Analysis of Road Traffic Noise among Urban Buildings Using Spatial Subdivision-Based Beam Tracing Method

Simulation and Analysis of Road Traffic Noise among Urban Buildings Using Spatial Subdivision-Based Beam Tracing Method

Studying the factors that affect urban road noise – Case study: El-Tahrir Street, Al-Dokki Cairo, Egypt

Research on the Noise Pollution From Different Vehicle Categories in the Urban Area

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