An aircraft noise prediction model considering meteorological effects on noise propagation developed for air traffic optimization

2016 ◽  
Vol 140 (4) ◽  
pp. 3257-3257
Author(s):  
Hirokazu Ishii ◽  
Adriana Andreeva-Mori ◽  
Takatoshi Yokota ◽  
Koichi Makino ◽  
Toshio Matsumoto
Keyword(s):  
Prediction Model ◽  
Aircraft Noise ◽  
Air Traffic ◽  
Noise Prediction ◽  
Noise Propagation ◽  
Traffic Optimization ◽  
Meteorological Effects

Road Traffic Noise Prediction Model

2012 ◽  
Vol 3 (4) ◽  
pp. 110-112
Author(s):  
Rahul Singh ◽  
◽  
Parveen Bawa ◽  
Ranjan Kumar Thakur
Keyword(s):  
Prediction Model ◽  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Noise Prediction

Acoustic Modeling of Meteorological Effects on Roadway Noise

2021 ◽  
pp. 036119812199458
Author(s):  
Roger L. Wayson ◽  
Kenneth Kaliski
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Model Development ◽  
The United States ◽  
Noise Model ◽  
Road Traffic Noise ◽  
Atmospheric Conditions ◽  
Noise Propagation ◽  
Transportation Research ◽  
Meteorological Effects

Modeling road traffic noise levels without including the effects of meteorology may lead to substantial errors. In the United States, the required model is the Traffic Noise Model which does not include meteorology effects caused by refraction. In response, the Transportation Research Board sponsored NCHRP 25-52, Meteorological Effects on Roadway Noise, to collect highway noise data under different meteorological conditions, document the meteorological effects on roadway noise propagation under different atmospheric conditions, develop best practices, and provide guidance on how to: (a) quantify meteorological effects on roadway noise propagation; and (b) explain those effects to the public. The completed project at 16 barrier and no-barrier measurement positions adjacent to Interstate 17 (I-17) in Phoenix, Arizona provided the database which has enabled substantial developments in modeling. This report provides more recent information on the model development that can be directly applied by the noise analyst to include meteorological effects from simple look-up tables to more precise use of statistical equations.

Data Collection and Modeling Results to Permit Estimation of Meteorological Effects on Roadway Noise

2019 ◽  
Vol 2673 (11) ◽  
pp. 243-253
Author(s):  
Roger L. Wayson ◽  
Kenneth Kaliski ◽  
John M. MacDonald ◽  
Erik M. Salomons ◽  
Darlene D. Reiter
Keyword(s):  
United States ◽  
Data Collection ◽  
Road Traffic ◽  
Meteorological Data ◽  
Traffic Noise ◽  
The United States ◽  
Road Traffic Noise ◽  
Atmospheric Conditions ◽  
Noise Propagation ◽  
Meteorological Effects

The estimation of absolute road traffic noise levels without including the effects of meteorology is thought to be a major source of error in the estimation process commonly used in the United States. In response, the Transportation Research Board-sponsored NCHRP 25-52, Meteorological Effects on Roadway Noise, to collect highway noise data under different meteorological conditions, document the meteorological effects on roadway noise propagation under different atmospheric conditions, develop best practices, and provide guidance on how to (a) quantify meteorological effects on roadway noise propagation and (b) explain those effects to the public. The completed project involved collecting and analyzing 35,000 min of sound and meteorological data at 16 barrier and no-barrier measurement positions adjacent to Interstate 17 in Phoenix, Arizona. This report provides information on the data collection and the modeling recommendations. The database assembled is thought to be among the best available in the United States to permit analysis of meteorological effects on roadway noise. The study recommendations will advance the methodology for estimating the meteorological effects on roadway noise in the United States.

Traffic noise prediction model of an Indian road: an increased scenario of vehicles and honking

2020 ◽  
Vol 27 (30) ◽  
pp. 38311-38320
Author(s):  
Chaitanya Thakre ◽  
Vijaya Laxmi ◽  
Ritesh Vijay ◽  
Deepak J. Killedar ◽  
Rakesh Kumar
Keyword(s):  
Prediction Model ◽  
Traffic Noise ◽  
Noise Prediction
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