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Railway Noise Model

Authors: MacDonald, John M.; Wayson, Roger L.;

Railway Noise Model

Abstract

The Railway Noise Model (RWNM) was developed at the University of Central Florida and predicts sound levels at receivers near railway operations for analyses used in environmental documents. The RWNM is a simulation model, and trains are modeled as moving point sources of sound. The user can create model objects, tracks, barriers, and receivers, using either the mouse or spreadsheet interfaces. During simulation, the user observes trains moving along railways and the relationships to receiver locations. The RWNM simulates a 24-h period of rail traffic and computes day/night sound pressure level (Ldn), maximum sound pressure level (Lmax), sound exposure level (SEL), and equivalent sound pressure level (Leq) at the receivers. The RWNM uses REMEL (reference energy mean emission levels) curves based on Federal Transit Administration (FTA) reported Lmax pass-by levels for locomotives and rail cars. In addition, the model has the ability to model heavy rail locomotives and rail cars, which makes it applicable to Federal Railroad Administration projects. Testing has shown that the RWNM results match those of the FTA-approved spreadsheet, although heavy rail validation is limited.

Countries
Australia, United States
Keywords

330, Rail transit, Locomotives, Computer interfaces, mode - rail, Noise pollution, Heavy rail transit, Rapid transit, Railroads, Mathematical models, Computer simulation, Man computer interfaces, 004, User interfaces (Computer science), Railroad cars, Railways, Human computer interfaces, Noise, Simulation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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