@article {Dare:2016:0736-2501:324,
title = "Nonlinear, statistical models of tire-pavement noise",
journal = "Noise Control Engineering Journal",
parent_itemid = "infobike://ince/ncej",
publishercode ="ince",
year = "2016",
volume = "64",
number = "3",
publication date ="2016-05-01T00:00:00",
pages = "324-334",
itemtype = "ARTICLE",
issn = "0736-2501",
url = "https://ince.publisher.ingentaconnect.com/content/ince/ncej/2016/00000064/00000003/art00004",
doi = "doi:10.3397/1/376382",
keyword = "73.1, 11.7.1",
author = "Dare, Tyler and McDaniel, Rebecca and Shah, Ayesha",
abstract = "Tire-pavement noise is the result of a complex system of noise generation mechanisms and is affected by several different pavement and atmospheric parameters. Accurately predicting tire-pavement noise from given a set of parameters has proven difficult for researchers. The purpose of
this research was to explore a wealth of pavement, atmospheric and noise data taken at the MnROAD pavement test facility and to develop a model to predict tire-pavement noise on asphalt pavements. Using a series of sub-models, variables significant to noise generation were identified. Finally,
two variations of a model of noise generation were developed, each capable of predicting one-third octave band on-board sound intensity (OBSI) spectra. The model was developed using a hybrid statistical-experimental approach and was able to predict overall OBSI levels to within 1.5 dB for
80-90% of the pavements tested.",
}