Nonlinear, statistical models of tire-pavement noise

Tyler Dare, Rebecca McDaniel, Ayesha Shah

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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 amodel 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.

Original languageEnglish (US)
Pages (from-to)324-334
Number of pages11
JournalNoise Control Engineering Journal
Volume64
Issue number3
DOIs
StatePublished - May 2016

All Science Journal Classification (ASJC) codes

  • Building and Construction
  • Automotive Engineering
  • Aerospace Engineering
  • Acoustics and Ultrasonics
  • Mechanical Engineering
  • Public Health, Environmental and Occupational Health
  • Industrial and Manufacturing Engineering

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