TY - JOUR
T1 - Development and validation of a tenable process for quantifying texture spikiness for pavement noise prediction
AU - Izevbekhai, Bernard Igbafen
AU - Voller, Vaughan R
PY - 2013/2/1
Y1 - 2013/2/1
N2 - In pavement infrastructure, it is important to characterise the surfaces for an effective prediction of noise. One of the major influencing variables, texture orientation, also called spikiness, is a measure of how spiky the surface asperities are. Tyre-pavement interaction noise is associated with mechanisms triggered by micro-, macro-and megatexture. Of the variables within macro-texture range, texture spikiness has gained increased interest by providing explanations for scenarios with similar texture direction and mean profile depth on the same level of distress yet exhibiting very different noise levels. A tool created in this research, 'PARSER', facilitated computation of skewness/spikiness statistics. This paper therefore tenably quantifies texture spikiness by the method of skewness of amplitude distribution function. Consequently, a logical quantification of texture spikiness has facilitated a phenomenological noise prediction model. When properly quantified, texture spikiness is an indispensable tyre-pavement interaction variable.
AB - In pavement infrastructure, it is important to characterise the surfaces for an effective prediction of noise. One of the major influencing variables, texture orientation, also called spikiness, is a measure of how spiky the surface asperities are. Tyre-pavement interaction noise is associated with mechanisms triggered by micro-, macro-and megatexture. Of the variables within macro-texture range, texture spikiness has gained increased interest by providing explanations for scenarios with similar texture direction and mean profile depth on the same level of distress yet exhibiting very different noise levels. A tool created in this research, 'PARSER', facilitated computation of skewness/spikiness statistics. This paper therefore tenably quantifies texture spikiness by the method of skewness of amplitude distribution function. Consequently, a logical quantification of texture spikiness has facilitated a phenomenological noise prediction model. When properly quantified, texture spikiness is an indispensable tyre-pavement interaction variable.
KW - asperity interval
KW - on-board sound intensity
KW - skewness
KW - spikiness
KW - texture orientation
UR - http://www.scopus.com/inward/record.url?scp=84871021168&partnerID=8YFLogxK
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U2 - 10.1080/10298436.2012.698013
DO - 10.1080/10298436.2012.698013
M3 - Article
AN - SCOPUS:84871021168
SN - 1029-8436
VL - 14
SP - 190
EP - 205
JO - International Journal of Pavement Engineering
JF - International Journal of Pavement Engineering
IS - 2
ER -