Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/31386

TitleA model for equivalent axle load factors
Author(s)Amorim, Sara R.
Pais, Jorge C.
Vale, Aline C.
Minhoto, Manuel J. C.
KeywordsAxle type
Equivalent axle load factor
Equivalent single axle load
Road pavements
Traffic
Wheel type
Issue date2015
PublisherTaylor & Francis
JournalInternational Journal of Pavement Engineering
CitationAmorim S. R., Pais J. C., Vale A. C., Minhoto M. J. C. A model for equivalent axle load factors, International Journal of Pavement Engineering, 2015.
Abstract(s)Most design methods for road pavements require the design traffic, based on the transformation of the traffic spectrum, to be calculated into a number of equivalent passages of a standard axle using the equivalent axle load factors. Generally, these factors only consider the type of axle (single, tandem or tridem), but they do not consider the type of wheel on the axles, i.e., single or dual wheel. The type of wheel has an important influence on the calculation of the design traffic. The existing design methods assume that the equivalent axle load factors are valid for all pavement structures and do not consider the thickness and stiffness of the pavement layers. This paper presents the results of the development of a model for the calculation of the equivalent axle load factors considering the type of axle, the type of wheel and the constitution of the pavement. The model was developed based on the tensile strain at the bottom of the asphalt layer that is responsible for bottom-up cracking in asphalt pavement, which is the most widely considered distress mode for flexible road pavements. The work developed in this study also presents the influence of the type of wheel (single and dual) on pavement performance. The results of this work allowed the conclusion that the equivalent axle load factors for single wheels is approximately 10 times greater than for a dual wheel. This work also proposes average values for the equivalent axle load factors. An artificial neural network was developed to calculate the equivalent axle load factors.
TypeArticle
URIhttp://hdl.handle.net/1822/31386
DOI10.1080/10298436.2014.968570
ISSN1464-8164
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:C-TAC - Artigos em Revistas Internacionais

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