A nonlinear model for predicting pavement serviceability

Jorge A. Prozzi, Samer M. Madanat

Research output: Contribution to conferencePaper

Abstract

A recursive nonlinear model was developed to predict pavement deterioration. Pavement deterioration was assessed in terms of loss of serviceability - expressed as a function of traffic characteristics, pavement structural properties and environmental conditions. The model highlights some of the advantages of relaxing the linear restriction usually placed on the model specification. First, a functional form that better represents the physical deterioration process can be used. Second, the estimated parameters are unbiased because of proper specification and the use of sound estimation techniques. Finally, the standard error of the regression was reduced by half that of the equivalent existing linear model. The model developed enables the determination of an unbiased exponent of the so-called power law, and equivalent loads for different axle configurations. The estimated exponent confirms the value of 4.2 traditionally used. However, equivalent loads estimated for different axle configurations differed from traditionally used values. The estimated equivalent load for a single axle with single wheels is 44 kN, while the equivalent load for a tandem axle with dual wheels is 148 kN.

Original languageEnglish (US)
Pages481-488
Number of pages8
DOIs
StatePublished - 2002
EventProceedings of the seventh International Conference on: Applications of Advanced Technology in Transportation - Cambridge, MA, United States
Duration: Aug 5 2002Aug 7 2002

Other

OtherProceedings of the seventh International Conference on: Applications of Advanced Technology in Transportation
CountryUnited States
CityCambridge, MA
Period8/5/028/7/02

ASJC Scopus subject areas

  • Engineering(all)

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    Prozzi, J. A., & Madanat, S. M. (2002). A nonlinear model for predicting pavement serviceability. 481-488. Paper presented at Proceedings of the seventh International Conference on: Applications of Advanced Technology in Transportation, Cambridge, MA, United States. https://doi.org/10.1061/40632(245)61