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Evaluation of New Mechanistic–Empirical Pavement Design Guide Rutting Models for Multiple-Axle Loads

Authors: Hassan K. Salama; Syed Waqar Haider; Karim Chatti;

Evaluation of New Mechanistic–Empirical Pavement Design Guide Rutting Models for Multiple-Axle Loads

Abstract

The new FHWA Mechanistic–Empirical Pavement Design Guide (M-E PDG) does away with the AASHO-derived concept of the equivalent single-axle load and calculates damage caused by various axle configurations directly. Because multiple axles represent about half the axle configurations that the pavement will experience, there is a need to evaluate the M-E PDG procedure for predicting rutting due to multiple-axle configurations. Axle factors (AFs) based on rutting were calculated for different axle configurations by using three procedures: the M-E PDG, accounting for the effect of each individual axle within a group, and integrating the entire strain pulse. The AFs from these procedures were compared with laboratory-derived values for asphalt concrete. Also, layer rutting contributions were predicted for six in-service SPS-1 experiment sections from the Long-Term Pavement Performance Program with the M-E PDG software and were compared with the analysis of their transverse surface profiles. The results show that the M-E PDG procedure underestimates rutting prediction due to multiple axles. Calibration of the M-E PDG rut models with field data seems to improve their prediction, although it is still lower than expected for multiple axles. The best method for calculating rut depths under multiple axles appears to be integration of the entire strain pulse. This method shows that rutting damage is proportional to the number of axles within an axle group. This theory was confirmed in the laboratory for asphalt concrete. Also, although the M-E PDG rut models are superior to previous rut models, in that they are able to dissect the total surface rutting between all pavement layers, their prediction of the individual layer rutting contributions does not always agree with results from the analysis of measured transverse profiles.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Average
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