4.5 Article

Asphalt fatigue endurance limit estimation and impact on perpetual pavement design

期刊

INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
卷 23, 期 4, 页码 1239-1247

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/10298436.2020.1797735

关键词

Fatigue endurance limit; asphalt concrete; fatigue cracking; perpetual pavement design

资金

  1. NCAT Pavement Test Track
  2. Federal Highway Administration

向作者/读者索取更多资源

This study evaluated the effectiveness of two methods, NCHRP 9-38 and NCHRP 9-44A, in estimating the fatigue endurance limit (FEL) of asphalt. The impact of these methods on asphalt thickness was also investigated. The results showed that the NCHRP 9-38 method yielded greater FEL values. Additionally, the NCHRP 9-44A model produced similar results for different types of mixtures when a rest period exceeding 5 seconds was entered.
The National Cooperative Highway Research Program (NCHRP) Project 9-38 developed a method for estimating asphalt fatigue endurance limit (FEL) which employs bending beam fatigue (BBF) lives. Another project, NCHRP 9-44A, used BBF test data to formulate a healing-based FEL prediction model. Both procedures were evaluated in this study by utilising data from the National Center for Asphalt Technology Pavement Test Track. The estimated FELs were used in perpetual pavement design to investigate their impact on asphalt thickness. The NCHRP 9-44A-predicted FELs increased with longer rest periods, but largely stabilised after 8 s, which agreed with the NCHRP 9-44A researchers' conclusion that no healing occurs after a rest period of 5-10 s. Overall, the NCHRP 9-38 method yielded greater FELs. Without binder modification and/or high binder content, both methods provided similar FELs, if a rest period longer than 5 s was entered in the NCHRP 9-44A model. Generally, the NCHRP 9-44A-predicted FELs produced thicker layers. However, for conventional asphalt mixtures, both sets of FEL yielded similar thicknesses, if the NCHRP 9-44A model applied a rest period exceeding 5 s. The NCHRP 9-44A model's predictive capability will increase if it is recalibrated with mixtures containing modified binder and/or higher binder contents.

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