4.6 Article

Numerical evaluation of pavement design parameters for the fatigue cracking and rutting performance of asphalt pavements

期刊

MATERIALS AND STRUCTURES
卷 49, 期 9, 页码 3619-3634

出版社

SPRINGER
DOI: 10.1617/s11527-015-0744-x

关键词

Asphalt; Pavement; Pavement design; Fatigue cracking; Rutting; LVECD program; Field condition

资金

  1. Federal Highway Administration [DTFH61-08-H-00005]
  2. FHWA

向作者/读者索取更多资源

Over recent years, significant research has been conducted to investigate ways to predict fatigue cracking and permanent deformation (rutting), which are two common distresses found in asphalt pavements. These distresses are affected by material properties, environmental conditions, and the pavement's structure. This paper investigates common pavement design parameters, including surface mixture type, base layer thickness, base layer type, sub-base layer thickness, and an anti-frost layer, with regard to the asphalt pavement performance of the Korea Expressway Corporation (KEC) test road. Test roads are often regarded as the most realistic tools for evaluating the effects of various parameters because they are subjected to real traffic and environmental factors. The KEC test road is 7.7 km long and was constructed with the aim of developing a Korean mechanistic-empirical pavement design guide. According to the findings, the surface layer type, base layer thickness, and base layer material type were found to affect the fatigue cracking and rutting performance, whereas the sub-base thickness and anti-frost layer were found not to affect the amount of distress significantly. The newly developed 'layered viscoelastic pavement analysis for critical distresses' (LVECD) program was able to capture the effects of the changes in the aforementioned parameters on the amount of cracking and rut depths. Reasonable agreement was found between the LVECD predictions and the field distress measurements. However, it remains necessary to develop a laboratory-to-field transfer function in order to obtain more accurate field performance predictions.

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