Please use this identifier to cite or link to this item: https://doi.org/10.1061/(ASCE)0733-947X(2004)130:5(675)
Title: Rutting prediction of asphalt pavement layer using C-φ model
Authors: Fwa, T.F. 
Tan, S.A. 
Zhu, L.Y. 
Issue Date: Sep-2004
Citation: Fwa, T.F., Tan, S.A., Zhu, L.Y. (2004-09). Rutting prediction of asphalt pavement layer using C-φ model. Journal of Transportation Engineering 130 (5) : 675-683. ScholarBank@NUS Repository. https://doi.org/10.1061/(ASCE)0733-947X(2004)130:5(675)
Abstract: Past research has shown that the concept of C-φ (cohesion and angle of friction) can be applied for asphalt paving mix design. It has also been established that the C-φ model is able to analyze the behavior of asphalt pavement under load, thereby permitting the incorporation of mechanistic or semimechanistic distress models into asphalt mix design as well as pavement thickness design. Therefore the C-φ concept offers a useful basis for an integrated procedure for asphalt paving mix design and asphalt pavement design. This paper further illustrates the usefulness of the C-φ based approach by developing a rutting prediction model based on the C-φ model. The proposed rutting prediction model employs the widely adopted expression of power relationship as the basic equation for prediction of cumulative damage. The basic expression is modified by incorporating the following effects: (1) the effect of load through a stress ratio computed using the C-φ concept, (2) the effect of temperature, and (3) the effect of loading speed. The applicability of the model is demonstrated using laboratory wheel tracking tests on three different mix types. A proposed procedure of applyłng the rut depth prediction model for estimation of rut depths in in-service pavements is also outlined. © ASCE.
Source Title: Journal of Transportation Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/66117
ISSN: 0733947X
DOI: 10.1061/(ASCE)0733-947X(2004)130:5(675)
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.