Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Predicting the rutting behaviour of natural fibre-reinforced cold mix asphalt using the finite element method

Shanbara, HK, Ruddock, F and Atherton, W (2018) Predicting the rutting behaviour of natural fibre-reinforced cold mix asphalt using the finite element method. Construction and Building Materials, 167. pp. 907-917. ISSN 0950-0618

[img] Text
Predicting the rutting behaviour of natural fibre-reinforced cold mix asphalt using the finite element method.pdf - Accepted Version
Restricted to Repository staff only until 22 February 2020.
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB)

Abstract

This paper describes the development of a three-dimensional (3-D), finite element model (FEM) of flexible pavements made with cold mix asphalt (CMA), which has itself been reinforced with two different natural fibres: jute and coir. A 3-D finite element model was employed to predict the viscoelastic response of flexible CMA pavements when subjected to multiple axle loads, different bituminous material properties, tire speeds and temperatures. The analysis was conducted by the finite element computer package ABAQUS/STANDARD. The pavements were subject to cyclic and static loading conditions to test for permanent deformation (rutting). The accuracy of the developed model was validated by comparing the predicted results with those measured in the lab. Reinforced and unreinforced CMA mixture models were simulated in this research. The results indicate that the CMA mixtures reinforced with natural fibres, are effective in mitigating permanent deformation (rutting). These reinforcing materials can extend the service life of flexible pavements. © 2018 Elsevier Ltd

Item Type: Article
Uncontrolled Keywords: 0905 Civil Engineering, 1202 Building
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TH Building construction
Divisions: Civil Engineering
Publisher: Elsevier
Date Deposited: 27 Apr 2018 11:14
Last Modified: 15 Sep 2018 09:27
DOI or Identification number: 10.1016/j.conbuildmat.2018.02.072
URI: http://researchonline.ljmu.ac.uk/id/eprint/8593

Actions (login required)

View Item View Item