eprintid: 14230
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/42/30
datestamp: 2023-11-10 03:28:48
lastmod: 2023-11-10 03:28:48
status_changed: 2023-11-10 01:56:22
type: article
metadata_visibility: show
creators_name: Al-Sabaeei, A.M.
creators_name: Napiah, M.B.
creators_name: Sutanto, M.H.
creators_name: Rahmad, S.
creators_name: Yusoff, N.I.M.
creators_name: Alaloul, W.S.
title: Determination of rheological properties of bio-asphalt binders through experimental and multilayer feed-forward neural network methods
ispublished: pub
keywords: Asphalt; Binders; Complex networks; Multilayer neural networks; Multilayers; Palm oil; Rheology, Asphalt binders; Base asphalt; Complex modulus; Crude palm oil; Dynamic shear rheometer; Modelling method; Multilayer feedforward neural networks; Rheological property, Feedforward neural networks
note: cited By 11
abstract: This study seeks to determine the rheological properties of unaged and RTFO-aged bio-asphalt binders using experimental and modelling methods. Crude palm oil (CPO) was used as a bio-oil at varying percentages of 0, 5, 10 and 15 by total weight of asphalt binder. The dynamic shear rheometer (DSR) was used to investigate the rheological properties of bio-asphalt binders. The multilayer feed-forward neural network method was used to predict the complex modulus and phase angle of bio-asphalt binders by virtue of its ability to learn and adapt. Result of the DSR analysis showed that the complex modulus of bio-asphalt with 5 CPO is almost similar as that of the base asphalt binder, and that higher CPO content resulted in reduced complex modulus and higher phase angle. Result of the modelling shows that all models have an R2 value greater than 0.99, thus indicating the good agreement between the predicted and the experimental results. © 2021 THE AUTHORS
date: 2021
publisher: Ain Shams University
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105060591&doi=10.1016%2fj.asej.2021.04.003&partnerID=40&md5=0601c2c81ccbc5c062dbfc70eac849cc
id_number: 10.1016/j.asej.2021.04.003
full_text_status: none
publication: Ain Shams Engineering Journal
volume: 12
number: 4
pagerange: 3485-3493
refereed: TRUE
issn: 20904479
citation:   Al-Sabaeei, A.M. and Napiah, M.B. and Sutanto, M.H. and Rahmad, S. and Yusoff, N.I.M. and Alaloul, W.S.  (2021) Determination of rheological properties of bio-asphalt binders through experimental and multilayer feed-forward neural network methods.  Ain Shams Engineering Journal, 12 (4).  pp. 3485-3493.  ISSN 20904479