TY  - JOUR
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105060591&doi=10.1016%2fj.asej.2021.04.003&partnerID=40&md5=0601c2c81ccbc5c062dbfc70eac849cc
JF  - Ain Shams Engineering Journal
A1  - Al-Sabaeei, A.M.
A1  - Napiah, M.B.
A1  - Sutanto, M.H.
A1  - Rahmad, S.
A1  - Yusoff, N.I.M.
A1  - Alaloul, W.S.
VL  - 12
Y1  - 2021///
N2  - 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
IS  - 4
KW  - Asphalt; Binders; Complex networks; Multilayer neural networks; Multilayers; Palm oil; Rheology
KW  -  Asphalt binders; Base asphalt; Complex modulus; Crude palm oil; Dynamic shear rheometer; Modelling method; Multilayer feedforward neural networks; Rheological property
KW  -  Feedforward neural networks
ID  - scholars14230
EP  - 3493
SN  - 20904479
PB  - Ain Shams University
N1  - cited By 11
SP  - 3485
TI  - Determination of rheological properties of bio-asphalt binders through experimental and multilayer feed-forward neural network methods
AV  - none
ER  -