Determination of rheological properties of bio-asphalt binders through experimental and multilayer feed-forward neural network methods

Ain Shams Engineering Journal

Muslich H Sutanto¹  Madzlan B Napiah²  Nur Izzi Md Yusoff²  Wesam S Alaloul³  Suzielah Rahmad³  Abdulnaser M Al-Sabaeei³ 

[1] Corresponding author.;Environmental Engineering, UniversitiTeknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia;;Department of Civil &

关键词: Bio-asphalt;    Crude palm oil;    Rheological properties;    Artificial neural network;   

DOI  :  

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown