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

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) wa...

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Autores principales: Abdulnaser M Al-Sabaeei, Madzlan B Napiah, Muslich H Sutanto, Suzielah Rahmad, Nur Izzi Md Yusoff, Wesam S Alaloul
Formato: article
Lenguaje:EN
Publicado: Elsevier 2021
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Acceso en línea:https://doaj.org/article/d1cf9b8937c443f7a423cdb3acfde582
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Sumario: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.