Short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system

Alas, Mustafa (2022) Short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system. Jurnal Kejuruteraan, 34 (4). pp. 719-727. ISSN 0128-0198


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The influence of polymer/nanocomposites (Acrylete-Styrene-Acrylonitrile (ASA)/ Nanosilica (Si)) asphalt binder aging and performance characteristics was investigated. ASA was used at 5% while nanosilcia was blended in 3, 5 and 7% concentrations by the weight of asphalt. Temperature sensitivity, aging resistance and viscoelastic properties of the asphalt binders were evaluated by conducting physical and dynamic shear rheometer (DSR) testing procedures. The tests were performed under unaged and short-term aged conditions by simulating the aging of asphalt in a Rolling thin film oven (RTFO). Additionally, the Adaptive Neuro-Fuzzy Inference System (ANFIS) modelling technique was adopted to predict the short-term aged behaviour of asphalt binders by using the viscoelastic properties of asphalt in an unaged state. The experimental outcomes from the DSR tests showed that the complex modulus (G*) was increased and the phase angle (δ) was reduced for the modified binders, indicating an improvement in the viscoelastic properties compared to the control asphalt binder. Furthermore, the considerably small difference in the G* and δ between the binders in unaged and RTFO aged states indicated that the modifiers had a positive effect in terms of improving the aging resistance of the asphalt binders. Moreover, the ANFIS model prediction capacity, which was assessed by the Coefficient of Determination (R2) and Mean Squared Error (MSE) and Mean Average Percentage Error (MAPE) was shown to be capable of accurately predicting the short term-aging behaviour of asphalt binders from the asphalt binder viscoelastic properties in an unaged state with an R2 value of 0.977, MSE of 0.00032 and MAPE of 0.286.

Item Type:Article
Keywords:Polymer nanocomposite; Acrylete-styrene-acrylonitrile; Nanosilica; Dynamic shear rheometer; Short-term aging; Artificial intelligence
Journal:Jurnal Kejuruteraan
ID Code:20339
Deposited By: ms aida -
Deposited On:26 Oct 2022 07:30
Last Modified:02 Nov 2022 01:01

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