Short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system
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, ag...
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Penerbit Universiti Kebangsaan Malaysia
2022
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my-ukm.journal.203392022-11-02T01:01:27Z http://journalarticle.ukm.my/20339/ Short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system Alas, Mustafa 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. Penerbit Universiti Kebangsaan Malaysia 2022 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/20339/1/19.pdf 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 https://www.ukm.my/jkukm/volume-3404-2022/ |
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| description |
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. |
| format |
Article |
| author |
Alas, Mustafa |
| spellingShingle |
Alas, Mustafa Short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system |
| author_facet |
Alas, Mustafa |
| author_sort |
Alas, Mustafa |
| title |
Short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system |
| title_short |
Short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system |
| title_full |
Short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system |
| title_fullStr |
Short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system |
| title_full_unstemmed |
Short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system |
| title_sort |
short-term aging performance and simulation of modified binders using adaptive neuro-fuzzy inference system |
| publisher |
Penerbit Universiti Kebangsaan Malaysia |
| publishDate |
2022 |
| url |
http://journalarticle.ukm.my/20339/1/19.pdf http://journalarticle.ukm.my/20339/ https://www.ukm.my/jkukm/volume-3404-2022/ |
| _version_ |
1748704126805475328 |
| score |
13.211869 |