Evaluation of static creep of FORTA-FI strengthened asphalt mixtures using experimental, statistical and feed-forward back-propagation ANN techniques

This paper investigates the effect of using different proportions (0%, 1%, 3%, 5%) of FORTA-FI fiber on asphalt mixtures static creep behavior under different compactive efforts (35 blows, 50 blows, 75 blows) and testing temperatures (25°C, 40°C, 55°C). The accumulated micro-strain was found to increase as temperature increases and stiffness modulus was found to decrease as temperature increases. These results are expected due to the viscoelastic nature of asphalt mixtures. Additionally, feed-forward back-propagation Artificial Neural Network (ANN) was utilized in order to build a model that describes and predicts the relationship between deformation and stiffness modulus with multiple variables such as Temperature (Temp), Fiber Content (FC) and Compactive Effort (CE). Evidently, a powerful predictive model was developed with Coefficient of Determination (R²) of 94%. The results using the SPSS statistical software of the two-way and three-way Analysis of Variance (ANOVA) tools showed that temperature and FORTA-FI content have significant interaction effects. Whereas, compactive effort effect on stiffness modulus was insignificant. Further, results obtained using Minitab statistical software confirmed the above findings.

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  • English

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  • Accession Number: 01713749
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 31 2019 3:14PM