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Comparison of BBR results of EVA polymer and nano-CaCO3-modified bitumen using burger model, relaxation modulus, dissipation energy ratio, ANOVA, and artificial neural networks

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Abstract

Temperature and loading time influence the viscoelastic behavior of bitumen. The present study aimed to compare the results of some analyses including Burger model, relaxation modulus, dissipation energy ratio, statistical analysis of ANOVA and artificial neural networks (ANN) and to investigate the viscoelastic behavior of bitumen modified with nano-CaCO3 (NCCO) and ethylene-vinyl acetate (EVA). To this end, the Bending Beam Rheometer (BBR) tests were conducted on NCCO- and EVA-modified bitumen at various temperatures. According to the previous studies, NCCO was utilized for 4% and 6% weight of neat bitumen and the BBR test was conducted at low temperatures of −6 and −12°C. In addition, EVA was utilized for 6% weight of neat bitumen and the BBR test was conducted at low temperatures of −6, −12 and −18°C. Hence, results of four models showed that EVA-modified bitumen could improve the viscoelastic behavior of bitumen in low temperatures and NCCO had a negligible effect on improving bitumen. Finally, results of the Burger model, relaxation modulus, and dissipation energy ratio were compared and based on these results, the relaxation modulus and dissipation energy ratio were more accurate than the Burger model. Additionally, results of the statistical analysis of ANOVA were weaker than the artificial neural networks (ANN) method.

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Authors and Affiliations

  1. Civil Engineering Department, KN Toosi University of Technology, Tehran, Iran

    Mansour Fakhri

  2. Department of Road and Transportation Science and Research Branch, Islamic Azad University, Tehran, Iran

    Atousa Kianfar

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  1. Mansour Fakhri
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  2. Atousa Kianfar
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Correspondence to Atousa Kianfar.

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Peer review under responsibility of Chinese Society of Pavement Engineering.

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Fakhri, M., Kianfar, A. Comparison of BBR results of EVA polymer and nano-CaCO3-modified bitumen using burger model, relaxation modulus, dissipation energy ratio, ANOVA, and artificial neural networks. Int. J. Pavement Res. Technol. 14, 85–97 (2021). https://doi.org/10.1007/s42947-020-0006-3

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  • DOI: https://doi.org/10.1007/s42947-020-0006-3

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