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      Further Investigation on Damage Model of Eco-Friendly Basalt Fiber Modified Asphalt Mixture under Freeze-Thaw Cycles

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      Applied Sciences
      MDPI AG

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          Abstract

          The main distresses of asphalt pavements in seasonally frozen regions are due to the effects of water action, freeze-thaw cycles, and so on. Basalt fiber, as an eco-friendly mineral fiber with high mechanical performance, has been adopted to reinforce asphalt mixture in order to improve its mechanical properties. This study investigated the freeze-thaw damage characteristics of asphalt mixtures reinforced with eco-friendly basalt fiber by volume and mechanical properties—air voids, splitting tensile strength, and indirect tensile stiffness modulus tests. Test results indicated that asphalt mixtures reinforced with eco-friendly basalt fiber had better mechanical properties (i.e., splitting tensile strength and indirect tensile stiffness modulus) before and after freeze-thaw cycles. Furthermore, this study developed logistic damage models of asphalt mixtures in terms of the damage characteristics, and found that adding basalt fiber could significantly reduce the damage degree by about 25%, and slow down the damage grow rate by about 45% compared with control group without basalt fiber. Moreover, multi-variable grey models (GM) (1,N) were established for modelling the damage characteristics of asphalt mixtures under the effect of freeze-thaw cycles. GM (1,3) was proven as an effective prediction model to perform better in prediction accuracy compared to GM (1,2).

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          Most cited references47

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          Investigation of rutting performance of asphalt mixtures containing polymer modifiers

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            Characterization of asphalt mastics reinforced with basalt fibers

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              Investigation of rheological and fatigue properties of asphalt mixtures containing polyester fibers

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                Author and article information

                Contributors
                Journal
                ASPCC7
                Applied Sciences
                Applied Sciences
                MDPI AG
                2076-3417
                January 2019
                December 25 2018
                : 9
                : 1
                : 60
                Article
                10.3390/app9010060
                cf7686c1-6478-4c42-a019-d0cddceefa8d
                © 2018

                https://creativecommons.org/licenses/by/4.0/

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