Crumb rubber modified bitumen (CRMB) can be regarded as a binary composite system in which swollen rubber particles are embedded in the bitumen matrix. Previous study has successfully implemented the micromechanics models in predicting the complex moduli of CRMB binders using more representative constituent parameters. In the regime of master curves, while the micromechanics models used predicted well in the high-frequency range, they underestimated the complex modulus in the low-frequency range. The current study aims to further improve the prediction accuracy of micromechanics models for CRMB by considering the interparticle interactions. To accomplish this goal, a new reinforcement mechanism called chain entanglement effect was introduced to account for the interparticle interaction effect. Results show that the polymer chain entanglement effect accounts for the underestimation of complex modulus and lack of elasticity (overestimation of phase angle) for CRMB at high temperatures/low frequencies. The mechanical properties of bitumen matrix and entangled polymer network can be determined based on the rubber content. The introduction of the entangled polymer network to the generalized self-consistent model significantly improved the prediction accuracy for both complex modulus and phase angle in the whole frequency range. In summary, by incorporating the physio-chemical interaction mechanism into the currently available models, a new dedicated micromechanics model for predicting the mechanical properties of CRMB has been developed. The predicted viscoelastic behaviors can thereafter be used as inputs for an improved mix design.


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    Title :

    Micromechanics-Based Viscoelasticity Predictions of Crumb Rubber Modified Bitumen Considering Polymer Network Effects


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2022-05-05




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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