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Asphalt content prediction model of asphalt mixtures based on dielectric properties

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Abstract

Asphalt content, one of the important indicators of asphalt pavement quality evaluation, is also an important basis for evaluating the segregation degrees of asphalt pavement. Therefore, the realization of the nondestructive measurement of the asphalt content of asphalt pavement is of great significance for the evaluation of the quality of the pavement and the determination of the segregation degrees. In order to realize the nondestructive detection of the asphalt content of asphalt mixtures, this study established five asphalt mixture prediction models through theoretical derivation based on five composite dielectric models. Through the relative permittivity measurement tests of six types of asphalt mixtures with different asphalt content, the accuracy of the asphalt content prediction models of various asphalt mixtures was compared and verified. After comparing the accuracy, the asphalt content prediction model based on the Rayleigh model was found to have strong applicability for any type of asphalt mixture and can be used as a basic theoretical model for the asphalt content prediction of asphalt mixtures. In addition, this study combined the asphalt content prediction models of asphalt mixtures and set the relative permittivity judgment threshold of the asphalt pavement segregation degrees based on the boundary value of void ratio and asphalt content. Moreover, the research theoretically realized the nondestructive judgment of the asphalt pavement segregation degrees based on the relative permittivity of the asphalt pavement, which has important practical significance in evaluating the quality of the asphalt pavement and making targeted maintenance decisions for different segregation degrees of asphalt pavement.

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Acknowledgements

The authors acknowledge the financial support of the 973 Program of the Ministry of Science and Technology of China (Project No. 2015CB060100) and the Key Research and Development Project of Science and Technology Department of Hubei Province of China (Project No. 2020BCA085). Special thanks to the 1,000-Youth Elite Program of China for the start-up funds used to purchase laboratory equipment crucial to this research.

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Authors and Affiliations

  1. Hubei Provincial Communications Investment Group Co., Ltd, 36 Longyang Avenue, Wuhan, 430051, Hubei Province, China

    Xiaohe Yu & Zaiwu Zhang

  2. School of Transportation, Wuhan University of Technology, Hubei Highway Engineering Research Center, 1178 Heping Avenue, Wuhan, 430063, Hubei Province, China

    Rong Luo, Tingting Huang & Manzhe Xiao

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  1. Xiaohe Yu
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Yu, X., Zhang, Z., Luo, R. et al. Asphalt content prediction model of asphalt mixtures based on dielectric properties. Mater Struct 56, 10 (2023). https://doi.org/10.1617/s11527-022-02095-4

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