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A platform for research: civil engineering, architecture and urbanism
Asphalt content prediction model of asphalt mixtures based on dielectric properties
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.
Asphalt content prediction model of asphalt mixtures based on dielectric properties
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.
Asphalt content prediction model of asphalt mixtures based on dielectric properties
Mater Struct
Yu, Xiaohe (author) / Zhang, Zaiwu (author) / Luo, Rong (author) / Huang, Tingting (author) / Xiao, Manzhe (author)
2023-02-01
Article (Journal)
Electronic Resource
English
Asphalt content prediction model of asphalt mixtures based on dielectric properties
| Online Contents | 2023
Prediction Model of Asphalt Content of Asphalt Mixture Based on Dielectric Properties
| DOAJ | 2020