Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Prediction Model of Asphalt Content of Asphalt Mixture Based on Dielectric Properties
The rapid detection of asphalt content in asphalt mixture is of great significance to the quality evaluation of asphalt pavement. Based on the dielectric properties of an asphalt mixture, the prediction model of asphalt content is deduced theoretically using three types of dielectric models: Lichtenecker-Rother (L-R) model, Rayleigh model, and Bottcher equation. Under the condition of laboratory mixing at room temperature (about 20–25°C), a dielectric test of asphalt mixture is conducted to verify the applicability of the model. The test results indicate that the dielectric constant of the asphalt mixture is inversely proportional to the asphalt content and directly proportional to the aggregate size of the mixture. Among the models, the Rayleigh model has a wide range of applications and exhibits a high accuracy, with an average relative error of only 1.86%. The results provide a theoretical basis for the nondestructive testing of asphalt pavements using ground-penetrating radar.
Prediction Model of Asphalt Content of Asphalt Mixture Based on Dielectric Properties
The rapid detection of asphalt content in asphalt mixture is of great significance to the quality evaluation of asphalt pavement. Based on the dielectric properties of an asphalt mixture, the prediction model of asphalt content is deduced theoretically using three types of dielectric models: Lichtenecker-Rother (L-R) model, Rayleigh model, and Bottcher equation. Under the condition of laboratory mixing at room temperature (about 20–25°C), a dielectric test of asphalt mixture is conducted to verify the applicability of the model. The test results indicate that the dielectric constant of the asphalt mixture is inversely proportional to the asphalt content and directly proportional to the aggregate size of the mixture. Among the models, the Rayleigh model has a wide range of applications and exhibits a high accuracy, with an average relative error of only 1.86%. The results provide a theoretical basis for the nondestructive testing of asphalt pavements using ground-penetrating radar.
Prediction Model of Asphalt Content of Asphalt Mixture Based on Dielectric Properties
Yanhui Zhong (Autor:in) / Yilong Wang (Autor:in) / Bei Zhang (Autor:in) / Xiaolong Li (Autor:in) / Songtao Li (Autor:in) / Yanmei Zhong (Autor:in) / Meimei Hao (Autor:in) / Yanlong Gao (Autor:in)
2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Metadata by DOAJ is licensed under CC BY-SA 1.0
Asphalt content prediction model of asphalt mixtures based on dielectric properties
Online Contents | 2023
|Asphalt content prediction model of asphalt mixtures based on dielectric properties
Springer Verlag | 2023
|Creep Properties of Asphalt Binder, Asphalt Mastic and Asphalt Mixture
Springer Verlag | 2021
|