Dielectric Model Considering Interface Effects for Asphalt Mixtures Based on Spherical Polarization Theory

Accurate measurement and calculation of the dielectric constant of asphalt mixture serve as fundamental steps for enhancing the precision of ground-penetrating radar (GPR) in asphalt pavement quality inspection. To establish a dielectric model that precisely captures the structural characteristics of asphalt mixtures, mesostructure and microstructure analyses of the asphalt mixture are conducted based on a multiscale analysis approach; the results are then correlated with the macroscopic dielectric properties of the materials. Leveraging principles from dielectric physics, particularly the spherical polarization theory, a dielectric model for the mesostructure of the hybrid medium is developed (referred to as the improved model). Building upon the improved model, an asphalt mixture dielectric model that considers the microscale interface effect is constructed using the composite sphere combination method (referred to as the presented model). The results demonstrate that the improved model enhances the precision of calculating the dielectric constant of asphalt mastic and mixture by an average of 1.53% and 2.94%, respectively, compared to the original classical model. Moreover, the presented model shows further enhancement in accuracy compared to the improved model. Specifically, the overall average improvement of the presented model over the improved and original classical models is 2.86% and 5.8%, respectively. Notably, the presented model exhibits significantly higher accuracy compared to other classical models (such as the S-K, Looyenga, and Brown models). The research models align more closely with the actual composition of asphalt mixture, resulting in more precise calculation of the dielectric constant. This study offers guidance for enhancing the accuracy of GPR road quality detection and for the application of dielectric properties in the field of intelligent transportation.

Authors

Institutions

Publication Details

Journal
Journal of Materials in Civil Engineering
Published
2025-03-26
DOI
https://doi.org/10.1061/jmcee7.mteng-20031
Citations
2
Primary Topic
Geophysical Methods and Applications
Type
article
Field-Weighted Citation Impact
2.29
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dielectric Model Considering Interface Effects for Asphalt Mixtures Based on Spherical Polarization Theory

Yongding Niu, Yanhui Zhong, Bei Zhang, Yanlong Gao et al.
2 citations
Journal of Materials in Civil Engineering
Geophysical Methods and Applications
2.29
article

Dielectric Model Considering Interface Effects for Asphalt Mixtures Based on Spherical Polarization Theory

Yongding Niu, Yanhui Zhong, Bei Zhang, Yanlong Gao, Quansheng Zang, Baolin Wang, Yaqi Li, Mingyang Ma
article en
2 citations

Abstract

Accurate measurement and calculation of the dielectric constant of asphalt mixture serve as fundamental steps for enhancing the precision of ground-penetrating radar (GPR) in asphalt pavement quality inspection. To establish a dielectric model that precisely captures the structural characteristics of asphalt mixtures, mesostructure and microstructure analyses of the asphalt mixture are conducted based on a multiscale analysis approach; the results are then correlated with the macroscopic dielectric properties of the materials. Leveraging principles from dielectric physics, particularly the spherical polarization theory, a dielectric model for the mesostructure of the hybrid medium is developed (referred to as the improved model). Building upon the improved model, an asphalt mixture dielectric model that considers the microscale interface effect is constructed using the composite sphere combination method (referred to as the presented model). The results demonstrate that the improved model enhances the precision of calculating the dielectric constant of asphalt mastic and mixture by an average of 1.53% and 2.94%, respectively, compared to the original classical model. Moreover, the presented model shows further enhancement in accuracy compared to the improved model. Specifically, the overall average improvement of the presented model over the improved and original classical models is 2.86% and 5.8%, respectively. Notably, the presented model exhibits significantly higher accuracy compared to other classical models (such as the S-K, Looyenga, and Brown models). The research models align more closely with the actual composition of asphalt mixture, resulting in more precise calculation of the dielectric constant. This study offers guidance for enhancing the accuracy of GPR road quality detection and for the application of dielectric properties in the field of intelligent transportation.

Journal of Materials in Civil EngineeringVol. 37(6)
Zhengzhou University (CN), Henan Energy & Chemical Industry Group (China) (CN)
Openalex Percentile: Top 14%
Geophysical Methods and Applications
2.29
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.