Technical Papers
Sep 19, 2022

Modeling the Behavior of an Aggregate Skeleton during Static Creep of an Asphalt Mixture Based on a Three-Dimensional Mesoscale Random Model

Publication: Journal of Materials in Civil Engineering
Volume 34, Issue 12

Abstract

The aggregate skeleton and its evolution under external loads are crucial to evaluate the mechanical properties of the asphalt mixture. This study developed a method to identify the three-dimensionally (3D) aggregate skeleton based on geometry information. The proposed method can identify the evolution process of the aggregate skeleton during loading in the finite element method (FEM). Random models based on the Gilbert–Johnson–Keerthi (GJK) algorithm are used to study the influence of the concave–convex degree of the gradation curve and the magnitude of the creep load on the aggregate skeleton during the creep process. The results indicate that the aggregate skeleton undergoes three stages during creep: aggregate redistribution, skeleton formation, and skeleton failure after reaching the ultimate load, while the increase of load causes the aggregate skeleton to lose its bearing capacity faster. More coarse aggregate raises the strength of the aggregate skeleton, but it is more likely to break down quickly once it reaches the strength. More fine aggregate enhances the stability of the aggregate skeleton. The proposed identification method can serve as a general tool to investigate the evolution process of the internal aggregate structure of the asphalt mixture.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The research reported in this article is supported by the National High Technology Research and Development Program of China (2021YFC3001901 and 2021YFC3001903) and the National Natural Science Foundation of China (11972216 and 11802162).

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Go to Journal of Materials in Civil Engineering
Journal of Materials in Civil Engineering
Volume 34Issue 12December 2022

History

Received: Dec 10, 2021
Accepted: Mar 4, 2022
Published online: Sep 19, 2022
Published in print: Dec 1, 2022
Discussion open until: Feb 19, 2023

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Master’s Candidate, Engineering Research Center of Eco-Environment in Three Gorges Reservoir Region, Ministry of Education, China Three Gorges Univ., Yichang 443002, China; Dept. of Engineering Mechanics, College of Hydraulic & Environmental Engineering, China Three Gorges Univ., Yichang 443002, China. Email: [email protected]
Professor, Engineering Research Center of Eco-Environment in Three Gorges Reservoir Region, Ministry of Education, China Three Gorges Univ., Yichang 443002, China; Dept. of Engineering Mechanics, College of Hydraulic & Environmental Engineering, China Three Gorges Univ., Yichang 443002, China. Email: [email protected]
Associate Professor, Engineering Research Center of Eco-Environment in Three Gorges Reservoir Region, Ministry of Education, China Three Gorges Univ., Yichang 443002, China; Dept. of Engineering Mechanics, College of Hydraulic & Environmental Engineering, China Three Gorges Univ., Yichang 443002, China (corresponding author). Email: [email protected]
Professor, Engineering Research Center of Eco-Environment in Three Gorges Reservoir Region, Ministry of Education, China Three Gorges Univ., Yichang 443002, China; Director, Dept. of Hydropower Engineering, College of Hydraulic & Environmental Engineering, China Three Gorges Univ., Yichang 443002, China. Email: [email protected]

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Cited by

  • Data-Mining Framework Integrating 3D Random Aggregate Method and Finite-Element Method for Mesoscopic Simulation of Asphalt Concrete, Journal of Transportation Engineering, Part B: Pavements, 10.1061/JPEODX.PVENG-1505, 150, 3, (2024).
  • Evaluation of Steel Slag Optimal Replacement in Asphalt Mixture under Microwave Heating Based on 3D Polyhedral Aggregate Electromagnetic-Thermal Meso-Model, Coatings, 10.3390/coatings13030517, 13, 3, (517), (2023).

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