Effect of Skeleton Networks on the Bearing Capacity of Large Stone Porous Asphalt Mixes Using the Discrete Element Method
Publication: Journal of Materials in Civil Engineering
Volume 36, Issue 4
Abstract
Large stone porous asphalt mixes (LSPMs) have the characteristics of large gaps, large content of coarse aggregate, and large particle size of coarse aggregate. Compared with the traditional asphalt-treated base (ATB), LSPM forms a more obvious skeleton structure in the process of bearing load. In this study, the discrete element method (DEM) model of LSPM is established, and an evaluation method for studying the bearing capacity and high-temperature performance of LSPM through an internal skeleton network is proposed. Firstly, the DEM model of asphalt mixture with different gradations is established, and the virtual uniaxial penetration test is carried out. Then, the performance of the skeleton network inside the asphalt mixture is analyzed, and the contribution of each group of aggregates to the skeleton network is further studied. The experimental results show that the bearing capacity of an asphalt mixture is closely related to the performance of internal skeleton network. The skeleton network inside the asphalt mixture is extracted by the value of the contact force, the angle between the contacts, and the contact continuity. When the skeleton network has better bearing capacity and load-transfer capacity, the asphalt mixture can bear more external load in the virtual penetration test. The contribution of different coarse aggregates to the skeleton network is analyzed from four perspectives: total contact force, vertical work, contact number, and effective coordination number. The aggregates of 19–26.5 and 4.75–9.5 mm constitute the main body of the load-transfer path and play a major role in bearing and transmitting the load in the skeleton network.
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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
This work was supported by the National Natural Science Foundation of China (No. 52078132) and the Scientific Research Foundation of Graduate School of Southeast University. The authors gratefully acknowledge their financial support. In addition, thank you to all the authors in the following references.
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Published In
Journal of Materials in Civil Engineering
Volume 36 • Issue 4 • April 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Aug 24, 2023
Accepted: Oct 2, 2023
Published online: Jan 27, 2024
Published in print: Apr 1, 2024
Discussion open until: Jun 27, 2024
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