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Pavement Analysis and Design by Multiphysics Reconstructing Algorithm for the Virtual Asphalt Mixture Based on the Discrete-Element Method

Autor(en):




Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Advances in Civil Engineering, , v. 2018
Seite(n): 1-11
DOI: 10.1155/2018/5180562
Abstrakt:

Based on the Particle Flow Code in Two dimensions (PFC2D), an algorithm for modeling the two-dimensional virtual asphalt mixture was proposed in this study. By combining the AIMS scanning technology (Aggregate Imaging Measurement System) with the designed stochastic algorithm, the virtual coarse aggregates could be generated rapidly and precisely. Different from the conventional methods, the contour shapes of the coarse aggregates were rebuilt only to balance the shape modeling precision and simulation efficiency. Then by distributing the coarse particles within container, virtual skeletons were formed firstly. An innovate algorithm was proposed afterwards to distinguish the external and internal area of the coarse aggregates and then model the mastic part by filling the irregular hollow shape with uniformly arranged balls. By deleting the mastic balls randomly, the voids were reconstructed consistent with the actual ratio. In the end, the virtual uniaxial compressive tests of AC-16 were simulated within PFC2D and the dynamic modulus at different load frequencies was predicted. The results indicated that the proposed algorithm could not only model the asphalt mixture precisely but also characterized its mechanical behavior as well.

Copyright: © 2018 Danhua Wang et al.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

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  • Reference-ID
    10176769
  • Veröffentlicht am:
    30.11.2018
  • Geändert am:
    02.06.2021
 
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