Effect of warm additives on rutting and fatigue behaviour of asphalt mixtures

2013 ◽  
Vol 47 ◽  
pp. 240-244 ◽  
Author(s):  
Elsa Sanchez-Alonso ◽  
Angel Vega-Zamanillo ◽  
Miguel Angel Calzada-Perez ◽  
Daniel Castro-Fresno
2018 ◽  
Vol 51 (4) ◽  
Author(s):  
Elsa Sanchez-Alonso ◽  
Angel Vega-Zamanillo ◽  
Miguel Angel Calzada-Perez ◽  
Daniel Castro-Fresno

2020 ◽  
Vol 53 (4) ◽  
Author(s):  
Francisco Morea ◽  
Miguel Sol-Sanchez ◽  
Fernando Moreno-Navarro ◽  
Raúl Zerbino

Author(s):  
Silvio Lisboa Schuster ◽  
Cléber Faccin ◽  
Fernando Dekeper Boeira ◽  
Luciano Pivoto Specht ◽  
Deividi da Silva Pereira ◽  
...  

1987 ◽  
Vol 48 (C3) ◽  
pp. C3-745-C3-751 ◽  
Author(s):  
J. SCHNEIDER ◽  
H.-J. GUDLADT ◽  
V. GEROLD

2019 ◽  
Author(s):  
Teng Man

The compaction of asphalt mixture is crucial to the mechanical properties and the maintenance of the pavement. However, the mix design, which based on the compaction properties, remains largely on empirical data. We found difficulties to relate the aggregate size distribution and the asphalt binder properties to the compaction behavior in both the field and laboratory compaction of asphalt mixtures. In this paper, we would like to propose a simple hybrid model to predict the compaction of asphalt mixtures. In this model, we divided the compaction process into two mechanisms: (i) visco-plastic deformation of an ordered thickly-coated granular assembly, and (ii) the transition from an ordered system to a disordered system due to particle rearrangement. This model could take into account both the viscous properties of the asphalt binder and grain size distributions of the aggregates. Additionally, we suggest to use the discrete element method to understand the particle rearrangement during the compaction process. This model is calibrated based on the SuperPave gyratory compaction tests in the pavement lab. In the end, we compared the model results to experimental data to show that this model prediction had a good agreement with the experiments, thus, had great potentials to be implemented to improve the design of asphalt mixtures.


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