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Optimizing Asphalt Surface Course Compaction: Insights from Aggregate Triaxial Acceleration Responses
The compaction quality of asphalt surface courses has a significant impact on the overall performance of asphalt pavements, but the dynamic response and compaction degree variations of different asphalt surface courses (top, middle, and bottom surface courses) during vibrational compaction have stil...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673026/ https://www.ncbi.nlm.nih.gov/pubmed/38005166 http://dx.doi.org/10.3390/ma16227239 |
Sumario: | The compaction quality of asphalt surface courses has a significant impact on the overall performance of asphalt pavements, but the dynamic response and compaction degree variations of different asphalt surface courses (top, middle, and bottom surface courses) during vibrational compaction have still received limited research. SmartRock sensors can be utilized to monitor aggregate acceleration in real-time. This study aims to address this gap using SmartRock sensor technology to further understand the compaction mechanisms of different asphalt surface courses from a particle perspective, as well as the relationship between aggregate acceleration and compaction degree. The results indicate that the rolling of steel drums induces a significant alteration of the aggregate acceleration along the roller’s rolling direction, primarily resulting in horizontal shearing in that direction. As distance increases, vibration waves gradually attenuate on both sides of vibrating drums, and surface course thickness and gradation significantly affect acceleration amplitude. There is a linear correlation between triaxial aggregate acceleration and compaction degree, with the vertical correlation being the strongest. Finally, an empirical relationship between triaxial acceleration and pavement compaction degree was established, providing a basis for predicting the asphalt surface course density. These findings enhance our understanding of pavement compaction mechanisms and promote innovation in asphalt pavement compaction and quality control methods. |
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