2022
DOI: 10.1016/j.conbuildmat.2022.129452
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Refined decomposition: A new separation method for RAP materials and its effect on aggregate properties

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Cited by 24 publications
(11 citation statements)
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“…The combination of Tables 3-5 and Figure 6 shows that for the RAM containing 50% RAP, the curve of the RAM-FR was significantly narrower than that of the RAM-UR, implying that the dispersion of road performance test results for the RAM-FR became lower. This indicates that the road performance variability of the RAM can be effectively controlled by the fractionation process of RAP material [38]. Compared with the curves of the RAM-UR, the curves of the RAM-FR showed a significant forward shift, indicating that the road performance of the RAM can be improved by controlling the variability.…”
Section: Analysis Of the Variability In Road Properties For Recycled ...mentioning
confidence: 88%
“…The combination of Tables 3-5 and Figure 6 shows that for the RAM containing 50% RAP, the curve of the RAM-FR was significantly narrower than that of the RAM-UR, implying that the dispersion of road performance test results for the RAM-FR became lower. This indicates that the road performance variability of the RAM can be effectively controlled by the fractionation process of RAP material [38]. Compared with the curves of the RAM-UR, the curves of the RAM-FR showed a significant forward shift, indicating that the road performance of the RAM can be improved by controlling the variability.…”
Section: Analysis Of the Variability In Road Properties For Recycled ...mentioning
confidence: 88%
“…In order to ensure the quality of recycled asphalt mixtures, the general plant-mixed thermal regeneration requires a ratio of RAP addition of 15% to 30% [8][9][10]. For this reason, researchers have proposed asphalt and mineral separation techniques, including physical refined separation methods [11][12][13],…”
Section: Introductionmentioning
confidence: 99%
“…With the development of artificial intelligence, machine learning models have attracted more and more attention from civil engineers because of their high prediction accuracy and high prediction efficiency [31,32], and have been successfully applied to the prediction of concrete strength [33][34][35][36][37]. Hoang et al [38] proposed using Gaussian Process Regression (GPR) to simulate the mechanical properties of high-performance concrete (HPC) and compared the prediction effect of GPR with the prediction models of least squares support vector machines and artificial neural networks.…”
Section: Introductionmentioning
confidence: 99%