A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Laboratory Method to Characterize Coarse Aggregate Segregation for HMA
Aggregate gradation segregation in asphalt mixtures can result in early damage and reduced durability in asphalt pavement. However, presently, most methods of segregation detection can be performed only after the design of hot-mix asphalt (HMA) or asphalt paving is completed. To identify the segregation characteristics of different aggregate gradations in the mix design of HMA, a simple laboratory method was developed that includes the definition of evaluation indicator of segregation degree for coarse aggregate gradation and the corresponding testing apparatus. In addition, the model for evaluating coarse aggregate segregation was established using a multivariate nonlinear regression method. Based on the model for evaluating coarse aggregate segregation, a prediction method for HMA segregation was proposed. The results of an application case showed that the models for evaluating coarse aggregate segregation and prediction method for HMA segregation are feasible and reasonable. The method to characterize coarse aggregate segregation presented in this paper may help in optimizing the design of aggregate gradation in HMA.
Laboratory Method to Characterize Coarse Aggregate Segregation for HMA
Aggregate gradation segregation in asphalt mixtures can result in early damage and reduced durability in asphalt pavement. However, presently, most methods of segregation detection can be performed only after the design of hot-mix asphalt (HMA) or asphalt paving is completed. To identify the segregation characteristics of different aggregate gradations in the mix design of HMA, a simple laboratory method was developed that includes the definition of evaluation indicator of segregation degree for coarse aggregate gradation and the corresponding testing apparatus. In addition, the model for evaluating coarse aggregate segregation was established using a multivariate nonlinear regression method. Based on the model for evaluating coarse aggregate segregation, a prediction method for HMA segregation was proposed. The results of an application case showed that the models for evaluating coarse aggregate segregation and prediction method for HMA segregation are feasible and reasonable. The method to characterize coarse aggregate segregation presented in this paper may help in optimizing the design of aggregate gradation in HMA.
Laboratory Method to Characterize Coarse Aggregate Segregation for HMA
Cao, Weidong (author) / Liu, Shutang (author) / Xue, Zhichao (author) / Chen, Luchuan (author) / Zhang, Zhidong (author)
2020-10-23
Article (Journal)
Electronic Resource
Unknown
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