Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4912628 | Construction and Building Materials | 2018 | 10 Pages |
Abstract
The objective of this study is to investigate the relationship between long-term skid resistance of epoxy asphalt mixture (EAM) and multiple engineering parameters involving mixture design parameters, construction parameters and operation parameters. Firstly, a database of 124 data sets was obtained, including optimal binder content, aggregate gradation characteristics, bulk specific gravity, air-void content and load repetitions for input parameters, and long-term skid resistance of EAM simulated by an accelerated pavement test for output. Secondly, using the database, an optimized GA-BP neural network model (i.e. GA-BP model) was established to predict the long-term skid resistance, and then a comprehensive sensitivity analysis was conducted to explore the effect of input parameters on the skid-resistant evolution based on the trained neural network. Results show that the optimized GA-BP model can effectively predict the long-term skid resistance of EAM, and the long-term skid resistance has a significant negative correlation with binder content and shape characteristic of aggregate gradation. In addition, bulk specific gravity is the most important factor influencing the long-term skid resistance, and also has the most remarkable interaction effect with other input parameters.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Civil and Structural Engineering
Authors
Dong Zheng, Zhen-dong Qian, Yang Liu, Chang-bo Liu,