Determination and Monitoring of Key Construction Control Indices for Low-Temperature Performance of Asphalt Mixtures Based on BIM Platform
Author(s): |
Yulong Zhao
Ying Gao Ke Zhang Yao Zhang Mingce Yu |
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Medium: | journal article |
Language(s): | English |
Published in: | Advances in Civil Engineering, January 2021, v. 2021 |
Page(s): | 1-20 |
DOI: | 10.1155/2021/6637684 |
Abstract: |
The construction control indices were commonly used to ensure the quality of asphalt layers in the construction process. However, the relationship between the construction control indices and the low-temperature performance of asphalt layers is not clear. The purpose of this paper was to investigate the effect of the variations of the construction control indices on the low-temperature performance of asphalt mixtures to determine the key construction control indices, and propose the method for the monitoring of these indices using the Building Information Modeling (BIM) platform. The low-temperature performance of asphalt mixtures was evaluated by the semicircular bend (SCB) test. A new prediction model of critical strain energy release rate was established to evaluate the low-temperature performance of the asphalt layer. Five factors are considered for the low-temperature performance, which are the gradation and asphalt-aggregate ratio in the asphalt mixture plant, rolling temperature, gradation segregation, and temperature segregation. Orthogonal test (OT) results indicated that the order of importance of factors affecting the low-temperature performance is asphalt-stone ratio, gradation, and molding temperature. The influences of gradation segregation and temperature segregation on the low-temperature performance were quantified in this study. Furthermore, the construction control indices were monitored by the BIM platform developed in this research. In the construction process of the asphalt layer, the gradation variation caused by the segregation should be paid more attention to ensure the low-temperature performance of the pavement. |
Copyright: | © Yulong Zhao et al. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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10604193 - Published on:
26/04/2021 - Last updated on:
02/06/2021