Analysis of long-term performance and snowmelt capacity of anti-freezing asphalt pavement

doi:10.1520/ACEM20200026

CORC > 兰州理工大学 > 兰州理工大学 > 土木工程学院

	Analysis of long-term performance and snowmelt capacity of anti-freezing asphalt pavement
	Wu, Shujuan 1,2; Zheng, Mulian 2; Liu, Qing 3; Zhou, Wen 4; Li, Yifeng 5; Ma, Zonghui 6
刊名	Advances in Civil Engineering Materials
	2020
卷号	9 期号:1 页码:683-710
关键词	Asphalt pavements Backpropagation Dissolution Fillers Freezing Melting Mixtures Neural networks Snow Stability Temperature Tensile strain Tensile strength Back propagation neural networks High temperature stability Long term performance Low temperature crack resistances Regression coefficient Soaking temperature Stone matrix asphalt Tensile strength ratios
ISSN号	23791357
DOI	10.1520/ACEM20200026
英文摘要	Anti-Freezing Asphalt Pavement (AFAP) has good snow-melting performance and is used widely in many countries around the world. The objective of this study was to analyze AFAP's long-term performance and predict its snow-melting ability. Two types of anti-freezing stone matrix asphalt (SMA) mixtures (SMA-13 with Iceguard and SMA-13 with Mafilon) were prepared with the Marshall method. Water stability, high-temperature stability, low-temperature crack resistance, and freeze-thaw split tests were conducted to evaluate mixtures' performance. Meanwhile, the effect of anti-freezing filler, asphalt content, and soaking temperature on the salt dissolution of anti-freezing asphalt mixtures was analyzed, and the snow-melting ability of AFAP was predicted based on the Back Propagation (BP) neural network. The results illustrated that water stability of anti-icing asphalt mixture reduced, and the dynamic stability after short-term aging was improved. The tensile strain and tensile strength ratio of the anti-icing asphalt mixture reduced after long-term aging and soaking in water. In addition, the salt dissolution rate increased with the increase of anti-freezing filler content and the decrease of asphalt content. The research conducted suggests that the BP Neural Network can be utilized to predict the snow-melting ability of the anti-freezing asphalt mixture, and the regression coefficient of the predicted and measured salt dissolution was higher. Copyright © 2020 by ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959
WOS研究方向	Materials Science
语种	英语
出版者	ASTM International
WOS记录号	WOS:000600069700001
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/151093]
专题	土木工程学院
作者单位	1.School of Civil Engineering, Lanzhou University of Technology, No. 287, Langongping Rd., Qilihe District, Lanzhou, Gansu; 730050, China; 2.Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang'an University, Middle Section of South Erhuan, Xi'an, Shaanxi; 710064, China; 3.Guangdong Nanyue Transportation Investment and Construction Co., Ltd., No. 27 Baiyun Rd., Guangzhou; 510000, China; 4.Anhui Transport Consulting and Design Institute Co., Ltd., No. 180, Xiangzhang Ave., High-tech Zone, Hefei; 230088, China; 5.Highway Administration Bureau of Rizhao City, 7 Yantai Rd., Rizhao, Shandong; 276826, China; 6.Highway Administration Bureau of Dezhou City, 1255 Mid Dongfeng Rd., Decheng District, Dezhou, Shandong; 253006, China
推荐引用方式 GB/T 7714	Wu, Shujuan,Zheng, Mulian,Liu, Qing,et al. Analysis of long-term performance and snowmelt capacity of anti-freezing asphalt pavement[J]. Advances in Civil Engineering Materials,2020,9(1):683-710.
APA	Wu, Shujuan,Zheng, Mulian,Liu, Qing,Zhou, Wen,Li, Yifeng,&Ma, Zonghui.(2020).Analysis of long-term performance and snowmelt capacity of anti-freezing asphalt pavement.Advances in Civil Engineering Materials,9(1),683-710.
MLA	Wu, Shujuan,et al."Analysis of long-term performance and snowmelt capacity of anti-freezing asphalt pavement".Advances in Civil Engineering Materials 9.1(2020):683-710.