Study on curing degree of emulsified asphalt chip seal based on the comprehensive electrical properties index

Zeng, Qingwei; Zhang, Yang; Yang, Shunxin; Xiao, Feng; Luan, Dongxing; Cui, Qixuan

doi:10.1016/j.conbuildmat.2024.135401

Construction and Building Materials

2024

DOI: 10.1016/j.conbuildmat.2024.135401

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Study on curing degree of emulsified asphalt chip seal based on the comprehensive electrical properties index

Qingwei Zeng,

Yang Zhang,

Shunxin Yang

et al.

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2024

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Cited by 2 publications

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Data Cleaning Framework for Pavement Maintenance and Rehabilitation Decision-Making in Pavement Management System Based on Artificial Neural Networks

Zeng,

Xiao,

Zhang

et al. 2024

J. Infrastruct. Syst.

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Data Cleaning Framework for Pavement Maintenance and Rehabilitation Decision-Making in Pavement Management System Based on Artificial Neural Networks

Zeng,

Xiao,

Zhang

et al. 2024

J. Infrastruct. Syst.

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Ordinal Clustering Based Homogeneous Road Segments in Asphalt Pavement Maintenance and Rehabilitation Optimized Decision-Making

Xu,

Zeng,

Chen

et al. 2024

Transportation Research Record: Journal of the Transportation R

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An increase in the number of work zones on roads and highways will result in more costs from the increased frequency of maintenance and rehabilitation (M&R) equipment transfers. The number of M&R decision-making segments can affect decision-making efficiency and the number of work zones. Fixed segmentation and traditional dynamic homogeneous segmentation techniques, such as the cumulative difference approach (CDA) and K-means algorithms, cannot determine the optimal number of decision-making segments. To address this issue, this paper proposes a method to develop a multi-year asphalt pavement M&R plan that incorporates homogeneous road segmentation based on an ordinal clustering approach (OCA). The proposed method first applies an ordinal clustering approach to the survey units to identify homogeneous segments. These segments are then incorporated into a multi-year asphalt pavement M&R optimization decision-making model to determine the M&R plan. Data from 2022 covering 15.9 km of continuous asphalt pavement on the Donglv Highway in Shanxi Province were selected for analysis. These results demonstrate: 1) the OCA exhibits superior decision-making accuracy compared with the CDA; 2) compared with the M&R plans for survey units and CDA for homogeneous segments, the proposed method's M&R plan can be resolved faster and see fewer work zones, all achieved with a similar level of investment and meeting performance improvement; and 3) the M&R plan generated using the proposed method requires lower M&R investment but achieves higher performance compared with the actual M&R plan. These findings validate the effectiveness of the proposed method in producing improved M&R plans.

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Study on curing degree of emulsified asphalt chip seal based on the comprehensive electrical properties index

Cited by 2 publications

References 24 publications

Data Cleaning Framework for Pavement Maintenance and Rehabilitation Decision-Making in Pavement Management System Based on Artificial Neural Networks

Data Cleaning Framework for Pavement Maintenance and Rehabilitation Decision-Making in Pavement Management System Based on Artificial Neural Networks

Ordinal Clustering Based Homogeneous Road Segments in Asphalt Pavement Maintenance and Rehabilitation Optimized Decision-Making

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