Study on the skid resistance decay of submerged asphalt pavements based on texture parameters

Abstract It is well known that prolonged rainwater erosion can adversely affect the surface texture of asphalt pavements, leading to a rapid decline in their skid resistance. This study utilized a small-scale accelerated loading device, a high-precision 3D scanner, and digital image processing technology to investigate the surface texture wear process and skid resistance decay trends of basalt asphalt pavement and steel slag asphalt pavement under water erosion and traffic load. The results indicate that under submerged conditions, the skid resistance (BPN) of asphalt pavement declines rapidly during the first 500,000 load cycles, and the rate of decline gradually stabilizes after 500,000 cycles. After 1.2 million load cycles, the BPN of basalt pavement decreased by 28.10%, while that of steel slag pavement decreased by 21.18%, indicating that the skid resistance of steel slag pavement is significantly better than that of basalt pavement. Texture parameters—namely, root mean square height, peak material volume, core material volume, void volume of the core, and valley void volume—exhibited the same decay trend as BPN. The average correlation coefficients between BPN and texture parameters were 0.846, 0.848, 0.898, and 0.916, respectively, indicating that texture parameters can be used as evaluation indicators for skid resistance decay. Finally, the decay of pavement skid resistance was predicted using an exponential decay equation.

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Publication Details

Journal
Materials and Structures
Published
2024-11-11
DOI
https://doi.org/10.1617/s11527-024-02484-x
Citations
2
Primary Topic
Asphalt Pavement Performance Evaluation
Type
article
Field-Weighted Citation Impact
0.52

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article

Study on the skid resistance decay of submerged asphalt pavements based on texture parameters

Bin Zhou, Rongxin Guo, Yan Feng, Junjie Li et al.
2 citations
Materials and Structures
Asphalt Pavement Performance Evaluation
0.52
article

Study on the skid resistance decay of submerged asphalt pavements based on texture parameters

Bin Zhou, Rongxin Guo, Yan Feng, Junjie Li, Hong Wang, Bao Lingchen, Lv Binjin, Huang Kaiyong
article en
2 citations

Abstract

Abstract It is well known that prolonged rainwater erosion can adversely affect the surface texture of asphalt pavements, leading to a rapid decline in their skid resistance. This study utilized a small-scale accelerated loading device, a high-precision 3D scanner, and digital image processing technology to investigate the surface texture wear process and skid resistance decay trends of basalt asphalt pavement and steel slag asphalt pavement under water erosion and traffic load. The results indicate that under submerged conditions, the skid resistance (BPN) of asphalt pavement declines rapidly during the first 500,000 load cycles, and the rate of decline gradually stabilizes after 500,000 cycles. After 1.2 million load cycles, the BPN of basalt pavement decreased by 28.10%, while that of steel slag pavement decreased by 21.18%, indicating that the skid resistance of steel slag pavement is significantly better than that of basalt pavement. Texture parameters—namely, root mean square height, peak material volume, core material volume, void volume of the core, and valley void volume—exhibited the same decay trend as BPN. The average correlation coefficients between BPN and texture parameters were 0.846, 0.848, 0.898, and 0.916, respectively, indicating that texture parameters can be used as evaluation indicators for skid resistance decay. Finally, the decay of pavement skid resistance was predicted using an exponential decay equation.

Materials and StructuresVol. 57(10)
Kunming University of Science and Technology (CN)
Yunnan Provincial Science and Technology Department
Clean water and sanitation
Openalex Percentile: Top 35%
Asphalt Pavement Performance Evaluation
0.52
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Study on the skid resistance decay of submerged asphalt pavements based on texture parameters — Bin Zhou, Rongxin Guo, et al. · Materials and Structures (2024) | TGRS Research Map | TGRS