Abstract
The hydroplaning propensity on the steel bridge deck pavement (SBDP) is higher than ordinary road pavements. In this study, the objective is to develop a hydroplaning model to evaluate the hydroplaning behaviors for SBDPs. To achieve this goal, a finite element (FE) model of a 3D-patterned radial tire model was developed at first, and the grounding characteristics of tire on the SBDP were calculated as an initial condition for the follow-up hydroplaning analysis. The X-ray CT scanning device and Ostu thresholding method were used for image processing of pavement surface topography, and the 3D FE model of SBDP was established by the reverse stereological theory and voxel modeling technique, which can accurately reconstruct the pavement morphology. A fluid model was established to simulate the dynamic characteristics of water film between the tire and SBDP. On this basis, the tire–fluid–pavement interaction model was developed based on the CEL (Couple Eulerian–Lagrangian) algorithm, and it was verified by the hydroplaning empirical equations. Finally, the hydroplaning behaviors on the SBDP were studied. The findings from this study can provide a tool for hydroplaning evaluation on SBDPs, and will be helpful to improve the driving safety of SBDP in rainy days.
Highlights
Hydroplaning on pavement in rainy conditions is a common phenomenon threatening driving safety [1]
The tire–fluid–pavement interaction model was developed based on the CEL (Couple Eulerian–Lagrangian) algorithm, and it was verified by the hydroplaning empirical equations
Hydroplaning is the main cause of accidents in rainy days, and reducing the risk of hydroplaning is of great importance to driving safety
Summary
Hydroplaning on pavement in rainy conditions is a common phenomenon threatening driving safety [1]. Gallaway et al [3] developed a hydroplaning equation based on the hydroplaning test, and the quantitative relationship between tire inflation pressure, tire pattern depth, water film thickness, pavement surface macrotexture characteristic, and hydroplaning speed was determined in the equation. Developed a tire–fluid–pavement interaction model to evaluate the driving safety on a wet asphalt pavement, and revealed the influences of water film depth and pavement surface texture on the hydroplaning speed. Zhu et al [15,16] developed a tire–fluid–pavement model based on the CEL algorithm, and it was found that higher tire inflation pressure, thinner water film, and more abundant macrotexture can enhance the hydroplaning speed through numerical analysis.
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