The hydro-mechanical interaction in novel polyurethane-bound pervious pavement by considering the saturation states in unbound granular base course

ABSTRACT

The pore-water pressure generated by intermittent dynamic vehicle loading under various saturation states is recognized as a critical factor influencing the behaviour of permeable pavement structures, especially the behaviour of UGB layer. However, the underlying mechanisms of hydro-mechanical interaction in the UGB layer and the influence on the pavement structure are still unclear. This study aims to characterize the changes in dynamic response in permeable pavement structures under various saturation conditions by considering the hydro-mechanical interaction within the UGB layer. To achieve this objective, a full-scale test track with a PUPM wearing course was constructed. Pressures and water distribution were characterized by embedded sensors within different layers of the test track when subjected to the accelerating pavement test. Based on the coupled SAME model, the water distribution and the dynamic response of UGB in the rainfall events were both characterised and solved by FEM. The results predicted by the proposed SAME model correspond to the field measurements, and the influence of the water content on the resilient modulus distribution within the UGB layer was then estimated. Based on the predictions for the stress state of the UGB layer, the sensitivity analysis was also proposed.

KEYWORDS:

• Water content
• matric suction
• unsaturated flow
• hydro-mechanical interaction
• polyurethane bound pervious material (PUPM)

Acknowledgments

This work was supported by the National Key Research and Development Program of China (grant number: 2019YFE0116300) and the Deutsche Forschungsgemeinschaft [grant number: GR1024/25-2 and FOR2089 (OE514/1-2 and OE514/4-2)].

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Key Research and Development Program of China (grant number: 2019YFE0116300) and the Deutsche Forschungsgemeinschaft [grant number: GR1024/25-2 and FOR2089 (OE514/1-2 and OE514/4-2)].