To address the limitations of current concrete permeability evaluation, which can only test cored samples or on specific positions, this study proposed an innovative in-situ approach based on dynamic water film changes for evaluating concrete surface permeability. A porosity prediction model of concrete surface has been developed through ElasticNet regression, based on the data of dynamic water film thickness and concrete surface porosity. Considering different testing environment, the correction factors of temperature, relative humidity, wind speed, solar radiation intensity, and surface slope were determined. Then, we developed a large area in-situ test system based on moving platform for concrete surface permeability evaluation. The result indicates that there is a significant correlation between the water film permeation rate and the porosity, and the porosity prediction model exhibits high accuracy. The large area in-situ test system streamlines the concrete pavement permeability evaluation process, thereby contributes to maintenance and management of concrete pavements.
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