4.6 Article

Maintenance Time of Permeable Asphalt Pavement Based on Entropy-Analytic Hierarchy Process Analysis

Journal

COATINGS
Volume 11, Issue 12, Pages -

Publisher

MDPI
DOI: 10.3390/coatings11121516

Keywords

permeable asphalt pavement; entropy-analytic hierarchy process; maintenance time; drainage coefficient

Funding

  1. General Project of Liaoning Provincial Department of Education [lnjc202014]

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The study revealed that the drainage capacity of permeable pavements follows a parabolic exponential attenuation law. By examining the road water storage capacity, the latest pavement maintenance time at different rainfall levels was obtained, allowing for more accurate decisions compared to regular time intervals to address drainage issues caused by multiple factors.
Dust, sediment, and stone chips often block the rainwater-infiltration paths of permeable pavements, which, in conjunction with vehicle load, reduces drainage capacity. To restore this capacity, a reasonable maintenance time and suitable maintenance measures must be determined. Therefore, we investigated the void attenuation and decline in drainage capacity of permeable asphalt pavements under the combined action of dust blockage and vehicle load. First, the water seepage coefficient decay and the decay rate under blocking and compaction were determined via clogging and compaction experiments. Second, experimental data were incorporated into an entropy-analytic hierarchy process analysis model, with the gross domestic product ratio, wind scale, and maximum five-year rainfall for the area. Finally, three test roads were studied as the weight to rank the maintenance urgency and predict the maintenance timing for each road under different rainfall conditions. The results demonstrate that the drainage capacity of permeable pavements obeys the parabolic exponential attenuation law. From the findings regarding road water storage capacity, the latest pavement maintenance time at different rainfall levels were obtained. This predicted maintenance time enables better decisions than regular time on code, which is the effect of drainage caused by multiple factors.

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