Road use and electrothermal performance of graphene-conductive asphalt-recycled pervious concrete under severe cold environment

Abstract

Conductive-asphalt-recycled pervious concrete alleviates the urban “heat island effect” and “rain island effect” to realize the resourceful and efficient use of waste concrete and also reduces the probability of urban snow and ice disasters to ensure the safety of winter operation of asphalt pavements in cold areas. This study presents a theoretical and technical basis for ensuring the winter operational safety of asphalt pavements in cold regions. First, we compound graphene and carbon fiber as conductive phase materials and prepare graphene-conductive asphalt-recycled permeable concrete using recycled coarse aggregates with straight top and bottom holes. Then, we analyzed the electrical conductivity, road performance, and electrothermal performance of the specimens prepared using different recycled coarse aggregate substitution rates under different snowfall levels to determine their snow melting efficiency and verify their application in cold regions. The results indicate that the quality of the recycled aggregates is high, the optimal conductive filler ratio is 0.3% polyacrylonitrile-based carbon fiber and 1.5% graphene by mass of asphalt, and the resistivity of the specimens is only 3.2 Ω·m. Moreover, the conductivity and road performance of the graphene-conductive asphalt-recycled concrete decreases with an increase in the replacement rate of the recycled coarse aggregate, and the artificially prefabricated upper and lower through holes affect the conductivity of the specimens to a certain extent. Further, the graphene-conductive asphalt-recycled pervious concrete shows excellent snow melting potential, and as the required snow melting thickness and snow melting time increase, the effect of pervious asphalt slabs for snow melting efficiency becomes more significant. Moreover, when the replacement rate of the recycled concrete aggregate is within the range of 0–50%, it can be completed in 2–3 h under different snowfall levels of snow melting requirements.