The quantitative assessment of clogging and cleaning effects on the permeability of pervious concrete

Abstract

Portland Cement Pervious Concrete (PCPC) is a unique and effective mean to solve the important environmental issues and support green, sustainable growth, by reducing stormwater and providing treatment of pollutants contained within. However, clogging of PCPC leading to potential problems in serviceability has been regarded as one of the primary drawbacks of PCPC applications. In order to quantitatively assess the effects of clogging mechanisms on the permeability of pervious concrete, the clogging potential of three void ratios of pervious concrete, 15%, 20% and 25%, were examined using three different soil types: sand, clay silt and clay silty sand. Pervious concrete cylindrical specimens were exposed to sediments mixed in water to simulate runoff with small and large load of soil sediments. Pressure washing, vacuuming and a combination of both were applied as rehabilitation methods to clean the clogged specimens. The clogging tests were conducted using falling head permeability apparatus by allowing the “dirty water” to flow through the specimen and the permeability was determined during the clogging and after the cleaning process in each clogging cycle. Totally 20 clogging cycles were repeated on each sample to simulate the 20 years of pavement service life. The results indicated that clay silty sand had a greater chance of clogging the specimen than sand and clay because of the cohesiveness and the wider particle size distribution. Residual permeability and permeability recoveries increased with increasing porosity of the specimens. Pressure washing followed by vacuuming was demonstrated to be the most efficient method of rehabilitation. The results of simulated sedimentation tests and the quantitative relationship between the permeability reduction and recovery of PCPC have the potential to optimize the pervious concrete mix design and maintenance strategies for rational soil characteristics and working condition scenarios.