Assessing the hydraulic conductivity of road paving materials using representative pore size and grading entropy

Abstract

Pavements are ubiquitous civil engineering structures which form the important lifelines that connect communities. They must remain serviceable after events such as flooding, cyclones and extreme freeze-thaw cycles. The hydraulic conductivity of road pavements is important to understand their performance. This paper summarises some recent work aimed at improving the prediction of the hydraulic conductivity of asphalt concrete. Laboratory test results show the use of the 'hand pumping method' to measure the percentage of connected air voids in asphalt concrete specimens. The representative pore size concept is used to analyse an updated database of hydraulic conductivity measurements of asphalt concrete. The effect of nominal maximum aggregate size is studied. Preliminary efforts to use the grading entropy framework to predict the hydraulic conductivity of asphalt concrete are reported.

Comparison of Prediction Models for the Permeability of Granular Materials Using a Database

“…Lőrincz et al (2005) and Singh (2014) provide more extensive commentary on the origins and details of the 'grading entropy' approach. Using a similar database to that presented in Vardanega et al (2017), Feng et al (2018b) performed multiple linear regression analysis to a large database of hydraulic conductivity measurements on asphalt concrete using the grading entropy co-ordinates as predictors. Feng et al (2018a) performed similar analysis for a set of laboratory data on a single gravel and found Equation 8 8Like the 'Hazen' and 'Shepherd' approaches no measurement of void ratio is included in this approach.…”