An integrated DoE - Stochastic multi criteria decision-making analysis applied for experimental evaluation of fiber reinforced porous asphalt mixtures

Abstract

Porous asphalt (PA) mixture offers multiple benefits such as noise mitigation, skid resistance and management of storm water and runoff quality. However, its durability is not as promising compared to dense-graded asphalt mixtures. The objective of this research is to evaluate the functional and mechanical performance of PA mixtures modified with nylon and hydrated lime through experimental tests including air voids, permeability, raveling resistance, moisture susceptibility and binder drain down. Taguchi approach was employed to analyze the performance of these responses. Additionally, a novel multi-criteria decision-making (MCDM) technique was employed to turn the multiple-response problem optimization into a single response problem optimization. Monte Carlo Stochastic simulations were included as a complement to deal with the uncertainty contained in the experimental quantitative data. The optimal levels for acquiring a proper overall response value in terms of functionality and durability were identified as 4.60% for binder content factor; 0.04% for fiber content factor and 1.50% for Hydrated Lime content factor.