Predicting Marshall stability and flow of bituminous mix containing waste fillers by the adaptive neuro-fuzzy inference system

摘要

The practice of using different non-biddable wastes in place of conventional filler is successively extended nowadays, leading it hard to predict the properties of modified bituminous mixes. The present work aims to explore the effect of using rice husk ash (RHA) and fly ash (FA) as an alternative filler in place of conventional filler like hydrated lime (HL) on Marshall stability and flow of bituminous mix by adaptive neuro-fuzzy inference system (ANFIS). This study involves the preparation of samples having seven different bitumen content varying from 3.5% to 6.5% with a 0.5% increment. Mixtures containing 2%, 4%, 6%, and 8% of HL, RHA, and FA separately as filler were fabricated and compared with the control mix (i.e. mix containing 2% hydrated lime as filler). Further, the Marshall mix design procedure was followed to determine the optimum bitumen content (OBC) of each mix. Experimental results showed that the replacement of conventional filler with RHA and FA improved the Marshall properties and decreased the OBC values of the modified mix when added with 4% filler ratio Further, to analyze parameters that are the most influential in the prediction of Marshall stability and flow, a sensitivity analysis using ANFIS network was carried out considering all the input variables. As per the results obtained, the filler types, percentage filler, and percentage bitumen have the most effect on modeling the Marshall stability and flow. Then by utilizing the selected input parameters, the Marshall stability and flow were modeled with Sugeno type ANFIS. In comparison, it is realized that predicted values are closely relevant to the actual one and the prediction ability of the ANFIS is suitable for getting the said values by avoiding the expensive, time consuming, and repetitive laboratory tests.