MODEL PREDICTING AND OPTIMIZATION FOR THE MARSHALL PROPERTIES OF COLD MIX-RECYCLED ASPHALT PAVEMENT (CRAP) USING RESPONSE SURFACE METHOD (RSM)

Cold bitumen emulsion mixture (CBEM) is one of the most sustainable road construction material worldwide. When recycled asphalt pavement (RAP) is introduced in the mix, Cold-mix Recycled Asphalt Pavement (CRAP) is obtained, which is known for cost effectiveness and environmental friendliness because of its huge saving in cost of material and reduced green house gas emission (GHG). CRAP has been in use for different purposes in roads work. In this project cationic emulsion, cement, RAP, lime, aggregates were used as materials. Response surface method (RSM) was used for generating 6-nos predicting model equations for Marshall properties of CRAP and subsequently optimized solutions containing optimum factors and responses were obtained for the purpose of road wearing course layer. The results showed that bulk density, total void, and stablity successfully fitted to quadratic model,VMA and VFA fitted to cubic model , while flow fitted to linear model, all with very high and satisfactory correlation factor R2 (85% to 97%) with difference between predicted and adjusted value of not more than 0.2. Validation of the 6-predicting model equations were conducted using new set of laboratory samples casted with optimized solutions obtained from the RSM which showed that the difference between predicted and experimental values lied within the absolute discrepancy of 5%. This indicated that all the model equations could be used as predicting models for any CRAP material. It also showed that Samples that used 5% cements as filler satisfactorily performed with up to 50% of Rap in the wearing course.