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This paper describes the development of novel/state-of-art computational framework to accurately predict the degree of binder activity of a reclaimed asphalt pavement sample as a percentage of the indirect tensile strength (ITS) using a reduced number of input variables that are relatively easy to obtain, namely compaction temperature, air voids and ITS. Different machine learning (ML) techniques were applied to obtain the most accurate data representation model. Specifically, three ML techniques were applied: 6th-degree multivariate polynomial regression with regularization, artificial neural network and random forest regression. The three techniques produced models with very similar precision, reporting a mean absolute error ranging from 12.2 to 12.8% of maximum ITS on the test data set. The work presented in this paper is an evolution in terms of data analysis of the results obtained within the interlaboratory tests conducted by Task Group 5 of the RILEM Technical Committee 264 on Reclaimed Asphalt Pavement. Hence, despite it has strong bonds with this framework, this work was developed independently and can be considered as a natural follow-up.

Cold recycling of reclaimed asphalt (RA) is a promising technique to build or to maintain roads, combining performance and environmental advantages. Although this technique has been extensively used worldwide, there is no unique and internationally-shared method to characterize cold recycled mixtures. The previous work of the RILEM TC 237-SIB TG6 successfully attempted to characterize different RA sources with both traditional parameters (gradation, bitumen content and geometrical properties) and non-conventional properties (fragmentation and strength testing). The current RILEM TC 264-RAP TG1 mainly focuses on the influence of different RA sources on physical and mechanical characteristics of cement-bitumen treated materials (CBTM) using foam or emulsified bitumen, taking into consideration compaction and curing methods. This paper presents results from the first step of the inter-laboratory project in which foamed bitumen and cement were used as binders. The influence of two RA sources, one from Alabama (USA) and one from San Marino, were investigated through the collaboration of several laboratories. Specimens were manufactured with the same diameter by means of both Marshall and gyratory compactors and then cured following two procedures: free surface drying (FSD) and partially-surface drying (PSD). A preliminary study allowed obtaining specimens with similar volumetric properties. Along with compactability and water loss, the indirect tensile stiffness modulus was measured and analyzed. The results have shown that the RA source and curing procedure influence the CBTM mechanical properties.

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Most cold in-place recycling (CIR) construction uses asphalt emulsion or foamed asphalt as stabilizing agent, which requires placing and compacting at optimum moisture or fluid content in the field. To ensure the CIR layer gains appreciable mechanical capacity to support traffic (including that of construction vehicles), the CIR layer must cure. Curing is typically expressed in relation to moisture content in the CIR layer; however, there is need to explore if a direct link exists between the amount of moisture in CIR and the mechanical properties of CIR. Presently, to ensure sufficient curing, construction specifications recommend time estimates with minimal consideration of how various factors such as material variations, climatic inputs, and construction process differences may affect the curing evolution. The objective of this study was to investigate and identify the critical factors that affect the curing evolution of CIR materials. Curing was evaluated in relation to moisture loss (using gravimetric measurements) and gain in mechanical properties (using indirect tensile strength and resilient modulus tests). The results show that there is further gain in mechanical properties after the CIR mixtures have reached an equilibrium moisture condition. Additionally, the following factors were identified to most significantly affect the curing evolution of CIR materials: stabilizer type and amount, active filler type and amount, initial moisture content, curing temperature (when active filler is present), and moisture reintroduction through external sources (e.g., rainfall). On the other hand, density and curing temperature (in the absence of active filler) did not seem to affect the rate of curing.