Mixture-property-independent asphalt film thickness model (original) (raw)

The durability of asphalt mixtures and hence the service life of asphalt pavement surface layers depends to a large extent on the asphalt film thickness. The current Superpave Voids in Mineral Aggregate (VMA) criterion relates mixture durability with VMA. The need to modify the Superpave criterion was supported by a previous study [1]. As the Superpave VMA criterion is based on the minimum asphalt content in the asphalt mixture and not on the asphaltfilm thickness, this minimum requirement does not ensure mixture durability in many cases. Additionally, coarse asphalt mixtures that tend to have enough asphalt film thicknesses normally have difficulty fulfilling the Superpave minimum VMA criteria. From this contention, the need for simple and reasonably accurate models to estimate the asphalt binder film thicknesses in asphalt mixtures becomes essential. In this study, a model for estimating the asphalt film thickness (FT b) has been developed using only para-meters/properties of the two mixture constituents (aggregate and asphalt binder) and without the inclusion of any mixture property. The derivation of the model is based on physics, and the determined model coefficients (constants) have been obtained through statistical regression analysis. Superpave aggregate gradations of three nominal maximum aggregate sizes (NMAS), 9.5, 12.5, and 19.0 mm with aggregate gradations passing above, below, crossover, hump through, and pass through restricted zone were used. Superpave Gyratory Compactor (SGC) test data of 100 compacted asphalt mixtures were used in developing the model, and SGC data of 31 mixtures were used for verification of the model. MS Excel program solver was used for regression analysis. The final outcome is a physics-based statistical regression model, with a high enough coefficient of determination (R 2) value of 0.9 for FT b , which is easy to use and likely to predict the film thickness with a reasonable degree of accuracy. 1. Background The conventional method used by most highway agencies to compute the asphalt film thickness in asphalt mixtures was developed about 50 years ago and needs to be updated. There are very limited studies in the literature that have focused on this topic to come up or develop new models or formulas to estimate the asphalt film thickness as can be seen from the scanty available information reviewed below. Attia et al. [2] evaluated the voids in mineral aggregate (VMA) and the asphalt film thickness (AFT) as mixture design parameters through field performance of Superpave mixtures. Film thickness was estimated by different formulas using calculated aggregate surface area. Pavement sections with early flushing and rutting problems were considered in the study to correlate the AFT with the development of pavement distresses. The findings of their study showed that the AFT capability to explain specific field performance distresses such as rutting and bleeding is dependent on the calculation method. Heitzman, [3] developed new models for asphalt film thickness based on random spatial distribution of particles in asphalt mixtures. The models were applied to Iowa State Department of Transportation (DOT) hot-mix asphalt (HMA). The results indicated that the proposed models accounted for the individual aggregate source gradations, specific gravities, and particle shape that comprise the HMA blend, and might give a better measure of mixture durability. Radovskiy, [4] developed analytical formulas for asphalt film thickness in compacted asphalt mixtures to determine the film thickness for any volume fraction of aggregates and any volume fraction of effective asphalt. The formulas were developed using a model of asphalt concrete in which the aggregates are spherical with arbitrary size distribution. Details of the calculations were summarized and examples were provided. Li et al. [5] in their study proposed a computation approach that was believed to improve the current conventional method for asphalt film thickness calculation by considering shape factors and flat surface