A Porous Elasto-Plastic Compaction Model for Asphalt Mixtures with Parameter Estimation Algorithm

Estimation of field compaction requirements to achieve a target density is important for predicting construction costs of asphalt concrete pavements. A model to predict the effects of mixture volumetric properties on compaction efficiency is desirable to optimize the design of asphalt mixtures. A compaction model is developed to predict laboratory compaction by the Superpave gyratory compactor. The presented work represents only a preliminary evaluation of the model to extend it to field compaction conditions. A pressure dependent porous material with elastoplastic matrix is assumed to contract under a prescribed compaction pressure induced by the Superpave gyratory compactor to a 6 in. cylindrical sample. Plastic strains are integrated from an incremental elastoplastic constitutive equation by forward difference method. Three model constants, q₁, q₂ and σ_y, are calibrated to determine measured deflections from the gyratory compactor by means of Levenberg-Marquardt nonlinear parameter estimation algorithm. A statistical correlation between estimated parameters and volumetric components are constructed to evaluate the effects of mixture properties on the estimated model constants. The proposed constitutive model accurately predicts the volume change behavior of mixture specimens undergoing gyratory compaction. Mixture volumetric properties also show correlations with the estimated model constants.