Accuracy of Predictive Models for Dynamic Modulus of Hot-Mix Asphalt

TLDR: In this paper, the authors discuss the accuracy and robustness of various predictive models (Witczak 1999 and 2006 and ANN-based models) for estimating the HMA ∣ E* ∣ inputs needed for the new mechanistic-empirical pavement design guide.

Abstract: Various models have been developed over the past several decades to predict the dynamic modulus ∣ E* ∣ of hot-mix asphalt (HMA) based on regression analysis of laboratory measurements. The models most widely used in the asphalt community today are the Witczak 1999 and 2006 predictive models. Although the overall predictive accuracies for these existing models as reported by their developers are quite high, the models generally tend to overemphasize the influence of temperature and understate the influence of other mixture characteristics. Model accuracy also tends to fall off at the low and high temperature extremes. Recently, researchers at Iowa State Univ. have developed a novel approach for predicting HMA ∣ E* ∣ using an artificial neural network (ANN) methodology. This paper discusses the accuracy and robustness of the various predictive models (Witczak 1999 and 2006 and ANN-based models) for estimating the HMA ∣ E* ∣ inputs needed for the new mechanistic-empirical pavement design guide. The ANN-based...