Evaluation of a Predicted Dynamic Modulus for Florida Mixtures

Abstract

The new 2002 AASHTO guide for the design of pavement structures is based on mechanistic principles and requires the dynamic modulus as input to compute stress, strain, and rutting and cracking damage in flexible pavements. The 2002 AASHTO guide has three different levels of analysis; the level used depends on the importance of the pavement structure in question. Dynamic modulus testing is required for Level 1 pavement analysis, whereas no laboratory test data are required for Level 2 and Level 3 pavement analysis. Instead, a predictive dynamic modulus equation is used to generate input values. It is of significant importance to state agencies to understand how well the dynamic modulus for locally available materials compares with the predicted dynamic modulus. This paper presents the results of a study by the Florida Department of Transportation and the University of Florida that focused on the evaluation of the dynamic modulus predictive equation used in the new AASHTO 2002 guide for mixtures typical to Florida. The resulting research program consisted of dynamic modulus testing of 28 mixtures common to Florida. Results showed that on average the predictive modulus equation used in the new AASHTO 2002 flexible pavement design guide appeared to work well for Florida mixtures when used with a multiplier to account for the uniqueness of local mixtures. Results of the study also identified optimal viscosity–temperature relationships that result in the closest correspondence between measured and predicted dynamic modulus values.

Evaluation of dynamic modulus of typical asphalt mixtures in Northeast US Region

“…In addition, it is hypothesized that the Witczak equation may not be suitable for predicting |E * | of polymer-modified binders (Dongre et al, 2005). Birgisson, Sholar, and Roque (2005) examined the quality of Witczak model predictions for typical asphalt mixes in Florida. They found that Equation (3) can be used to predict measured |E * | values with the reliability of 85 to 90%, if the appropriate multiplier is used.…”

“…On the other hand, a non-linear behaviour of asphalt mixture was detected at higher temperatures and/or lower frequencies, which is in contradiction to the trends observed in binders (Masad & Bahia, 2002). Similarly, Birgisson et al (2005) concluded that the response of asphalt mixture at high temperature (40 • C) is more dependent on the aggregate structure than it is at low temperature.…”

Evaluation of Dynamic Modulus Predictive Equations for Southeastern United States Asphalt Mixtures

“…For use in the MEPDG, viscosity can be obtained in many ways: by using typical values embedded in the MEPDG based on performance grade or measured penetration, by using empirical relationships with conventional binder tests (ring and ball, penetration, softening point, or kinematic viscosity), by measuring Brookfield rotational viscosity or absolute viscosity, or by converting DSR G b * measured at 10 rad/s (6). Brookfield rotational viscosity is converted to viscosity at a desired temperature by determining regression parameters A and VTS from the relationship in the following equation: *, using recommended values for A and VTS, those predictions based on Brookfield rotational viscosity had the lowest bias and highest coefficient of determination (R 2 ) (11).…”

How the Mix Factors Affect the Dynamic Modulus of Hot-Mix Asphalt

“…The |E*| of HMA depends on many mix factors: aggregate, binder, air voids, specimen size, etc. Many researchers developed empirical based |E*| models to address these factors and to predict the dynamic modulus of HMA [1][2][3][4][5][6][7][8][9][10]. These models try to predict the |E*| values using the aggregate gradation, viscosity, shear modulus, etc.…”