New relationships have been identified between the layer condition indicators of flexible pavements and falling weight deflectometer (FWD) deflections. Synthetic databases were generated using dynamic finite element analysis with nonlinear material models. The sensitivity of various deflection basin parameters (DBPs) to layer conditions was comprehensively examined on the basis of the developed databases. Three types of layer condition indicators were identified in the study, including DBPs, effective layer moduli, and stresses and strains. The DBPs identified from the sensitivity study were used in developing new relationships between the selected condition indicators and FWD deflections by applying regression and artificial neural network techniques. Even though these relationships include the complicated dynamic effect of FWD loading and nonlinear behavior of unbound materials, the time to obtain results from these procedures is insignificant, thus making the procedures suitable for field implementation.

Mechanistic–empirical pavement design has received significant attention from the pavement community as the method for designing asphalt pavements in the future. Currently available software for mechanistic–empirical pavement design includes the AASHTOWare Pavement ME Design (Pavement ME) program. The Pavement ME program allows users to predict pavement distresses by applying layered elastic theory for the mechanical responses and using empirical models for the distress predictions. The layered viscoelastic pavement design for critical distresses (LVECD) program, which employs three-dimensional viscoelastic finite element analysis with moving loads, can also be used to predict the fatigue and rutting performance of pavements. The LVECD program employs the simplified viscoelastic continuum damage (S-VECD) model as the material model for the fatigue performance predictions of asphalt mixtures under complex loading and environmental conditions. This paper examines and compares the performance of 33 pavement sections from five research projects located in the United States, Canada, and South Korea by using both the Pavement ME and LVECD computer programs. To verify the results obtained from these two programs, the simulations were compared with the field performance data. In terms of ranking, the LVECD simulations provided better agreement with the field performance data than did the Pavement ME simulations. One of the main reasons for the better predictions obtained by the LVECD program is that its fatigue performance predictions depend on the mixture properties of all the layers, whereas the Pavement ME program considers the fatigue properties of only the bottom layer mixture.

Nondestructive condition assessment criteria were developed for application in conjunction with the condition evaluation indicators that are estimated based on falling weight deflectometer (FWD) deflections. Data obtained from state departments of transportation and DATAPAVE 2.0 were used in developing these criteria. To account for the effects of pavement structure and temperature on FWD deflection analysis, structure and temperature correction procedures based on synthetic databases were applied. Also, a deflection prescreening procedure was established to identify and correct any irregular deflection basins potentially arising from measurement errors. All the calibrated predictive procedures, structure and temperature correction procedures, and prescreening algorithms were incorporated into the user-friendly deflection analysis program with graphical interface, Asphalt Pavement Layer Condition Assessment Program, or APLCAP.

Research project NCHRP 9–19 identifies the confined dynamic modulus as one of three favorable indicators for evaluating the rutting potential of a mixture. Though important, dynamic modulus testing at multiple confining pressures takes too long for state highway agencies to use it routinely. Therefore, several methods have been suggested to measure and predict confined dynamic modulus values without the need to run numerous tests. Experimental results show that the linear viscoelastic properties of an asphalt mixture are not affected by different confinements and that all confining stress effects are manifest in the elastic modulus at equilibrium, similar to unbound granular materials. The proposed method uses a Prony series representation of the dynamic modulus curve and master curve shift factors obtained from unconfined testing. This method uses the elastic modulus values predicted from a modified version of the universal material model to predict dynamic moduli at different levels of confinement. Beyond the typical AASHTO TP62 testing procedure under an unconfined condition, additional testing is conducted at 54°C at three levels of confinement. This reduced testing protocol provides reasonable results, with most errors less than 20%. The largest errors between the measured confined and unconfined data were generally overpredicted values at 54°C because the universal model overpredicted the elastic modulus. The applicability of this method is verified for the asphalt mixture performance tester as long as three levels less than 250 kPa are used, because 250 kPa is the maximum confining pressure that the tester can handle.