Traffic-speed deflectometers (TSD) are used in several countries to evaluate the pavement structural condition at the network level. Fatigue and rutting strains are commonly used as pavement critical responses in mechanistic-empirical design procedures to predict pavement structural performance. For successful pavement management system (PMS) application, robust indices that can be readily computed from TSD measurements and best related to the pavement critical responses should be identified. In this study, a comprehensive sensitivity analysis on deflection basin indices and their correlations with fatigue and rutting strains is performed using a range of pavement structures. A commercially available program was used in the first part of the study to compute dynamic deflection basins and evaluate the effects of material properties and vehicle speed on the indices. The indices that best relate to critical responses were identified from the software analyses and subsequently evaluated with a wider r...

The procedures in Mechanistic-Empirical Pavement Design Guide (MEPDG) and Caltrans software program using Mechanistic-Empirical (CalME) methodologies to address wheel wander are relatively simple and based on dividing the wheel wander distribution into a number of segments (say five) of equal areas. Such approaches suffer from a major limitation that the selection of equal segments is arbitrary, and can, therefore, lead to biased results relative to realistic transverse wheel wander distribution. The proposed Monte-Carlo simulation scheme provided cumulative distribution functions for all the critical responses and they in turn were used to estimate pavement performance (or life). The investigation covered a variety of pavement factors that significantly affect pavement performance or life. The factors included are: (1) pavement layer configuration (thin and thick); (2) pavement material properties (unmodified and polymer-modified asphalt mixture); and (3) tyre configurations (dual and wide-base). In this paper, the focus has been on the description of the proposed approach and its application in two of the important modes of failure in asphalt concrete pavements: fatigue cracking (top-down and bottom-up) and rutting. The required traffic-induced pavement strain database needed in the pavement performance investigations was developed using the 3D-Move analysis software. The proposed approach is more appealing than current procedures (e.g. MEPDG and CalME) since the pavement response distributions were derived statistically. The pavement design information presented are in the form of data sets that the pavement engineers and researchers can readily use to assess the impact of wheel wander in terms of many important factors such as pavement layer configuration, non-uniform tyre contact distribution, vehicle speed, etc., that affect long-term pavement performance.

Structural number (SN) represents the structural capacity of a flexible pavement system to sustain anticipated traffic and is among the structural indices most commonly used by pavement design engineers in the U.S. Effective structural number (SN_eff) is an indicator of structural capacity of in-service pavement sections and is conventionally estimated from nondestructive testing (NDT) device data such as falling weight deflectometers (FWDs) using methods such as suggested by AASHTO. In addition to pavement design, structural condition is a critical input for the selection of maintenance and rehabilitation strategies in pavement management system (PMS) application. However, use of SN in network level application has not been practical because of limitations of FWD such as stop-and-go operation, lane closures, and low testing frequency. The traffic speed deflectometer (TSD), a continuous deflection device, has recently been gaining worldwide application as a reliable NDT device for network level PMS applications. The objective of this study is to develop a practical approach to compute and utilize SN of in-service flexible pavements from TSD data for network level PMS applications. The study is based on the fundamental that, for the same pavement, SN_eff from the TSD using the proposed method should be in good agreement with SN_eff from the FWD using AASHTO method. The developed method was field validated with TSD and FWD data collected at in-service pavement sections. In addition, the use of structural number ratio, defined as a ratio of SN_eff to required SN, in network level prioritization of structural capacity improvements was illustrated.

Two traffic speed deflection devices (TSDDs) that measure surface deflections at posted traffic speeds (up to 80–96 kph) were evaluated through a recent Federal Highway Administration project that included field trials at the MnROAD facility. Four geophones were embedded near the pavement surface to measure surface deflections during field trials at each of three MnROAD cells. In addition, the MnROAD facility counted with numerous other sensors such as strain gauges to measure pavement responses and thermocouple trees to collect pavement temperature at various depths. For the implementation of TSDDs in any network-level pavement management system, it is important to utilise a proper analytical model that can accommodate moving load and viscoelastic properties of pavement layers in the simulation of TSDD measurements. The 3D-Move software was chosen for this purpose. The viscoelastic properties used for the asphalt concrete (AC) layer include dynamic modulus and damping coefficient as a function of frequency relevant to the temperature at the time of the MnROAD field trials. The field trials and available data represented realistic field case scenarios to validate once more 3D-Move specifically for TSDD measurements. The proposed dynamic analytical model provided a good match with a variety of independent pavement responses that included surface deflection bowls (measured using embedded geophone sensors) as well as horizontal strains at the bottom of the AC layers (measured using MnROAD sensors).

Pavement structural condition evaluation plays an important role in assessing rehabilitation needs and making prudent investment decisions. Recently the use of Traffic Speed Deflectometer (TSD), is being considered for pavement structural evaluation especially for network level pavement management applications. Among various TSD data measurements and indices, Surface Curvature Index (SCI_TSD), is a widely-used index for assessing the structural condition of the AC layers. Since asphalt modulus is temperature sensitive, measured deflections and consequently the computed SCI_TSD are also affected by pavement temperature at the time of testing. For consistent pavement evaluation, SCI_TSD computed across sections and over time should be adjusted to a reference temperature. This study presents an applied method for adjusting SCI_TSD to a reference temperature. The method was based on a model developed from a dataset built from responses computed with dynamic-viscoelastic analyses under TSD moving load in a wide range of pavement properties. The method was field evaluated with TSD data from three locations within the US and one location each in Europe and Australia. The results showed that the proposed method can reasonably adjust SCI_TSD to a reference temperature which enables its application in pavement structural assessment and subsequent use in pavement management activities.