The Florida Department of Transportation (FDOT) is in the process of evaluating the protocols for collecting and analyzing roughness data. As part of that evaluation, a nationwide survey was performed to identify the trends and practices of various departments of transportation with regard to roughness data collection and analysis. All responding states indicated interest in obtaining the results of the survey, which was mailed to all 50 state departments of transportation. The responses show that most states are using laser-type road profilers for roughness measurements. The international roughness index (IRI) is the most widely used roughness index. Highway Performance Monitoring System (HPMS) data from different states are collected by using different equipment, and the data are collected in various wheelpaths and filtered differently. Stricter guidelines should be developed to ensure the consistency of HPMS data.
The Florida Department of Transportation is in the process of evaluating rubblizing concrete pavements as an effective rehabilitation technique for eliminating reflected cracks in asphalt overlays on top of concrete pavements. As part of that evaluation, a nationwide survey was performed to gather information about the practices of other departments of transportation with regard to rubblization and to determine the overall performance of rubblized sections in various states. The survey indicated that most states have a relatively small number of rubblized sections, with the exception of three states that have more than 10 sections each. The construction techniques, overlay thicknesses, and field performance varied from state to state. However, it was clear that most states are highly satisfied with rubblization as a good means for eliminating reflected cracks. Only a few states indicated problems with rubblization, mainly due to weak subgrade.
Analytical investigations of Dynaflect and falling weight deflectometer (FWD) were performed using a linear elastic multilayer computer program (BISAR) to generate deflections for different combinations of layer thicknesses and moduli. The generated data base was used to develop layer moduli prediction equations for each NDT device. Prediction equations from multiple linear regression analysis of the FWD data were dependent upon all sensor positions except for the subgrade modulus prediction, which required only the use of either the sixth or seventh sensor. However, it was found that the Dynaflect with modified sensor locations provided separation of deflection response between the upper pavement layers (asphalt concrete and granular base), the subbase, and the subgrade. Although the Dynaflect prediction equations were reasonably accurate on the basis of the analytical evaluation, they were considered too complex for practical use. NDT data were collected on flexible pavements at sites exhibiting a wide range in deflection response. The standard sensor positions were used for both FWD and Dynaflect testing of the pavement sections. However, the modified sensor positions for the Dynaflect were also used to collect deflection data. Mean pavement temperature, cores of asphalt concrete pavement, and cone penetration test data were obtained concurrently. Asphalt recovered from the cores Was tested to establish the asphalt viscosity-temperature relationship. Asphalt layer modulus values corresponding to pavement temperature during NDT testing were computed from a previously established relationship between resilient modulus of asphalt mixtures and asphalt viscosity. Cone penetration tests provided information on stratigraphy, soil type, and cone-bearing value. Plate-bearing test data were also obtained at several test sites. Analyses of the field deflection basins were performed using the viscosity predicted E1 value and the analytically predicted values for E2, E3, and E4. These moduli values were used in BISAR and adjusted (tuned) to give the best possible fit to the measured deflection basins.Multiple linear regression analyses were performed with the FWD tuned moduli to establish new prediction equations which were similar to those originally developed from the analytical study. Log-Log plots of layer moduli and deflections from the Dynaflect modified sensor configuration indicated that a simple power law equation was adequate for defining the composite modulus of asphalt concrete and granular base (E1.2), E3, and E4. The resulting Dynaflect prediction equations appear to give reliable layer moduli within the established layer thickness and deflection constraints. However, the predicted Dynaflect layer moduli are usually greater than the FWD predicted moduli, especially for the base and subbase layers. The cone penetrometer data were used to establish a relationship to the resilient moduli for use in predicting moduli of layers within the subgrade support system. Since pavement response and performance is highly dependent upon subgrade soil-moisture regime, the cone penetrometer provides data suitable for elastic layer modeling and pavement distress evaluation.
Initial pavement smoothness has been shown to improve overall pavement performance. This combined with the need to provide a comfortable ride for the driving public underscores the importance of achieving high initial pavement smoothness. The Florida Department of Transportation has developed smoothness specifications for asphalt pavements. These smoothness specifications will be used on high-speed facilities and will be based on measurements obtained with laser road profilers. The ultimate goal is to include incentive and disincentive specifications aimed at rewarding the contractor for a high-quality ride and simultaneously providing a financial deterrent to providing a poor-quality ride.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.