7 research outputs found
Mechanistic-Empirical Evaluation of Pavement Damage and Cost Attributed to Overweight Single-Trip and Multi-Trip Scenarios in Nevada
The movement of overweight (OW) vehicles has become more common over the years dueto its vital necessity for many important industries such as chemical, oil, defense, etc. UsingOW vehicles reduces the number of vehicles on highways, potentially decreasing trafficcongestion and emissions. However, the operation of large and heavy vehicles can lead toa speedy deterioration of the roadway system; hence necessitating additional resources tomaintain the conditions of roadway pavements at an acceptable level.This dissertation presents an approach that allows the estimation of pavementdamage associated costs (PDAC) attributable to OW vehicle moves. The PDAC can beestimated for different OW axle loadings and configurations with due considerations givento locally-calibrated pavement distress models, existing pavement condition, differentpavement repair options, and vehicle miles traveled (VMT). The approach uses the sameinformation currently requested by the Nevada Department of Transportation (NDOT)during the OW permit application process and provides a realistic methodology to assesspavement damage from single-trip and multi-trip OW scenarios. In the methodology, thedamage from OW vehicles is compared to that caused by a standard vehicle. It should benoted that the costs associated to the pavement damage caused by lighter vehicles grossvehicle weight (GVW) up to 80,000 lb. is assumed to be already covered by fuel taxes andwill be reflected in a PDAC of zero dollars.In the calculation of PDAC, the remaining service life (RSL) of the pavement wasconsidered, a RSL of one representing a new pavement section. The RSL is a directmultiplier of PDAC and it is used to consider the current condition of the pavement at thetime of the move. Consequently, lower PDACs will be estimated for an OW pass occurring iiion a pavement section with lower remaining life (i.e., a pavement section that has alreadybeen subjected to a percentage of its original design traffic).As part of this study a ten-year NDOT over-dimensional permit database containing367,595 entries was analyzed. Along with the ten-year permit database, thousands of actualover-dimensional permit forms which described GVW and the entire axle and loadconfigurations of the permitted vehicles were analyzed. The purpose of the analysis wasthe identification and classification of trends, GVW, axle loads/tire loads and otherimportant characteristics of the OW movements in Nevada. This analysis enabled thedesign of a comprehensive experimental plan of pavement analyses required to model OWvehicles under the different loading, pavement temperature, and speed conditions found inNevada.In the development of the PDAC methodology, relationships between the ACdynamic modulus master curve parameters and the respective pavement responses atvarious locations within the structure were taken into consideration. In fact, master curvesof pavement responses were constructed using the same non-linear models used in theconstruction of the sigmoidal dynamic modulus master curve. The effect of pavementtemperature, vehicle speed, and axle load level were considered in the development of 3Dsurfacecontaining entire maps of pavement responses shifted at selected temperatures.The presented methodology provides useful ways to assess pavement damage fromOW vehicles, eliminating the need for conducting individual deterministic pavementanalysis assessments. Through comparative analysis, it was found that the proposedmethodology produces PDAC values that are comparable to those levied by other statehighway agencies (SHAs) that implement distance and weight-distance fee structures. It ivwas also estimated that the PDAC methodology could produce significant increase inrevenue when assuming average input values. However, such increase in revenue is mostlyassociated with OW vehicles in the heaviest categories
Quality Control and Quality Assurance of Asphalt Mixtures Using Laboratory Rutting and Cracking Tests
The main objectives of this project were to review the available balanced-mix design (BMD) methodologies, understand the I-FIT and Hamburg Wheel Tracking Test (HWTT) test methods using INDOT asphalt mixtures, and to explore the application of these tests to both a BMD approach and as performance-related Quality Control (QC) and Quality Acceptance (QA) methods. Two QA mixture specimen types, plant-mixed laboratory-compacted (PMLC) and plant-mixed field-compacted (PMFC) were used in the determination of cracking and rutting parameters. Distribution functions for the flexibility index (FI) values and rutting parameters were determined for various mixture types. The effects of specimen geometry and air voids contents on the calculated Flexibility Index (FI) and rutting parameters were investigated. The fatigue characteristics of selected asphalt mixtures were determined using the S-VECD test according to different FI levels for different conditions. A typical full-depth pavement section was implemented in FlexPAVE to explore the cracking characteristics of INDOT asphalt mixtures by investigating the relationship between the FI values of QA samples with the FlexPAVE pavement performance predictions.
The FI values obtained from PMFC specimens were consistently higher than their corresponding PMLC specimens. This study also found that FI values were affected significantly by variations in specimen thickness and air voids contents, having higher FI values with higher air voids contents and thinner specimens. These observations do not agree with the general material-performance expectations that better cracking resistance is achieved with lower air voids content and thicker layers. Additionally, PG 70-22 mixtures show the lowest mean FI values followed by the PG 76-22 and 64-22 mixtures. The same order was observed from the ΔTc (asphalt binder cracking index) of INDOT’s 2017 and 2018 projects.
Finally, it was found that the HWTT showed reasonable sensitivity to the different characteristics (e.g., aggregate sizes, binder types, and air voids contents) of asphalt mixtures. Mixtures containing modified asphalt binders showed better rut resistance and higher Rutting Resistance Index (RRI) than those containing unmodified binders
Structural Evaluation of Full-Depth Flexible Pavement Using APT
The fundamentals of rutting behavior for thin full-depth flexible pavements (i.e., asphalt thickness less than 12 inches) are investigated in this study. The scope incorporates an experimental study using full-scale Accelerated Pavement Tests (APTs) to monitor the evolution of each pavement structural layer\u27s transverse profiles. The findings were then employed to verify the local rutting model coefficients used in the current pavement design method, the Mechanistic-Empirical Pavement Design Guide (MEPDG). Four APT sections were constructed using two thin typical pavement structures (seven-and ten-inches thick) and two types of surface course material (dense-graded and SMA). A mid-depth rut monitoring and automated laser profile systems were designed to reconstruct the transverse profiles at each pavement layer interface throughout the process of accelerated pavement deterioration that is produced during the APT. The contributions of each pavement structural layer to rutting and the evolution of layer deformation were derived. This study found that the permanent deformation within full-depth asphalt concrete significantly depends upon the pavement thickness. However, once the pavement reaches sufficient thickness (more than 12.5 inches), increasing the thickness does not significantly affect the permanent deformation. Additionally, for thin full-depth asphalt pavements with a dense-graded Hot Mix Asphalt (HMA) surface course, most pavement rutting is caused by the deformation of the asphalt concrete, with about half the rutting amount observed within the top four inches of the pavement layers. However, for thin full-depth asphalt pavements with an SMA surface course, most pavement rutting comes from the closet sublayer to the surface, i.e., the intermediate layer. The accuracy of the MEPDG’s prediction models for thin full-depth asphalt pavement was evaluated using some statistical parameters, including bias, the sum of squared error, and the standard error of estimates between the predicted and actual measurements. Based on the statistical analysis (at the 95% confidence level), no significant difference was found between the version 2.3-predicted and measured rutting of total asphalt concrete layer and subgrade for thick and thin pavements
Assessment of Dynamic Modulus Testing of Airfield Asphalt Mixes Using Small-Scale Test Specimens [Technical Note]
Dynamic modulus is a fundamental property of viscoelastic materials and is typically used as an indicator of mix performance and input for the structural design of flexible pavements. Dynamic modulus can be measured in the laboratory using the Asphalt Mixture Performance Tester (AMPT) using the standard-size test specimen geometry (100-mm diameter by 150-mm length). However, determining dynamic modulus from specimens representing field conditions (field cores) is challenging because the lift thickness of pavement layers is usually less than 150 mm. Therefore, this study compared dynamic modulus test results measured from three airfield asphalt mixes using the standard-size and two small-scale test specimen geometries. The comparative study used several approaches, including evaluating dynamic modulus magnitudes, master curves, statistical variability, and modeled pavement responses from pavement analysis software. Overall, dynamic modulus values from small-scale test specimens show uniformity and good agreement compared to the standard geometry and present less than a 10% difference. Therefore, it is recommended to implement small geometries in dynamic modulus testing to determine performance properties in the laboratory. However, results from small-scale test specimens conducted at high temperatures may need a careful review before implementation since they show more variability and less consistency than the standard-size test specimen\u2019s results