Efficient Pavement Thickness Design for Indiana

Over the past several decades, a dramatic increase in traffic volume, axle loads, and tire pressure has led to rapidly deteriorated pavements in the United States. Several types of pavement surface distresses have been noted by many state agencies across the country. Among these distresses, permanent deformation, also known as rutting, is one of the most serious forms of flexible pavement distress. This research investigates the fundamentals of rutting behavior for full-depth flexible pavements. The scope incorporates an experimental study using full-scale accelerated pavement tests (APTs) to monitor the evolution of the transverse profiles of each pavement structural layer. The findings were then employed to improve the rutting model that is embedded in the current pavement design method, the Mechanistic-Empirical Pavement Design Guide (MEPDG). Four APT sections were constructed using two typical pavement structures and two types of surface course material. A mid-depth rut monitoring and automated laser profile system was 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 asphalt concrete does not increase with an increase in pavement thickness once the pavement is sufficiently thick. Additionally, most pavement rutting is caused by the deformation of the asphalt concrete, with about half the amount of rutting observed within the top four inches of the pavement layers and only around ten percent of rutting observed in the subgrade. A guideline was developed to calibrate the MEPDG prediction models using a database that contains both APT sections and field roadway segments and accounts for the rutting in individual pavement layers. A procedure was developed to provide the most faithful simulations of the APT conditions using virtual weather station generation, special traffic configuration, and falling weight deflectometer evaluation. The accuracy of the MEPDG’s prediction models was improved after the calibration process. The sum of squared error and the standard error of estimates between the predicted and actual measurements were reduced. No significant difference was found between the predicted and actual total asphalt concrete layer rutting and subgrade rutting at the 95 percent confidence level. Model validation using a jack-knife resampling technique confirmed that the calibrated models are able to provide accurate and statistically sound performance predictions. New calibration factors of the MPEGD rutting model from this study have been successfully implemented by the INDOT pavement design team since 2017

Intelligent Compaction of Asphalt Pavement Implementation

The main purpose of this research is to determine the possibility of substituting in-place core density (% Gmm) for Hot Mix Asphalt (HMA) Quality Assurance (QA) in Indiana Department of Transportation Specification with Intelligent Compaction (IC) measurements. A questionnaire survey and interviews were conducted to gather information on: (1) the usage of IC technology in other states, (2) the benefits of applying IC technology, and (3) the application of IC technology forQuality Control/ Quality Assurance (QC/QA). Also the data available from IC demonstration performed on US 52 in 2009 was analyzed to identify the relationship between in-place density values (i.e., Non-Nuclear Gauge, NNG)and the IC Measurement Values (ICMVs). According to survey responses from 26 agencies, there was no state DOT using IC for QA as of June 2014. Only twoDOTs, including Alaska and Vermont have adopted IC in HMA compaction for QC. The reasons for not using IC technology in current QC/QA practices were: (1) satisfaction with existing QC/QA procedure, (2) difficulty of adjustment due to the lack of specifications in determining stiffness in HMA, and (3) lack of availability of IC equipment with contractors. However, it was responded that the most benefits of IC was night time paving and uniform compaction in QC. Analysis of the ICMV data obtained from a demonstration project on US 52 indicated that a NNG correlation showed an R2 value of 0.67. This finding supports the IC implementation in the current INDOT HMA QC. It should be noted that a correlation between core-density and ICMV could not be determined due to lack of reliable data. In conclusion, the research could not identify any possibility of adding IC into the INDOT specification for QA based on the survey, phone interviews and analysis of the data obtained from IC demonstration on US 52

Development of Volumetric Acceptance and Percent Within Limits (PWL) and Criteria for Stone Metrix Asphalt (SMA) Mixtures in Indiana

SMA is to be designed based on SMA volumetric properties in terms of air voids content (Va), voids in the mineral aggregate (VMA), and adequate stone-on-stone contact. For construction quality assurance (QA) purposes, INDOT currently accepts SMAs based on aggregate gradation and asphalt binder content. Thus, there is a discrepancy between SMA design criteria and construction acceptance. To better align design and construction, it is necessary to consider SMA volumetric properties in the use of QA. For HMA mixtures, INDOT has already transitioned from volumetric QA acceptance procedures to PWL. Today, SMA still uses adjustment points not based on robust statistics for QA acceptance. SMA QA samples and QA data sets were collected from projects constructed in 2019 and tested in the laboratory. The Hamburg Wheel Track Test (HWTT) was performed on the 2019 QA samples to evaluate SMA rutting performance. Additionally, the PWL for HMA was applied to the 2019 SMA QA data to see if the HMA PWL method would work for SMA. Possible SMA QA measurements were compared to past QA data and HMA QA measurements. In addition, Voids in the Coarse Aggregate (VCA) was evaluated as a possible SMA QA measurement. Finally, using the suitable QA measurements for SMA, a PWL parameter study was performed to find PWL that provides a Pay Factor (PF) equivalent to the current SMA Adjustment Point (AP) PF. The current SMA QA measurements (binder content, gradation, and density) are recommended for Indiana\u27s SMA PWL. Based on the results of applying PWL to SMA QA data for the last four years, SMA PWL specification limits are recommended. Also, the SMA PF equations are suggested to get the SMA PWL to have PF equivalent to the current AP PF

Tooth Instance Segmentation from Cone-Beam CT Images through Point-based Detection and Gaussian Disentanglement

Individual tooth segmentation and identification from cone-beam computed tomography images are preoperative prerequisites for orthodontic treatments. Instance segmentation methods using convolutional neural networks have demonstrated ground-breaking results on individual tooth segmentation tasks, and are used in various medical imaging applications. While point-based detection networks achieve superior results on dental images, it is still a challenging task to distinguish adjacent teeth because of their similar topologies and proximate nature. In this study, we propose a point-based tooth localization network that effectively disentangles each individual tooth based on a Gaussian disentanglement objective function. The proposed network first performs heatmap regression accompanied by box regression for all the anatomical teeth. A novel Gaussian disentanglement penalty is employed by minimizing the sum of the pixel-wise multiplication of the heatmaps for all adjacent teeth pairs. Subsequently, individual tooth segmentation is performed by converting a pixel-wise labeling task to a distance map regression task to minimize false positives in adjacent regions of the teeth. Experimental results demonstrate that the proposed algorithm outperforms state-of-the-art approaches by increasing the average precision of detection by 9.1%, which results in a high performance in terms of individual tooth segmentation. The primary significance of the proposed method is two-fold: 1) the introduction of a point-based tooth detection framework that does not require additional classification and 2) the design of a novel loss function that effectively separates Gaussian distributions based on heatmap responses in the point-based detection framework.Comment: 11 pages, 7 figure

Tack Coat Installation Performance Guidelines

A tack coat is a thin application of asphalt (typically emulsified) used to bond pavement layers together so that they act monolithically. Lack of bonding can lead to fatigue cracking, delamination, slippage and other distresses. This study was undertaken to explore the impacts of various tack coat materials, application rates, and other variables on tack coat performance. The ultimate original goal was to develop a tack coat quality acceptance system. As the study progressed, some of the original objectives and tasks were modified or dropped. Laboratory testing of lab- and field-fabricated specimens using a monotonic direct shear test was used to evaluate the factors of interest. The findings showed that the most commonly used tack materials in Indiana, AE-NT and SS-1h, can perform, with the AE-NT exhibiting somewhat better performance overall. INDOT’s tack specifications could be clarified. The current applications rates are reasonable but could be refined to provide more guidance for use on different types of surfaces, as widely recommended nationally. The use of spray pavers and alternate tack materials should be further explored. Planned spray paver trial projects could provide the opportunity to expand on the results of this project, to explore other test methods, gain more experience with shear testing, and assess typical tack applications on non-experimental projects to assess the state of the practice. Additional implementation studies may help to refine a performance test and criteria for use to assess tack coat quality. The importance of tack coats should be emphasized to contractors and field personnel

Subsurface Condition Evaluation for Asphalt Pavement Preservation Treatments

This report presents a case study on the SR-70 section with microsurface for understanding its performance; a development of a methodology for evaluating the asphalt pavement subsurface condition for applying pavement preservation treatments; and a development of a tool for identifying and quantifying the subsurface distresses. From the case study, it was found that the main distresses on SR-70 were longitudinal cracks, fatigue cracks, and potholes. The longitudinal cracking was the most widely distributed distress with 22% of lane length in the 2-mile test section among the three distress types. Based on the water stripping test results and the core visual observations, it was confirmed that the test section on SR-70 had the water stripping problem. In order to have a representative condition indicator for the test section, the conditions were converted into the scores scaled from 0 to 100. Layers with closer to a score of 100 have the better subsurface condition. Therefore, the 28% of the test section length with the surface distress was detected as the fair subsurface condition with a score of 56. The rest 72% of the length was estimated as the good subsurface condition with a score of 78. Similarly, 20.5% of the test section length with the problem locations determined by GPR had the fair subsurface condition with a score of 56 and the rest 79.5 % of the length had the good subsurface condition with a score of 76. The lab test results showed poor correlations among the water stripping severities, air voids, and tensile strengths. Thus, the air voids or tensile strength cannot properly estimate the water stripping severity or vice versa. When the laboratory test results with the surface distresses or in the GPR-based problem locations were compared to that without the surface distresses or in the GPR-based non-problem locations, in general, average air voids and water stripping severities decrease and average tensile strengths increase. The observation confirms that the evaluation processes are applicable for evaluating the subsurface condition. Furthermore, the probability that a location determined to be problematic by GPR to be on one of poor conditions based on lab tests was 1.0. The same probability was obtained for a GPS-based problem location. Accordingly, it was concluded that the laboratory tests with the surface distresses survey or the GPR measurement were reliable method to evaluate the subsurface condition. The FWD results had a weak correlation with the laboratory test results possibly due to fairly long testing interval (i.e., 328 ft). The current FWD test protocol should be improved for evaluating the subsurface condition in pavement preservation application. Guidelines of subsurface condition evaluation for pavement preservation treatment application was developed utilizing the findings from the case study. A concept of hierarchy was used in the guideline by taking project importance and available resources into consideration. A tool including guidelines, computer software (e.g., iSub and iMoisture), and its manual was also developed based on the methodology as a research product. Based on the guideline, it was concluded that the subsurface condition of the case study section on SR-70 was inadequate for the application of the pavement preservation treatments

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

Verification of the Enhanced Integrated Climatic Module Soil Subgrade Input Parameters in the MEPDG

At the beginning of 2009, INDOT adopted the Mechanistic-Empirical Pavement Design Guide (MEPDG) method to study the tong-term pavement performance. The implementation of this new design approach led to difficulties for the pavement to pass the INDOT performance criteria; in particular pavement roughness (IRI) when A-6 or A-7-6 soils were considered as subgrade. This study focuses on investigating the influence of the soil input parameters in the Enhanced Integrated Climatic Model (EICM) on the prediction of the soil resilient modulus (MR) in the MEPDG. A total of four sites located around the state of Indiana are used to propose/validate the observations and conclusions made in the research. The study shows that (1) for the climatic conditions existing in Indiana, the location of the water table does not affect the value that the MEPDG uses for the subgrade MR; (2) the gravimetric water content is the most influential parameter on the EICM since it is directly related to the optimum degree of saturation of the subgrade; and (3) For A-7-6 soils, the overall deformation of the pavement structure is controlled by the subgrade (~80% of total deformation). In order to properly model the pavement structure, the MR input into the MEPDG for the subgrade should represent the optimum condition. This value will then be reduced within the EICM to reflect actual site conditions; and the MR input into the MEPDG for the treated layer should be a constant (i.e. not affected by EICM) and with PI and P200 values that are representative of the soil after treatment, given that the fines content and plasticity of a chemically-treated soil tend to decrease with treatment