Long-Term Pavement Performance Program Research Articles

Impacts of Climatic Regions and Design Factors on the Condition and Distress of Specific Pavement Test Sections in the Long-Term Pavement Performance Program

One of the objectives of the Long-Term Pavement Performance Specific Pavement Studies (SPS)-1 experiment was to examine the effects of climatic regions and various design factors on the performance of flexible pavements. In a research study sponsored by FHWA’s Long-Term Pavement Performance program, the impacts of climatic regions, drainage, and the thickness of asphalt concrete layers on the functional and structural performance of the flexible pavement test sections of the SPS-1 experiment were analyzed. Functional performance was analyzed on the basis of ride quality [determined by using the international roughness index (IRI) and safety (rut depth)]. Structural performance was analyzed on the basis of alligator, transverse, and longitudinal cracking and rut depth. For each SPS-1 test section, functional performance was represented by the remaining functional period (RFP), and structural performance was represented by the remaining structural period (RSP). Both metrics, the RFP and the RSP, were developed in this study to rate the performance of flexible, rigid, and composite pavement sections. This paper presents and discusses the results of the analyses of the performance of the SPS-1 test sections. It is shown that, as expected, pavement performance is a function of the climatic region. Wet–freeze regions had a significant impact on pavement performance in terms of the IRI, rut depth, and cracking, and drainable bases were found to be more effective in the wet–freeze region than in the wet–no-freeze, dry–freeze, and dry–no-freeze regions.

Recommended Procedure to Adjust Inaccurate Weigh-in-Motion Data

Weigh-in-motion (WIM) stations are used to monitor traffic volumes and loadings on roads and bridges. When a station is installed, a vehicle of known axle weights is typically used to calibrate the sensors. Because of environmental changes, pavement changes, sensor fatigue, and repeated loadings, the initial calibration doesn’t always maintain its validity. Therefore, the WIM station output must be monitored so that potential problems can be identified and corrected. It is common for analysts to discover that WIM data are inaccurate when they are attempting to use the data for design or planning. An analyst must then decide whether to conduct the analysis with inaccurate data or to not conduct the analysis at all. There is a need to develop a procedure that allows inaccurate WIM data to be adjusted and remain usable. Adjustment of WIM data after they have been collected may not be an acceptable practice to all agencies or for certain applications. A new accuracy metric was developed that relates Class 9 front axle weight with gross vehicle weight with data from the Long-Term Pavement Performance (LTPP) program. This new metric and other existing accuracy metrics in the literature will serve as baselines for adjusting the data. The adjustment procedure involves time series analysis, which eliminates temperature-induced variations in weight measurements that are known to occur with certain WIM sensors. The adjustment procedure is applied to an LTPP WIM station to illustrate the data before and after adjustment.

Global Procedure for Temperature Adjustment of Measured Pavement Deflection Data: Based on the Long-Term Pavement Performance Seasonal Monitoring Program

Pavement surface deflection testing is carried out by most state highway agencies (SHAs) on a limited basis to assess the structural capacity of existing pavements and to select and design pavement treatments. One difficulty with analyzing pavement deflection data is that, for flexible pavements, the deflection is dependent on temperature. To properly use the deflection data, the data should be adjusted on the basis of the measured temperature during the data collection process. A few temperature adjustment procedures have been developed in the past, but most cannot be used globally and for all scenarios and they require input data that are generally not collected by most SHAs. This paper details a simplified process that can be easily used by SHAs to adjust the measured pavement deflection to a 21°C testing scenario, with data they routinely collect during falling weight deflectometer testing, to design pavement treatments such as asphalt overlay. During this study, sponsored by the Long-Term Pavement Performance (LTPP) program, the LTPP database was used to develop a global procedure to adjust the measured pavement deflection to the standard testing temperature of 21°C. Most of the LTPP test sections have been subjected to deflection testing on a periodic basis; test sections included in the LTPP Seasonal Monitoring Program were subjected to frequent deflection testing over time. The 41 test sections included in the analyses had different pavement cross sections, were subjected to various maintenance activities, were located in four climatic regions, and were subjected to various traffic levels. This robust deflection database is representative of the various SHA pavement networks across North America. The results and the processes can be adopted to meet the needs of most SHAs.

Validation of Long-Term Pavement Performance Prediction Models for Resilient Modulus of Unbound Granular Materials

Reliable characterization of unbound granular material and subgrade resilient modulus requires repeated load triaxial testing, advanced dynamic loading equipment, and technical experience not typically available in many geotechnical laboratories. For Level 2 design inputs, the Mechanistic–Empirical Pavement Design Guide recommends correlation models to estimate the resilient modulus of unbound granular material and subgrade from basic material properties (e.g., gradation, unconfined compressive strength, and California bearing ratio). These correlation models are developed from data on a wide range of soil and material types; this wide range increases the associated error with resilient modulus prediction. This paper compares laboratory measured resilient modulus for two types of locally available unbound granular materials to the predicted values; models developed under the Long-Term Pavement Performance (LTPP) program were used. Resilient modulus tests of six gradations of two types of material—100% crushed limestone and gravel—were conducted at two levels of moisture content. Results showed that the LTPP models significantly underestimated resilient modulus for the limestone material and showed high residuals associated with evaluating resilient modulus of both gravel and limestone materials. The coefficient of variation of the root mean square error was 50.3% for gravel and 55.6% for limestone. The high residuals associated with evaluating resilient modulus with the LTPP models justify the development of local prediction models to improve the reliability of Level 2 design inputs for unbound granular materials.

Local calibration of rigid pavement performance models using resampling methods

The performance prediction models in the Pavement-ME design software are nationally calibrated using in-service pavement material properties, pavement structure, climate and truck loadings, and performance data obtained from the Long-Term Pavement Performance programme. The nationally calibrated models may not perform well if the inputs and performance data used to calibrate those do not represent the local design and construction practices. Therefore, before implementing the new M-E design procedure, each state highway agency (SHA) should evaluate how well the nationally calibrated performance models predict the measured field performance. The local calibrations of the Pavement-ME performance models are recommended to improve the performance prediction capabilities to reflect the unique conditions and design practices. During the local calibration process, the traditional calibration techniques (split sampling) may not necessarily provide adequate results when limited number of pavement sections are available. Consequently, there is a need to employ statistical and resampling methodologies that are more efficient and robust for model calibrations given the data related challenges encountered by SHAs. The main objectives of the paper are to demonstrate the local calibration of rigid pavement performance models and compare the calibration results based on different resampling techniques. The bootstrap is a non-parametric and robust resampling technique for estimating standard errors and confidence intervals of a statistic. The main advantage of bootstrapping is that model parameters estimation is possible without making distribution assumptions. This paper presents the use of bootstrapping and jackknifing to locally calibrate the transverse cracking and IRI performance models for newly constructed and rehabilitated rigid pavements. The results of the calibration show that the standard error of estimate and bias are lower compared to the traditional sampling methods. In addition, the validation statistics are similar to that of the locally calibrated model, especially for the IRI model, which indicates robustness of the local model coefficients.

Effectiveness Analyses of Flexible Pavement Preventive Maintenance Treatments with LTPP SPS-3 Experiment Data

AbstractThe present study analyzes the effectiveness of preventive maintenance (PM) treatments of flexible pavements utilizing data obtained from the specific pavement study 3 (SPS-3) of the long-term pavement performance (LTPP) program online database. The PM treatments included in this study are thin hot mix asphalt (HMA) overlay, chip seal, slurry seal, and crack seal. International roughness index (IRI), rutting, fatigue cracking, longitudinal cracking, and transverse cracking were selected as indicators of pavement performance. Initial roughness change, long-term roughness change, and weighted distresses are used as measures of effectiveness. The logistic regression model is employed to investigate the influence of pretreatment roughness condition, pretreatment surface condition, and several other factors on the performance of PM treatments. Results from this study indicate that only thin overlay and chip seal are effective in retarding fatigue cracking. Thin overlay was also the only treatment effec...

Performance Trends on Interstate Highway Sections of the Long-Term Pavement Performance Program

The Moving Ahead for Progress in the 21st Century Act required FHWA to identify pertinent performance measures and to establish minimum acceptable levels for infrastructure condition. Because of differences in data collection and analysis between state highway agencies (SHAs), a comparison of the performance data from states is not viable. The Long-Term Pavement Performance (LTPP) sections are spread across various states but have been monitored following the same standards. With the use of LTPP data, analyses were conducted to gain insight into actual deterioration rates and the impact of maintenance and rehabilitation activities on the performance of Interstate highway pavements. An evaluation of the decline in longitudinal and transverse profiles showed that about 90% of pavement sections had experienced nominal changes from year to year. The reason for these changes could be that SHAs had been actively applying preservation strategies. The average annual rate of roughness progression increases when the surface ages. The highest annual rate of increase in the international roughness index (IRI) occurs when the surface is between 8 and 12 years old for flexible pavements and between 16 and 20 years old for rigid pavements. The percentages of significant annual changes (more than 20%) were approximately the same between increasing and decreasing IRI rates. These figures could mean that SHAs had been addressing roughness with proper treatments at the same rate as roughness had been progressing. In agreement with previous research findings, the current work found that milling before overlay increased the average IRI reduction but did not improve the effectiveness of overlays in reducing rutting.

Failure Probability of Resurfaced Preventive Maintenance Treatments

This study evaluated the effectiveness of various pavement preventive maintenance treatments through investigation of the failure probability of different performance indicators, including roughness, alligator cracking, longitudinal cracking, transverse cracking, rutting, and friction. For the study, 354 resurfacing pavement preventive maintenance projects were collected from the Long-Term Pavement Performance program database, including ones that used thin asphalt overlay, chip seal, slurry seal, and fog seal. Survival models were employed to conduct the analyses because of their capability to capture unobserved failure events and to systematically incorporate influencing factors (e.g., traffic, climate, pavement structural capacity, and pretreatment pavement performance). The statistical analysis showed that poor pretreatment performance was a significant factor in treatment failure and that preventive treatments would not be effective on pavement in poor condition. Stronger structural capacity of pavement greatly reduced fatigue cracking on the treatment surface: the bending of asphalt layer was alleviated through stronger base and subgrade support. Climate factors had a significant influence on the failure of transverse cracking and rutting and on friction loss. A warmer climate tended to cause permanent deformation and friction loss, probably as the result of asphalt softening. In general, chip seal was the most effective overall, followed by thin asphalt overlay, slurry seal, and fog seal. However, chip seal was vulnerable to friction loss: the aggregates could be pulled out as a result of the loss of asphalt adhesion.

Application of time–temperature superposition to develop master curves of cumulative plastic strain in repeated load permanent deformation tests

The repeated load permanent deformation (RLPD) test is used to capture the permanent deformation characteristics of asphalt mixtures for prediction of pavement rutting. The full characterisation of permanent deformation behaviour as required by the National Cooperative Highway Research Program (NCHRP) Project 9-30A enhanced rutting model requires time-consuming RLPD tests at three temperatures – low, intermediate and high. This study investigates the application of time–temperature superposition (TTS) to reduce the material characterisation testing effort in the context of the NCHRP 9-30A models. Dynamic modulus and RLPD test data were collected for 27 mixtures, including mixtures from long-term pavement performance (LTPP) programme. The temperature shift functions obtained from dynamic modulus data were used to shift the associated RLPD test results at various temperatures to develop a master curve of cumulative permanent strain versus reduced number of loading cycles. The cumulative permanent strain curves at different temperatures collapsed fairly well into a single RLPD master curve for the evaluated mixtures, confirming the validity of TTS for the RLPD test. The TTS procedure was also applied individually to the test results at a single temperature to predict the permanent strains at the other temperatures. The results from the 27 mixtures suggest that the RLPD master curve obtained by testing only at the high temperature (LTPPBind high temperature at 50% reliability – 5°C) permits accurate and precise predictions of the permanent deformations at all other temperatures. RLPD testing at a single temperature has the real practical benefit of significantly streamlining the asphalt material characterisation testing programme.

Performance Evaluation of Asphalt Overlays in Alberta Using Long Term Pavement Performance Specific Pavement Study 5 Sections

Performance data collected for the Long Term Pavement Performance program (LTPP)'s Specific Pavement Studies (SPS) 5 in Alberta was used to investigate overlay performance in Alberta's climate conditions. Comparison of peak deflection during the Falling Weight Deflectometer (FWD) test for different overlay sections with respect to the control section in seven test years showed that all overlays improved structural capacity of the pavement. The overlay thickness was found to be the most statistically significant factor to the pavement's structural response in comparison to pre-overlay conditions (milling) and asphalt mixture type. Further, overlay thickness and mixture type were found to be the most effective factors to alligator and transverse cracking, respectively. The Mechanistic Empirical Pavement Design Guide (MEPDG)-predicted International Roughness Index (IRI) was higher than the measured values in most years. The MEPDG-predicted pavement rutting was most sensitive to pavement structural design.

Relationship between Traffic Loading and Environmental Factors and Low-Volume Road Deterioration

Many countries use some form of model to determine road user charges. Trucks are expected to pay for most of the cost because heavy vehicles are responsible for most of the deterioration of roads. This research documents findings that will ultimately be used to refine the New Zealand road user charge models. The research was undertaken on data from the Long-Term Pavement Performance Program with the specific aim of determining the relative damage caused by heavy-vehicle loading alone compared with the combined effects of loading and environmental impacts. As part of the overall research process, a cluster analysis was undertaken. The results from this analysis also emphasized the importance of drainage. The cluster analysis resulted in a recommended stratification of low-volume roads on the basis of their urban or rural location, traffic loading, and climatic area. This stratification could be used for a more detailed implementation of a user charge model if needed. On similar low-volume roads, an approximate 0.1-mm/year higher rut rate was observed in areas that had a wetter climate in combination with sensitive in situ soil conditions. The results also illustrated that adequate drainage was vital for limiting environmental impacts. Roads with inadequate drainage had a rut rate 2.5 times as high as that of roads with the necessary provision for drainage.

Characterising the elastic behaviour of fine-grained subgrade soils under traffic loading

Resilient modulus is a measure of the elastic behaviour of subgrade soil under traffic loading. The design thickness of a pavement structure and its predicted performance are highly dependent on subgrade modulus. Characterisation of subgrade resilient modulus involves conducting advanced repeated loading triaxial testing that requires special equipment and technical experience that are not available in many soil laboratories. The objectives of this paper were to characterise the resilient modulus of typical fine-grained subgrade soils and develop design inputs for the Mechanistic-Empirical Pavement Design Guide. The resilient modulus of subgrade soil samples was tested at different levels of moisture content. Results of the laboratory testing were used to develop prediction models for resilient modulus as function of physical properties of the subgrade soil and stress state. The proposed models were compared to those developed under the Long-Term Pavement Performance programme. The results showed that the proposed models provided more reliable predictions with lower root mean square error.

Influence of road profile obstacles on road unevenness indicators

The study quantified the influence of the road profile obstacles on 27 different road unevenness indicators (RUI). The influence of obstacle height, length and number of obstacles per kilometre was assessed. The 2997 real longitudinal road-profile records from the Long-Term Pavement Performance program with considering asphalt concrete and cement concrete road surfaces were processed. 5169 obstacles were identified by a median filtering approach and their dimensions were quantified. The regression function based on linear coefficients for dependence of the RUI on three obstacle parameters was derived. The marked dependence of the road indicators on all three obstacle parameters was observed. The road indices describing the short wavelength band proved to be the most sensitive for detecting obstacle presence in a road profile.

Using a multi-phase model to predict flushing of sprayed seal pavements

Flushing is a pavement defect that has a negative effect on the structural integrity and performance of a pavement surface. The aim of this study was to develop a model to predict the occurrence and progression of flushing on sprayed seal pavements. Data analysis and model development were performed using data sourced from New Zealand's Long-Term Pavement Performance programme. The developed model consists of two phases to model (1) the probability of flushing initiating on a pavement and (2) the progression of flushing. The probability of flushing initiation was modelled using a logistic model format, and the progression of flushing was modelled using a linear model format. Testing of the developed model revealed that the logistic model predicted the probability of flushing initiation at 76% accuracy, whereas the linear model had statistically robust predictions of flushing. The developed model is recommended for use in sprayed seal pavement management processes.

Development of a mechanistic-empirical prediction model for joint spalling distress in concrete pavements

Joint spalling has been a typical distress problem in concrete pavements and an open research interest to many pavement engineers. However, most prediction models for joint spalling distress are developed only based on empirical observations from the field and the accuracy of the empirical models has been a question because there is a lack of mechanistic investigation to understand the detail mechanism. In this paper, a reliable spalling prediction model was developed on the basis of shear mechanism under both traffic loads and thermal curling. According to the concept of shear mechanism, the finite element method (FEM) is applied to analyze the numerical responses of pavement structure. A three-dimensional FE pavement model is developed based on the field section information obtained from Korean long-term pavement performance (LTPP) program. The principle shear stress obtained from FE analysis is accumulated at specific pavement age to evaluate its impact on the formation and the growth of joint spalling. A mechanistic-empirical (M-E) spalling prediction model is developed by relating the shear stress accumulation (SSA) to the filed performance of spalling. The proposed M-E prediction model is verified by using various field data from Korean LTPP to indicate its applicability to predict the spalling distress.

Impact of Various Trucks on Pavement Design and Analysis

This investigation assessed the sensitivity of Mechanistic–Empirical Pavement Design Guide (MEPDG) outcomes to normalized axle load spectra representing various loading conditions observed in the Specific Pavement Studies Transportation Pooled Fund Study of the Long-Term Pavement Performance program. The goal was to determine what vehicle classes and axle types with a wide range of axle loading conditions are likely to cause differences in pavement design outcomes when the MEPDG is used. Significant differences found in the MEPDG outcomes support the need for characterization of axle loading beyond a single default value for heavy trucks that dominate vehicle class distributions, especially for Class 9 trucks. The absence of differences for lightweight and under-represented trucks indicates that load spectra from various sites could be combined to develop a single default for some vehicle classes and axle types. The effect of bias in weigh-in-motion (WIM) axle weight measurements on the normalized axle load spectra estimates and the associated MEPDG outcomes was also investigated. It was found that drift in WIM system calibration leading to a more than 5% bias in mean error between true and WIM-measured axle weight could lead to significant differences in MEPDG design outcomes. These results were used to develop recommendations for creating axle loading defaults for the MEPDG.

Forensic Evaluation of the LTPP Specific Pavement Study Projects in Arizona

This paper presents a forensic investigation of selected Arizona specific pavement study (SPS) SPS-5 test sections. The investigation focused on identifying the causes of pavement failures, examining the pavement structural and functional performances, and measuring within-section layer thicknesses and material properties. In addition, the investigation addressed the potential effects of overlay thickness and overlay materials used (recycled and virgin asphalt) and the extent of surface preparation (minimum and intensive) on pavement performance. Destructive and nondestructive tests were conducted following the long-term pavement performance (LTPP) program test protocols. The main pavement distresses identified in the test sections included fatigue cracking, longitudinal cracking, transverse cracking, rutting, block cracking, and pumping. Based on the observations of the coring and trenching operations, most of the cracks were top-down cracks exhibiting high severity at the top and low severity at the bottom of the layer. Wheelpath rutting was observed in the overlay layer only, and virtually no rutting was detected in the lower layers. The maintenance activities (fog seals and crack sealing) applied over the years appeared to have reduced the propagation of fatigue and transverse cracks temporarily and did not significantly improve the postrehabilitation structural performance. While all sections performed well compared with the virgin asphalt overlay, the recycled overlay test sections exhibited the largest postrehabilitation rate of increase in roughness and rutting (with thinner overlays) over their monitoring period. Pavement deterioration was not associated with the base and subgrade layers. The extent of distress was also found to be associated with high binder content and air voids.

Ordinal Logistic Regression Model for Predicting AC Overlay Cracking

Predicting performance of asphalt concrete (AC) overlay is important for both pavement design and management. Based on 328 AC overlay sections from the long-term pavement performance (LTPP) program, ordinal logistic regression models were developed in this study to predict the probability of severity levels for alligator cracking. It was found that the alligator cracking is significantly affected by alligator cracking of the existing pavement, thickness of overlay, thickness of the existing AC, age of pavements after resurfacing, truck volume, freeze-thaw cycles, and the amount of precipitation per wet day. In addition, it was found that the use of recycled asphalt pavement in the amount specified in the SPS 3 experiment and preoverlay treatment significantly affect overlay cracking. Both statistical conformance tests and empirical verification using independent data indicate that the developed models are reasonably accurate. The model can generate the probability of a pavement staying at a certain distress level and the odds ratio, which enables highway agencies not only predict probability of cracking but also assess the confidence of making such predictions.

Mechanistic Approach to Pavement–Vehicle Interaction and Its Impact on Life-Cycle Assessment

The accuracy and the comprehensiveness of any pavement life-cycle assessment are limited by the ability of the supporting science to quantify the environmental impact. Pavement–vehicle interaction represents a significant knowledge gap that has important implications for many pavement life-cycle assessment studies. In the current study, the authors assumed that a mechanistic model that linked pavement structure and properties to fuel consumption could contribute to closing the uncertainty gap of pavement–vehicle interaction in life-cycle assessment of pavements. The simplest mechanistic pavement model, a Bernoulli–Euler beam on a viscoelastic foundation subjected to a moving load, was considered. Wave propagation properties derived from falling weight deflectometer time history data of FHWA's Long-Term Pavement Performance program were used to calibrate top-layer and substrate moduli for various asphalt and concrete systems. The model was validated against recorded deflection data. The mechanistic response was used to determine gradient force and rolling resistance to link deflection to vehicle fuel consumption. A comparison with independent field data provided realistic order-of-magnitude estimates of fuel consumption related to pavement–vehicle interaction as predicted by the model.

Relating Ride Quality and Structural Adequacy for Pavement Rehabilitation and Management Decisions

Ride quality and structural adequacy are key pavement performance indicators. The relationship between these indicators has been a topic of frequent and continuing discussion in the pavement community, but an accepted and widely used relationship has not yet been identified. The objective of this study was to identify and verify the relationship between these two performance indicators, if any, with data from the Long-Term Pavement Performance Program. This study was meant to improve the evaluation and use of pavement condition data in pavement rehabilitation and design decisions. More specifically, it was intended to develop and document a mechanism to include values of both ride and structural adequacy within the context of current network-level pavement management system practices for highway agency implementation to ensure smooth pavements that are also structurally adequate. To accomplish the study objective, two major activities were carried out: a literature search to gather, review, and synthesize available information on relating ride quality and structural adequacy and a review and assessment of data from the Long-Term Pavement Performance Program to determine if such a relationship exists. These two activities—as well as their major findings, observations, and conclusions—are detailed; a viable relationship could not be identified.