Mechanistic-Empirical Pavement Design Research Articles

Evaluation of four different climate sources on pavement mechanistic-empirical design and impact of surface shortwave radiation

ABSTRACT This paper compares the predicted distresses (via in the AASHTOWare Pavement ME Design software (PMED)) of asphalt concrete (AC) and jointed plain concrete pavement (JPCP) using four different climate data sources. These sources also include the Modern Era Retrospective Analysis for Research and Application (MERRA) Versions 1.0 and 2.0 (MERRA-1 and MERRA-2). Pavement performance predictions generated using these data showed disagreement among some of the climate data sources, especially for MERRA-2. Comprehensive diurnal and other time-series analyses of the raw climate data found significant disagreements in the percent sunshine estimates. Percent sunshine is used in the PMED environmental effects model to semi-empirically estimate the downwelling shortwave radiation reaching the pavement surface. Both MERRA data (MERRA -1 and MERRA-2) independently provide direct predictions of downwelling surface shortwave radiation (SSR). The direct model predictions of SSR were used to back calculate ‘synthetic’ per cent sunshine for input into the PMED. The use of the synthetic per cent sunshine derived from the predicted SSR eliminated nearly all discrepancies in the predicted pavement performance using MERRA-1 versus MERRA-2 data. Based on these results, the authors recommend that SSR rather than per cent sunshine be used as a direct input to the PMED.

A binary logistic model for predicting the tertiary stage of permanent deformation of conventional asphalt concrete mixtures

Since the advent of Mechanistic-Empirical Pavement Design Guide (M-EPDG), characterisation of asphalt concrete (AC) mixtures using flow number remains the topic of interest for most of the literature. Consequently, many flow number models have been proposed in the literature, which only caters AC mixtures that attain the tertiary stage of permanent deformation (PD). The literature is devoid of any study that ascertain, whether an AC mix would attain the tertiary stage of PD or otherwise. As such, this study develops a binary logistic model as a function of volumetric and performance parameters of field and laboratory prepared AC mixtures using the standard maximum likelihood procedure. The logistic model specification is best suited to predict the mix probability of attaining the tertiary stage of PD. More specifically, an increase in air voids and percent passing sieve #200 in the mix and relatively low value of dynamic modulus translated into an increased probability of attaining the tertiary stage of PD. The field and laboratory mixtures are compared using the binary logistic model and a sensitivity analysis is also performed on the model. The comparison reveals the difference in both the type of mixtures, and suggests optimising and customising the laboratory mixtures to the field conditions.

Development of Resilient Modulus Prediction Model for Granular and Noncohesive Soils of New Mexico

Abstract The resilient modulus (MR) of unbound materials, i.e., base and subgrade, is an essential property for the Mechanistic-Empirical Pavement Design Guide (MEPDG). The MR of the unbound materials is highly dependent upon several factors such as physical properties of the materials, soil type, stress state, and moisture content. The MR values are usually determined by conducting repeated load triaxial compression tests in the laboratory. However, because of the complexity, difficulty, huge time, and effort associated with it, development of an MR prediction model based on soil physical properties has increasingly become an imperative. In this study, a model is developed to estimate the MR of base and noncohesive (A-2-4) subgrade soils that are commonly available in the state of New Mexico from a set of materials’ physical properties. First, subgrade and granular materials have been collected from different construction sites, and a laboratory MR test is conducted in accordance with the test standard AASHTO T-307, Standard Method of Test for Determining the Resilient Modulus of Soils and Aggregate Materials. The pertinent material constants (k1, k2, and k3) in the constitutive model have been evaluated from the laboratory test data using regression analysis. Materials coefficients are correlated to the selected physical properties. A new set of laboratory test results for another pavement site is used to verify the model. It is observed that the prediction model predicts MR values that agree well with the laboratory results. Therefore, the proposed model can be applied to the base and noncohesive subgrade soils for implementation in MEPDG.

Effects of Mix Factors on the Mechanistic-Empirical Flexible Pavement Design

This study investigates the sensitivity of the mechanistic-empirical flexible pavement design performance parameters such as cracking, rutting, and smoothness to mix factors for 11 categories of hot-mix asphalt (HMA) mixtures. For each category of HMA mixture, the variations in the pavement performances for different effective binder content (Vbe), air void (Va), voids-in-mineral aggregates (VMA), voids-filled-with asphalt (VFA), and asphalt content (AC) are examined by the AASHTOWare Pavement Mechanistic-Empirical Design, simply the AASHTOWare software analysis. Five types of distresses: international roughness index (IRI), total rutting, rutting in the HMA layer, bottom-up fatigue cracking, and top-down longitudinal fatigue cracking are considered in the analysis. Results show that the prediction of distresses values after 20-year of service life using the AASHTOWare software may differ by up to 170% for different specimens of a certain mix design. All distresses, except rutting, increase in Va, VMA, and VFA. Rutting in HMA increases with an increase in VMA and VFA, and is insensitive to Vbe, Va, and AC in the study range of these parameters.

A Comparison between the Empirical and Mechanistic-Empirical Pavement Design Methods

In this paper a comparative study has been carried out between the Mechanistic-Empirical Pavement Design Methods and the Empirical Pavement Design Methods. For the purpose of this paper, nine pavement design sections have been prepared using the Mechanistic-Empirical Methods represented by the Asphalt Institute Design Method (SW-1 software of the Asphalt Institute) and the Empirical Design represented by AASHTO 1993 and TRL Road Note No.31, using the same traffic loading and subgrade strength. Three traffic loading scenarios have been considered for this study.
 (Key words: Mechanistic-Empirical, Empirical, axle loads, Subgrade Strength, pavement design)

Performance evaluation of sulfur as alternative binder additive for asphalt mixtures

The performance of sulfur as alternative binder additive in asphalt mixtures was presented in this study. The effect of different sulfur contents was investigated to evaluate the rutting and cracking performances of sulfur modified asphalt mixtures. First, the engineering properties and morphologies of the sulfur modified asphalt binder were investigated using traditional binder tests and the Scanning Electron Microscopy (SEM). Second, further testing was conducted such as the Marshall stability (MS) test, wheel tracking (WT) test, indirect tensile (IDT) test, and indirect tensile fatigue (IDTF) test, to evaluate the performance resistance of sulfur modified asphalt mixtures. It was found that the sulfur modified binder can improve not only the mechanical properties of asphalt binder but also the rutting performance as well as cracking resistance of asphalt pavement significantly. Finally, the performance of sulfur modified asphalt mixtures was evaluated using the mechanistic empirical pavement design guide (MEPDG) program. Based on the results of the study, it can be concluded that the addition of sulfur can enhance the performance of asphalt mixtures significantly.

A-VTS model of bitumen viscosity transformed and made continuous across families of grades

ABSTRACT In current design procedures, asphalt binder grades are represented by tables of potential parameter values. In the Mechanistic-Empirical Pavement Design Guide these are A-VTS pairs. The discreteness of the grade choice prohibits both the use of gradient-based search as well as analytic methods to find an optimal solution. In this paper, we represent that information with continuous equations that are empirically nearly equivalent. A demonstration is presented using values from the Mechanistic-Empirical Pavement Design Guide documentation. Next, a method is presented to remove the unfortunate attribute of the A-VTS model, that it cannot be converted across units of measurement and still retain the same functional form. It is shown that the A-VTS model has a hidden parameter. If the third parameter is restored, the model of viscosity can be translated across units of measurement without changing its functional form. Finally, a method is presented to model the viscosity such that the parameters of the model are independent of the temperature units in which the parameters are estimated. This is an improvement over today’s situation where parameter estimates are incomparable across units of measurement. Now, parameters can be compared even if the experiments are carried out in different measurement units.

Effects of quantity and plasticity of fine particles on the workability and resilient behaviour of aggregate-soil mixtures for granular pavement layers

The paper presents the results of a laboratory investigation seeking to quantify the effects of fine quantity and type on the workability and resilient response of aggregate-fine soil mixtures for subbase formation. Laboratory devices were used to simulate in-field conditions and compact samples and evaluate their resilient response under pulsing loads. Four different types of fines passing through a 63 µm sieve (one non-plastic silt and three silty-clays exhibiting plastic behaviour) in three different quantities (5.4, 10.8 and 16.2%) were combined with coarser aggregates while maintaining the same grading distribution. A variant of the generalized model proposed in the Mechanistic Empirical Pavement Design Guide was calibrated to distinguish the contribution of fine type to resilient modulus from that of moisture content and suction. The results evidenced an improvement in mixture workability during the compaction process when using plastic fines instead of non-plastic ones. However, the quantity of plastic fines should be limited (lower than 10.8% within the aggregate skeleton) in order to achieve a high compaction level and to attain a hardening resilient behaviour rather than the softening one observed in the case of granular materials containing non-plastic fines.

Evaluation of Clustered Traffic Inputs for Mechanistic-Empirical Pavement Design: Case Study in New Jersey

Truck traffic is one of the significant inputs in design and analysis of pavement structures. This paper focuses on comprehensive cluster analysis of truck traffic in New Jersey for implementation of mechanistic-empirical pavement design. Multiple year traffic data were collected from a large number of weigh-in-motion stations across New Jersey. Statistical analysis was first conducted to analyze directional and temporal (yearly) variations of traffic data. Hierarchical cluster analysis was conducted and three optimum clusters were found for axle load spectra (single, tandem, tridem), vehicle class distribution, and axle/truck ratio, respectively. Road functional classifications were employed to identify different clusters as no common geographic trend could be perceived. The results illustrate that the predicted performance using the site-specific traffic data is comparable with that using the traffic cluster for the selected 10 sites. Among four different traffic inputs, the cluster traffic inputs generated the closest predictions of pavement life as compared with those using site-specific traffic input and the default traffic inputs yielded the highest error. It is recommended to use traffic clusters in mechanistic-empirical pavement design when site-specific data is unavailable.

Optimization of Lateral Wandering of Automated Vehicles to Reduce Hydroplaning Potential and to Improve Pavement Life

The deployment of automated vehicles (AVs) has many potential benefits, such as reductions in congestion and emissions, and safety improvements. However, two notable aspects of AVs are their impact on roadway hydroplaning and pavement life. Since most AVs are programmed to follow a set path and maintain a lateral position in the center of the lane, over time, significant rutting will occur in asphalt surfaced pavements. This study measured AV lateral wandering patterns and compared them with human driven vehicles. Both wandering patterns could be modeled with a normal distribution but have significantly different standard deviations. AVs have a standard deviation for the lateral traffic wander pattern at least three times smaller than human driven vehicles. The influences of AVs with smaller lateral wandering on pavement rutting and fatigue life were analyzed with the Texas Mechanistic-Empirical Flexible Pavement Design system. The research discovered that AVs would shorten pavement fatigue life by 20%. Additionally, pavement rut depths (RD) increased by 13% and reached critical values of the RD 30% earlier. Deeper ruts formed more quickly leading to thicker water films on wet roads, and consequently, a much higher risk of hydroplaning. The research also calculated maximum tolerable RDs at different hydroplaning speeds. AVs have a much smaller tolerable RD human driven vehicles because of a greater water film in the rutted wheel path. This research thus proposed an optimal AV lateral wandering pattern: a uniform distribution. A uniformly distributed lateral wandering pattern for AVs prolongs pavement fatigue life, reduces pavement RD, and decreases hydroplaning potential.

Updating Traffic Inputs for Use in the Pavement Mechanistic-Empirical Design in Michigan

A study, completed in 2009, characterized traffic inputs in support of implementing the new Mechanistic-Empirical Pavement Design Guide for the state of Michigan. The inputs included monthly adjustment factors, hourly distribution factors, vehicle class distributions, axle groups per vehicle, and axle load distributions for different axle configurations. During the last 7 years, new traffic data were collected that reflect recent economic growth, and additional and downgraded weigh-in-motion (WIM) sites. Performance models for the Pavement mechanistic-empirical (ME) design were recently calibrated to local conditions in Michigan. Hence it was appropriate to incorporate these changes in the re-evaluation of traffic inputs. Weight and classification data were obtained from 41 WIM sites throughout the Michigan to develop Level 1 (site-specific) traffic inputs. Cluster analyses were conducted to develop Level 2A inputs. Classification models (decision trees, random forests) were developed to assign a new site to these clusters; however, this proved difficult, hence, an alternative, simplified method to develop Level 2B inputs by grouping sites with similar attributes was also adopted. The optimal set of attributes for developing Level 2B inputs was identified by using an algorithm developed in this study. The effects of the developed hierarchical traffic inputs on the predicted performance of rigid and flexible pavements were investigated using Pavement-ME. Based on the statistical and practical significance of the life differences, appropriate levels were established for each traffic input. The methodology for developing traffic inputs is intuitive and could easily be adopted by Michigan Department of Transportation for future updates.

Accuracy of MEPDG Dynamic Modulus Predictions for Short-Term and Long-Term Aged Asphalt Mixtures

AbstractThis study examines the accuracy of dynamic modulus, |E*|, predictions made by the Mechanistic-Empirical Pavement Design Guide (MEPDG) for short-term and long-term aged hot mix asphalt (HMA...

Comparative Analysis between Modern-Era Retrospective Analysis for Research and Applications and Updated Mechanistic-Empirical Pavement Design Guide Climate Database in the State of Tennessee

The Mechanistic-Empirical Pavement Design Guide addresses climate effects on pavement design in a comprehensive way, which allows for investigating the effect of climate on pavement performance. However, it requires detailed climate inputs, which might not be readily available for most of the state departments of transportation. The AASHTOWare Pavement Mechanistic-Empirical Design (PMED) version 2.3 (v2.3) climate database encompasses 12 weather stations in the state of Tennessee, which does not satisfactorily represent all climatic regions in the state. The terrain in Tennessee varies from flat in the west to mountainous in the east. To evaluate the effectiveness of the updated AASHTOWare PMED v2.3 climate data input, this study analyses the performance of selected pavements in the state of Tennessee using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and the AASHTOWare PMED v2.3 databases as sources of PMED climate data inputs. A comparative analysis of the two climate data sources is conducted using eight long-term pavement performance (LTPP) sites in the state of Tennessee. The study revealed that MERRA as a climate data source for the state of Tennessee offers better geographic coverage, and therefore provides more precise distress predictions than the AASHTOWare PMED v2.3 climate database.

Development of a mechanistic-empirical model to predict equilibrium suction for subgrade soil

Suction in subgrade layer reaches an equilibrium condition several years after construction of the pavement. The equilibrium suction has a direct influence on the resilient modulus of subgrade soil. In the current mechanistic-empirical pavement design guide, equilibrium suction is determined based on the empirical relationship with water table depth. However studies have shown that other critical factors also influence equilibrium suction. In this study, a new mechanistic-empirical model is presented to predict equilibrium suction considering the effects of physical properties of the soil and climatic factors. A simple regression model is also generated to predict the equilibrium suction from readily available parameters i.e., Thornthwaite moisture index (TMI), plasticity index (PI), and dry suction value at surface (udry). In the final section of this paper, the effects of TMI and vegetation on equilibrium suction are evaluated for various soil classes and TMI ranges, respectively. A contour map of the equilibrium suction values for the entire continental United States has been generated using the geographic information system (GIS) platform and followed by the model predictions.

Recycling waste packaging tape into bituminous mixtures towards enhanced mechanical properties and environmental benefits

The rapid development of online shopping and express delivery brings vast amount of waste packing tape (WPT). Recycling WPT as an asphalt performance-enhanced modifier may bring benefits in both environmental and engineering aspects. This study aimed to evaluate the feasibility of using WPT to improve the mechanical properties of asphalt mixtures. To this end, the hot and warm WPT mixtures were prepared and tested. The engineering performance including mixture workability, stiffness modulus, fatigue resistance, rutting resistance, moisture susceptibility, tensile strength and tensile failure strain were characterized. Moreover, the long-term service performance of the mixture was predicted using AASHTO Mechanistic-Empirical Pavement Design software. Based upon the results of laboratory experiments and simulation, it was found that the mechanical performance of WPT asphalt mixture including moisture sensitivity, rutting and fatigue resistance of WPT modified asphalt mixture was comparable to that of SBS asphalt mixture. The life-long service performance of WPT mixture was much superior to that of raw asphalt mixture. The warm mix asphalt additive, FT-wax, allowed the WPT asphalt mixture to be produced at same temperature to mixture with raw asphalt. Meanwhile, the mechanical properties of warm WPT were slightly better than those of hot WPT. Finally, this study proves that recycling waste packing tapes as asphalt modifier is a promising solution with both environmental and engineering merits.

IMPACT OF CONCRETE MATERIAL INPUTS ON PERFORMANCE OF CONTINUOUSLY REINFORCED CONCRETE PAVEMENT

Continuously reinforced concrete pavement (CRCP) is increasingly being used in the United States based on its longer service life with minimal maintenance. CRCP provides excellent performance for heavily loaded traffic volume, if designed and constructed properly. The performance of CRCP is evaluated based on punch-outs and pavement roughness according to the Pavement ME (mechanistic-empirical) Design procedure which is the state-of-the-art pavement design tool. Design of CRCP is dependent on various factors including traffic, climate, material inputs and pavement geometry. This study focuses on evaluating the effects of concrete mechanical and thermal properties and traffic volume on CRCP performance. CRCP design simulations were conducted using Pavement ME Design software version 2.3 to evaluate the effects of material input data on CRCP performance and it was observed that there is significant difference between the performance predictions with time series data in comparison to the default data. The impact of material inputs is more significant on punch-outs distress as compared to the pavement roughness. This necessitates the importance of lab tested material inputs for accurate design of CRCP. The impact of traffic volume on CRCP performance was also evaluated and it was found that with increase in traffic volume, the pavement distresses increases and the performance decreases.

Gradient Boosted Models for Enhancing Fatigue Cracking Prediction in Mechanistic-Empirical Pavement Design Guide

AbstractThis study developed a gradient boosted model (GBM) to enhance the fatigue cracking predictive performance of transfer functions in the mechanistic-empirical pavement design guide (MEPDG). ...

Preliminary Local Calibration of Performance Prediction Models in AASHTOWare Pavement ME Design for Flexible Pavement Rehabilitation in Oregon

AbstractThe Oregon Department of Transportation (ODOT) is in the process of implementing the AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) for new pavement sections. However, the vast ...

Rutting and Fatigue Properties of Cellulose Fiber-Added Stone Mastic Asphalt Concrete Mixtures

This paper investigates dynamic response, rutting resistance, and fatigue behavior of three stone mastic asphalt (SMA) concrete mixtures selected on basis of nominal maximum aggregate size (NMAS): 25 mm, 19 mm, and 12.5 mm using cellulose fiber added as 0.3% of the total weight of aggregate. Superpave gyratory specimens were fabricated and subjected to the dynamic modulus (E∗) and flow tests (flow number and flow time) using an asphalt mixture performance tester. The E∗ test results were employed to develop stress-dependent master curves for each mixture, indicating that the mixture with the NMAS of 25 mm is relatively stiffer than other tested mixtures; this mixture also exhibits excellent strength against rutting failure. In addition, fatigue parameter, which is derived from dynamic response and phase angle, is determined, and results reveal that 12.5 mm NMAS mix has relatively better resistance to fatigue than other selected mixtures. Furthermore, nonlinear regression model specifications were utilized to predict accumulated strains as a function of loading cycles. Also, a flow number model is developed that predicts the rutting behavior of mixtures, and results suggest that model predicted and observed outputs of 25 mm SMA mix are found to be very close. The results of this study help in understanding the performance and behavior of cellulose fiber-added stone mastic asphalt concrete mixtures under varying simulated temperature and stress levels, which can be used in areas where the premature failure of flexible pavements is often observed. The testing protocol employed in this study will also help in evaluating pavement performance using Mechanistic-Empirical Pavement Design Guide.

Probabilistic prediction of asphalt pavement performance

Variability of pavement design parameters has always been a concern to pavement designers and highway agencies. A robust pavement design should take into account the variability of the design inputs and its impact on the reliability of the design. In this study, the variability effect of thickness and stiffness of pavement layers was investigated. The variability of these parameters was described by their mean values, standard deviations and probability distribution functions. Monte Carlo Simulation method was utilised to incorporate variability of the design parameters and to construct the probability distribution function of the outputs. KENLAYER software was used to calculate pavement response at predetermined critical locations; pavement reponse was then used to predict pavement performance regarding permanent deformation, bottom-up and top-down fatigue cracking by using the mechanistic empirical pavement design guide (MEPDG) models. A Matlab code was developed to run that analysis and obtain the probability distribution function of pavement performance indicators over time. It was found that the variability of pavement layer thickness and stiffness has a significant impact on pavement performance. Also, it was found that not only the mean of the predicted performance indicators is increasing over time, but the variance of these indicators is also increasing. This means that pavement condition cannot be described by the mean values of the indicators but by the probability distribution function which can describe pavement condition at any reliability level.