Mechanistic-Empirical Pavement Design Guide Software Research Articles

Structural contribution of open-graded friction course mixes in mechanistic–empirical pavement design

Open-graded friction course (OGFC) is often believed to have no contribution to the structural capacity of flexible pavement. In this study, five types of OGFC mixtures were prepared and tested for rutting potentials, and three of them were tested for dynamic moduli, which were further used to analyse pavement's response and performance based on the procedures in the mechanistic–empirical pavement design guide (MEPDG). It was found that the tensile strain at the bottom of asphalt concrete layers and the compressive strain at the top of sub-grade layer are sensitive to the availability of OGFC, regardless of mixture type. The fatigue and permanent deformation damages of a flexible pavement can be effectively reduced after adding the OGFC layer, due to the alteration of loading frequency, thermal gradient and modulus ratio. Trial designs using MEPDG software in two different climates verify the above observations.

Validating MEPDG with Tennessee Pavement Performance Data

To implement the Mechanistic-Empirical Pavement Design Guide (MEPDG) developed by AASHTO for pavement construction and rehabilitation, it is necessary to evaluate its performance prediction models using actual pavement performance data, material properties, traffic information, and environmental factors. This paper validated the MEPDG models using the performance of typical pavements in the state of Tennessee from pavement management system (PMS). With traffic and pavement structural information collected from PMS, the performance of selected highway pavement sections was analyzed with MEPDG Version 1.100 software. The predicted present serviceability index (PSI) and rutting were compared with the actual measurement values. An initial value for the international roughness index (IRI) was suggested for Tennessee highways through investigation into the actual roughness data. The dynamic moduli of asphalt mixtures for input level 1 were obtained from laboratory testing. Those for input level 3 were estimated with the Witczak model. The results show that rutting of asphalt concrete (AC) pavements was more accurately predicted at input level 1, whereas it was overpredicted at input level 3. Traffic level was found to be an important factor affecting predicted pavement roughness. It was also found that MEPDG software was relatively conservative for highway pavements with low traffic level. However, MEPDG with nationally averaged default parameters was not sensitive enough to differentiate various climates, traffic, and materials in Tennessee for the prediction of PSI.

Mechanistic-Based Approach to Evaluate Rutting Susceptibility of Hot-Mix Asphalt Mixtures by Use of Dynamic Triaxial Testing

Designing appropriate asphalt mixture type and properties is an important task that pavement engineers perform routinely. For many years, this key decision has been made by relying on empirical procedures that might not be representative of the specific project condition. Therefore, there is a need to develop an advanced yet simplified approach to assessing, on the basis of closely simulated field conditions, the rutting susceptibility of hot-mix asphalt (HMA) mixtures under a given set of traffic loads and environmental conditions. This paper presents a new mechanistic-based approach that evaluates asphalt mixtures by using the repeated load triaxial (RLT) test at field-representative testing conditions to determine the critical temperature of the HMA. An HMA mixture was considered appropriate for a specific project location when the determined critical temperature was greater than the effective asphalt pavement temperature for rutting determined by using the Mechanistic–Empirical Pavement Design Guide software. Predictive equations that accounted for the actual project characteristics, such as climate conditions, material characteristics, operational speed, and traffic loading, were developed to estimate the effective asphalt pavement temperature. Nine HMA mixtures were characterized and analyzed for rutting behavior. The critical temperature for each HMA mixture was obtained with RLT results and actual field performance. Flow number criteria as a function of traffic level were also developed. The proposed approach was validated by using three additional mixtures from Nevada and two mixtures from the WesTrack accelerated test facility. Good agreement between laboratory results and field performance was achieved and supports the appropriateness of the proposed approach.

Determination of axle load spectra based on percentage of overloaded trucks for mechanistic-empirical pavement design

The mechanistic-empirical pavement design guide (MEPDG) developed under National Cooperative Highway Research Program Project 1-37A requires the use of axle load spectra or load distribution factors (LDFs) for pavement thickness designs. The MEPDG allows for various levels of LDF inputs, varying from site-specific (level 1) to regional average (level 2) and national average (level 3). There exists a concern that the MEPDG level 2 and level 3 inputs do not take any site-specific information into consideration and thus may result in erroneous thickness design. This study proposed a new approach to determine the axle LDF and number of axles per truck (NAPT) for level 2 and level 3 inputs. The proposed approach requires that the design guide provide default LDFs and NAPTs for both normally loaded and overloaded trucks for various axle types and vehicle classes. Thus, design engineers can estimate LDFs and NAPTs for a particular project site based on the percentages of overloaded trucks of that site which are readily available from historical traffic data. The effectiveness of the proposed approach was evaluated using weight-in-motion data collected from 26 sites in China. The LDFs and NAPTs obtained from various approaches were used to predict truck factors using the American Association of State Highway and Transportation Officials equation and to predict pavement distresses using the MEPDG software. The prediction errors from the proposed approach are substantially reduced when compared to those obtained using the MEPDG approach, indicating the proposed approach to be a more accurate way for traffic loading characterisation. The proposed level 2 inputs can further reduce the prediction errors when compared to the proposed level 3 inputs. Among the three types of pavement distresses analysed using the MEPDG software, namely rutting, bottom-up and top-down fatigue cracking, rutting is the least sensitive to the variations in axle LDF and NAPT, while top-down cracking is the most sensitive to the variations.

Study of MEPDG Sensitivity Using Nonparametric Regression Procedures

AbstractBecause the new Mechanistic-Empirical Pavement Design Guide (MEPDG) includes numerous inputs, a sensitivity analysis using the Monte Carlo approach is not practical because it requires thousands of MEPDG runs. Instead, nonparametric regression procedures can be very useful to perform MEPDG sensitivity analysis. In this study, nonparametric regression procedures such as multivariate adaptive regression splines and gradient boosting machine are employed to identify inputs that contribute significantly to the outputs. Thirty inputs are used to randomly generate 750 input combinations by using Latin hypercube sampling. Using four-layer pavement geometry [two asphalt concrete (AC), base, and subgrade layers], simulations are run in MEPDG software to produce a time series of predicted distresses such as roughness, rutting, and cracking. Sensitivity analysis resulted in three groups of inputs to which the output is (1) highly sensitive, (2) moderately sensitive, and (3) minimally sensitive. Results show ...

Prediction of hot mix asphalt dynamic modulus using dimensional analysis

This study uses dimensional analysis to develop a consistent predictive model for the widely used dynamic modulus of hot mix asphalt in pavement design. The key variables that capture the effects of aggregate binder on the dynamic modulus of these materials were identified first. The Buckingham PI theorem was used to formulate the functional relationship among a set of non-dimensional variables from the original set. The functional form was defined based on 17 mixes commonly used in the state of Idaho in the USA. Subsequently the predictive model performance was verified on different field mixes in the literature. The results show that the proposed model, when utilised as level 1 inputs into the American Association of State Highway and Transportation Officials Mechanistic–Empirical Pavement Design Guide software, predicted pavement rutting values that were closer to measured values than those evaluated by existing prediction models.

Performance and Cost-Effectiveness of Sustainable Technologies in Flexible Pavements Using the Mechanistic-Empirical Pavement Design Guide

Past studies evaluated the mechanistic properties, economic benefits, and ecological impacts of sustainable asphalt mixtures. However, questions remain concerning the effects of these technologies on structural pavement design and performance. The objectives of this study were to evaluate the effects of selected sustainable technologies [warm-mix asphalt (WMA), reclaimed asphalt pavement (RAP), crumb rubber modifier (CRM), and sulfur additive] on the performance predicted by the Mechanistic-Empirical Pavement Design Guide (MEPDG) software and to assess the life-cycle costs (LCC) of pavement structures constructed with these sustainable alternatives. This study also determined if the MEPDG software is sensitive to variation in the mechanistic properties of asphalt mixtures containing selected sustainable technologies. Three typical pavement structures were analyzed at three traffic levels (low, medium, and high). On the basis of the results of this analysis, it was determined that the performance predicted by the MEPDG software was improved because of the use of sustainable mixtures. In addition, results indicated that sustainable technologies have the potential to reduce production and LCCs compared with conventional asphalt mixtures.

Streamlining Use of Mechanistic–Empirical Pavement Design Guide

The NCHRP Mechanistic–Empirical Pavement Design Guide (MEPDG) is a powerful tool for the design and analysis of highway pavements. Currently, the designer uses an iterative process to select design parameters and predict performance. If performance is unacceptable, the designer must change the design parameters until acceptable performance is achieved. A procedure outlined here used multiple adaptive regression splines (MARS) to develop predictive models obtained from a series of actual pavement design solutions from MEPDG software. Two model structures were developed: a series of models to predict individual pavement distress (rutting, fatigue cracking, and roughness) and a forward solution to predict pavement thickness from a desired level of distress. This model can be used to determine a starting thickness, which then can be used with the MEPDG software to obtain a refined design, potentially with fewer iterations to define an acceptable design thickness. These thickness prediction models can be developed for any subset of desired MEPDG solutions, such as typical designs within a state. The new DARWin-ME software can facilitate the development of these subsets through its sensitivity analysis procedure, which would allow the designer to develop a subset of solutions across a typical range of input values. Results could then be modeled with the MARS process to produce an efficient design solution for pavement thickness along with a quick performance prediction for specific pavement thickness. This procedure can significantly reduce the MEPDG iterations necessary to develop a viable design, to as few as two to three on either side of the predicted MARS model thickness. These results could be merged with a smart decision tree structure to execute the MEPDG procedure efficiently.

Evaluation of the Mechanistic–Empirical Pavement Design Guide model for permanent deformations in asphalt concrete

The model for permanent deformation in asphalt concrete (AC) layers used in the Mechanistic–Empirical Pavement Design Guide (MEPDG) was evaluated. Two instrumented flexible pavements were subjected to heavy vehicle simulator testing at three constant temperatures. Permanent deformation modelling was carried out using the MEPDG software v1.003 at the highest accuracy level. The nationally calibrated model resulted in underprediction by 35–45%. Model results were successfully calibrated to fit observation using field calibration factors that increased temperature susceptibility by 45–50% and decreased the dependency of the number of loadings by 30–40%. The field calibration factors should be confirmed by studying existing pavements before being employed. The model did not assess the permanent deformation contribution of each AC layer correctly. Therefore, the model should be refined with further trench studies using in-service pavements.

Toward Implementation of the Mechanistic–Empirical Pavement Design Guide in Latin America

The Mechanistic–Empirical Pavement Design Guide (MEPDG) and MEPDG software are tools that provide more rational pavement designs than previous guides. The application of the mechanistic–empirical method, however, requires careful consideration of the input data and proper calibration to local conditions. Since 2004, several efforts have been made in Chile to study implementation of MEPDG in that country. The work has included obtaining local input data (axle load distributions, weather, and material characteristics), calibration efforts for distress prediction, and comparison of pavement designs by using MEPDG and the local design method. Axle load distributions were obtained for three important highways in the most populated area in the country. Statistical analysis was performed to compare the default load spectra from MEPDG with the local spectra. Significant differences were observed. Weather information was obtained for six cities that represent broadly the different weather conditions in the country. Master curves were developed for Level 2 design on the basis of the aggregate and binder properties of the local materials. Preliminary local calibration factors were obtained for transverse cracking and faulting of jointed plain concrete pavement. These local data were employed to develop pavement designs with the MEPDG software; these designs were then compared with designs developed with the current Chilean design methodology, which is based on AASHTO 93 and 98 methods. The work presented shows that the implementation of the MEPDG is possible for countries of Latin America. Some recommendations are provided for future versions of the MEPDG to make use of the software in the Southern Hemisphere easier and friendlier.

Mechanistic–Empirical Pavement Design Guide–Based Pavement Design Catalog for Low-Volume Roads in Arkansas

Historically, low-volume roads in Arkansas were typically constructed by use of a standard section, that is, a double surface treatment over a specified thickness of granular base. Subsequent analysis indicated that these sections were structurally inadequate in many cases. In recent years, the Arkansas State Highway and Transportation Department has invested significant research dollars to implement the Mechanistic–Empirical Pavement Design Guide (MEPDG), which is widely believed to be a quantitative leap over the 1993 AASHTO design guide. However, the MEPDG research efforts mostly target high-volume roads. In this paper, a design catalog for low-volume roads (LVRs) in Arkansas was developed with MEPDG software, Version 1.10. The catalog offers a variety of feasible design alternatives for a comprehensive combination of site conditions. The factors considered include the five geographical regions in Arkansas and the typical Arkansas load spectrum for LVRs with three traffic levels, three subgrade types, and six potential aggregate types available in Arkansas that can be used as granular base and surface layer aggregates. All the MEPDG design inputs needed for the development of the design catalog are generated on the basis of the variety of previous MEPDG implementation research conducted in the state of Arkansas. It is anticipated that the design catalog will serve as a simplified and rational design process for the LVRs in Arkansas.

Calibration of Distress Models from the Mechanistic–Empirical Pavement Design Guide for Rigid Pavement Design in Argentina

This paper presents the main results of a calibration of distress models from the Mechanistic–Empirical Pavement Design Guide (MEPDG) to local conditions in Argentina to be used in rigid pavement structural design. Test sections with rigid pavements were selected to cover a wide range of climatic conditions in the central region of the country. Local road agencies provided information about pavement structure, traffic volume, and load spectra. Field distress data and international roughness index (IRI) values were collected and processed with MEPDG software; calibration factors were determined for the different distress models of rigid pavements. The accuracy of distress prediction was significantly improved if calibration factors that considered additional influence of climatic conditions, soil and base type, slab length, and pavement age were incorporated into the transverse joint-faulting and transverse-cracking models. Through the use of calibrated factors instead of default values provided in MEPDG models, the errors in distress predictions were reduced by more than one-half in all cases. Construction procedures seemed to influence the IRI roughness prediction. Better calibration results were obtained if different after-construction IRI values were considered for pavements constructed before and after the 1990s to reflect the difference between older and newer constructive techniques.

Use of Pavement Management Information System for Verification of Mechanistic–Empirical Pavement Design Guide Performance Predictions

The performance models used in the Mechanistic–Empirical Pavement Design Guide (MEPDG) are nationally calibrated with design inputs and performance data obtained primarily from the national Long-Term Pavement Performance database. It is necessary to verify and calibrate MEPDG performance models for local highway agencies’ implementation by taking into account local materials, traffic information, and environmental conditions. This paper discusses the existing pavement management information system (PMIS) with respect to the MEPDG and the accuracy of the nationally calibrated MEPDG prediction models for Iowa highway conditions. All the available PMIS data for Interstate and primary road systems in Iowa were retrieved from the Iowa Department of Transportation (DOT) PMIS. The retrieved databases were then compared and evaluated with respect to the input requirements and outputs for Version 1.0 of the MEPDG software. Using Iowa DOT's comprehensive PMIS database, researchers selected 16 types of pavement sections across Iowa (not used for national calibration in the NCHRP 1-37A study). A database of MEPDG inputs and the actual pavement performance measures for the selected pavement sites were prepared for verification. The accuracy of the MEPDG performance models for Iowa conditions was statistically evaluated. The verification testing showed promising results in terms of MEPDG's performance prediction accuracy for Iowa conditions. Recalibrating the MEPDG performance models for Iowa conditions is recommended to improve the accuracy of pavement performance predictions.

Verification of Virtual Climatic Data in MEPDG Using the LTPP Database

The Enhanced Integrated Climatic Model (EICM) integrated in the Mechanistic-Empirical Pavement Design Guide (MEPDG) allows users to select adjacent weather stations to generate a virtual weather station (VWS), whose data are further used to predict environmental impact on pavement performance. It is essential that the derived virtual data be accurate and representative of the actual climatic conditions. To evaluate the accuracy of the MEPDG generated VWS data, climatic data from corresponding automated weather stations (AWS) in the long-term pavement performance (LTPP) database are obtained to conduct the comparison analysis. It is observed that most VWS climatic data estimate the actual weather data reasonably well. However, in some cases, significant differences are observed. The potential factors resulting in the discrepancies are investigated. MEPDG analyses are conducted to quantify the climate data differences on predicted pavement performance. Finally, the paper presents recommendations when using the MEPDG software to generate VWS so as to help establish more accurate key climatic inputs.

Evaluation of the Mechanistic-Empirical Pavement Design Guide for implementation in Iowa

With the release of the new Mechanistic-Empirical Pavement Design Guide (MEPDG) in the United States, there is a big shift in pavement analysis and design and many state highway agencies are undertaking initiatives to implement the MEPDG. The Iowa Department of Transportation (IDOT) is one such highway agency in the United States interested in implementing the MEPDG. In order to effectively and efficiently transition to the MEPDG from the current empirical approach and accelerate its adoption, the IDOT needs a detailed implementation and training strategy. In support of the MEPDG implementation initiatives, sensitivity studies were conducted using the MEPDG software to identify design inputs pertaining to flexible pavements that are of particular sensitivity in Iowa. Based on a study of the MEPDG design components, results of sensitivity analyses, and past experience, this paper, which is the second of the 2 companion papers, presents key initiatives for implementing the MEPDG in Iowa. The need for implementing the MEPDG at IDOT and the results of rigid pavement input parameter sensitivity analysis are discussed in detail in the first paper.

Sensitivity Analysis of Rigid Pavement Systems Using the Mechanistic-Empirical Design Guide Software

Initiatives are underway to implement the new mechanistic-empirical pavement design guide (MEPDG) in Iowa. This paper focuses on the sensitivity study of jointed plain concrete pavements (JPCP) and continuously reinforced concrete pavements (CRCP) in Iowa using the MEPDG software. In this comprehensive study, the effect of MEPDG input parameters on the rigid pavement performance is evaluated using the different versions of the MEPDG software (0.7, 0.9, and 1.0) available to date. Representative JPCP and CRCP sections in Iowa were selected for analysis. Based on the sensitivity plots obtained from the MEPDG runs, the design input parameters were categorized as being most sensitive, moderately sensitive, or least sensitive in terms of their relative effect on distresses. In this study, the curl/warp effective temperature difference, the PCC coefficient of thermal expansion, and PCC thermal conductivity had the greatest impact on the JPCP and CRCP distresses. Compared to the original version of MEPDG software (Version 0.7), the updated versions (Versions 0.9 and 1.0) are more sensitive to inputs, which shows the evolution of engineering reasonableness.

Comparison of Georgia Department of Transportation Design Procedure with Mechanistic–Empirical Pavement Design

This research had several objectives: measure the dynamic modulus of commonly used hot-mix asphalt mix types, two aggregate base courses, and two soils that represent high and low values; compare the results of using measured moduli with Mechanistic–Empirical Pavement Design Guide (MEPDG) Level 3 default moduli for the subgrade and aggregate base material; and compare design results using the AASHTO 1972 Interim Guide for Pavement Design currently being used by the Georgia Department of Transportation (GDOT) with the MEPDG results. The research showed that the MEPDG Level 3 default values for resilient modulus of both soil and aggregate materials are significantly higher than the actual values determined from laboratory test results. Use of actual material properties and load spectra resulted in significantly greater structures being recommended than when Level 3 default values were used for the MEPDG design program. On the basis of these results, GDOT is cautioned against using the default values built into the MEPDG software and should conduct a thorough calibration study using Georgia materials before implementing the MEPDG design procedure.

Calibration of Flexible Pavement in Mechanistic–Empirical Pavement Design Guide for Washington State

The Mechanistic–Empirical Pavement Design Guide (MEPDG) is proposed as an advanced pavement design tool that integrates up-to-date pavement practices. Since MEPDG was released in 2004, the Washington State Department of Transportation (WSDOT) has continuously worked on calibrating and evaluating the program with regard to implementation for state and local agencies. This paper presents WSDOT's latest efforts on calibrating the flexible pavement portion of MEPDG with data obtained from the Washington State Pavement Management System. It describes preparation of required input data and provides detailed descriptions of input values, as they may apply to states with similar conditions. The calibration process is described, and results and potential implications are discussed. Major observations and general issues encountered in the calibration process are emphasized. An implementation plan is being prepared that may replace the 1993 AASHTO Design Guide with MEPDG in Washington State. This study provides valuable conclusions for national applications: ( a) the flexible pavement distress models were calibrated successfully, ( b) WSDOT flexible pavements require local calibration different from the defaults, and ( c) a software bug does not allow calibration of the roughness model. By making a few improvements and resolving software bugs, MEPDG software can be used as an advanced tool to design flexible pavements and predict future pavement performance.

Analysis of Load Pulse Durations for Marquette Interchange Instrumentation Project

The loading frequency is an important input for determining the stiffness of asphalt materials on the basis of their dynamic modulus data. This stiffness relationship is used in the Mechanistic–Empirical Pavement Design Guide (MEPDG) to calculate a pavement's structural response to loading. This response—typically maximum horizontal strain and vertical pressure—is then used to estimate the number of load repetitions to failure. The Marquette Interchange Perpetual Pavement Instrumentation Project is a research effort carried out by the Transportation Research Center at Marquette University. The project implemented different pavement sensors to provide researchers with a complete set of pavement response data for calibration of local design variables and to provide insight into the structural behavior of a perpetual pavement opened to live urban freeway traffic. An analysis of the strain and pressure data recorded from the project was conducted to measure the length of strain and pressure pulse durations. The load pulse durations for each axle were then analyzed and compared with models contained in the MEPDG software. The analysis showed that the models may broadly fit actual load durations, but the surrounding assumptions may not be adequate for all axle and load configurations.

Estimation of Truck Traffic Inputs for Mechanistic–Empirical Pavement Design in California

This study developed default truck traffic inputs for mechanistic–empirical pavement design procedures for the California highway system based on California weigh-in-motion (WIM) data. Both cluster analysis and regression analysis were applied to develop the default axle load spectra. Regression analysis produced unsatisfactory results so it was not used. On the basis of cluster analysis of axle load spectra, the WIM sites were divided into several groups, and default truck traffic inputs were estimated for each group. A decision tree was developed to help designers select the appropriate default factors based on easily available information: geographic location and traffic volume and composition. These data can be obtained from the California Department of Transportation annual report of annual average daily truck traffic. Traffic inputs were developed for both the Caltrans Mechanistic–Empirical Pavement Design and NCHRP Mechanistic–Empirical Pavement Design Guide software.