Mechanistic-empirical pavement design guide(MEPDG):a bird's-eye view

Past editions of the American Association of State Highway and Transportation Officials （AASHTO） Guide for Design of Pavement Structures have served well for several decades; nevertheless, many serious limitations exist for their continued use as the nation＇s primary pavement design procedures. Researchers are now incorporating the latest advances in pavement design into the new Mechanistic-Empirical Pavement Design Guide （MEPDG）, developed under the National Cooperative Highway Research Program （NCHRP） 1-37A project and adopted and published by AASHTO. The MEPDG procedure offers several dramatic improvements over the current pavement design guide and presents a new paradigm in the way pavement design is performed. However, MEPDG is substantially more complex than the AASHTO Design Guide by considering the input parameters that influence pavement performance, including traffic, climate, pavement structure and material properties, and applying the principles of engineering mechanics to predict critical pavement responses. It requires significantly more input from the designer. Some of the required data are either not tracked previously or are stored in locations not familiar to designers, and many data sets need to be preprocessed for use in the MEPDG. As a result, tremendous research work has been conducted and still more challenges need to be tackled both in federal and state levels for the full implementation of MEPDG. This paper, for the first time, provides a comprehensive bird＇s eye view for the MEPDG procedure, including the evolvement of the design methodology, an overview of the design philosophy and its components, the research conducted during the development, improvement, and implementation phases, and the challenges remained and future developments directions. It is anticipated that the efforts in this paper aid in enhancing the mechanistic-empirical based pavement design for future continuous improvement to keep up with changes in trucking, materials, construction, design concepts, computers, and so on.

Preliminary <i>k</i>-Values of Unbound Natural Quartzitic Gravels for Mechanistic-Empirical Pavement Design

The generalized constitutive model relating the resilient modulus (MR) of flexible pavement layer materials to stress state, adopted by the Mechanistic-Empirical Pavement Design Guide (MEPDG), contains a set of constants known as k-values (k1, k2, and k3) which are associated with the physical state of the layer materials. In Ghana, natural gravels constitute the predominant and sometimes the sole layer materials for most flexible pavements yet representative k-values of gravel materials, have not been determined to permit full application and implementation of the mechanistic-empirical design concept to pavements involving such materials. In this study, k-values characterising typical natural quartzitic gravels used for road construction in the country were derived by regression techniques from MR values determined using laboratory repeated load triaxial test. Using multiple linear regression technique, correlation relationships were then developed between the k-values and the physical properties of the gravels, namely, percentages of materials passing the 9.5 mm (P9.5) and 2.0 mm (P2.0) sieves, liquid limit (LL), maximum dry density (ρdmax), and optimum moisture content (wopt). The regression analysis returned k1 values which ranged between 441 and 958 with a mean of 516;k2 which varied between 0.0636 and 0.2168 with a mean value of 0.1216;and, k3 values which ranged between 0.1257 and 3.1590 with a mean value of 1.723. Contrary to what is mostly reported in literature, the analysis returned positive k3 values for all but one gravel material, suggesting stress hardening under octahedral shear stress for those materials. While an expanded sample base is required to fully characterize the whole gamut of natural gravels used in pavement construction in the country, this study on limited quartzitic gravel samples has given a good indication of strong linear correlations between the k-values and the index properties of the gravels, to permit estimates of the constants for such gravels be made where capability and opportunity for conducting resilient modulus tests do not exist.However, further work is recommended to fully characterise the exact nature of k3 values for quartzitic gravels in the country.

Resilient modulus prediction of soft low-plasticity Piedmont residual soil using dynamic cone penetrometer

Dynamic cone penetrometer（DCP） has been used for decades to estimate the shear strength and stiffness properties of the subgrade soils. There are several empirical correlations in the literature to predict the resilient modulus values at only a specific stress state from DCP data, corresponding to the predefined thicknesses of pavement layers（a 50 mm asphalt wearing course, a 100 mm asphalt binder course and a200 mm aggregate base course）. In this study, field-measured DCP data were utilized to estimate the resilient modulus of low-plasticity subgrade Piedmont residual soil. Piedmont residual soils are in-place weathered soils from igneous and metamorphic rocks, as opposed to transported or compacted soils.Hence the existing empirical correlations might not be applicable for these soils. An experimental program was conducted incorporating field DCP and laboratory resilient modulus tests on "undisturbed" soil specimens. The DCP tests were carried out at various locations in four test sections to evaluate subgrade stiffness variation laterally and with depth. Laboratory resilient modulus test results were analyzed in the context of the mechanistic-empirical pavement design guide（MEPDG） recommended universal constitutive model. A new approach for predicting the resilient modulus from DCP by estimating MEPDG constitutive model coefficients（k;,k;and k;） was developed through statistical analyses. The new model is capable of not only taking into account the in situ soil condition on the basis of field measurements,but also representing the resilient modulus at any stress state which addresses a limitation with existing empirical DCP models and its applicability for a specific case. Validation of the model is demonstrated by using data that were not used for model development, as well as data reported in the literature.

Evaluation of Dynamic Modulus of HMA Sigmoidal Prediction Models and Optimization by Approach of U.S. Mesh Sieve by AFNOR and LC Mesh Sieve

Pavement design tools are not universal. Indeed, in the sizing of pavements in the USA, the prediction models used in the calculation of the dynamic modulus of HMA are not adapted to the characterization of the mineral skeleton of the HMA mix designed with the French method. This article aims to assess the predictive models of the dynamic modulus used in the mechanistic-empirical design for their use in the design of bituminous pavements, and to develop new predictive models taking into account the sieve series LC and AFNOR standards. A total of six types of mixtures were subjected to the determination of complex modulus testing by direct tensile-compression on cylindrical specimens (26-700 LC) over a temperature range (5) and frequency (5) data. Dynamic modulus prediction models |E*| are studied Witczak model 1999 and model Witczak 2006. These models do not take into account the AFNOR or LC mesh sieve, an approach was made in relation to the US mesh sieve to replace ρ200 (0.075 mm), ρ4 (4.76 mm), ρ38 (9.5 mm) and ρ34 (19 mm) respectively by the AFNOR mesh P0.08 (0.08 mm), R5 (5 mm), R10 (10 mm) and R14 (14 mm). The result is the production of two models whose are evaluated by correlation with the values |E*| of modulus measured in the laboratory is satisfactory (R2 = 0.83 respectively R2 = 0.71 and p-value = 0.00). The optimization of these approximate models gave new models with the same frame as the original models and a better correlation with the data observed in the laboratory (respectively R2 = 0. 95 and R2 = 0.91 p-value = 0.00).

Multi-gene genetic programming extension of AASHTO M-E for design oflow-volume concrete pavements

The American Association of State Highway and Transportation Officials Mechanistic-Empirical Pavement DesignGuide (AASHTO M-E) offers an opportunity to design more economical and sustainable high-volume rigid pavementscompared to conventional design guidelines. It is achieved through optimizing pavement structural andthickness design under specified climate and traffic conditions using advanced M-E principles, thereby minimizingeconomic costs and environmental impact. However, the implementation of AASHTO M-E design for low-volumeconcrete pavements using AASHTOWare Pavement ME Design (Pavement ME) software is often overly conservative.This is because Pavement ME specifies the minimum design thickness of concrete slab as 152.4 mm (6 in.). Thispaper introduces a novel extension of the AASHTO M-E framework for the design of low-volume joint plain concretepavements (JPCPs) without modification of Pavement ME. It utilizes multi-gene genetic programming (MGGP)-based computational models to obtain rapid solutions for JPCP damage accumulation and long-term performanceanalyses. The developed MGGP models simulate the fatigue damage and differential energy accumulations. Thispermits the prediction of transverse cracking and joint faulting for a wide range of design input parameters and axlespectrum. The developed MGGP-based models match Pavement ME-predicted cracking and faulting for rigidpavements with conventional concrete slab thicknesses and enable rational extrapolation of performance predictionfor thinner JPCPs. This paper demonstrates how the developed computational model enables sustainable lowvolumepavement design using optimized ME solutions for Pittsburgh, PA, conditions.

A critical review of the fatigue life prediction of asphalt mixtures and pavements

New pavement construction techniques and the increased use of recycled materials have led to unexpected and premature pavement failure in recent years.The pavement’s exposure to daily and seasonal extreme temperature and repeated vehicular loads accumulate damage.Pavement cracking occurs once the cumulative damage surpasses the material’s cracking threshold.Fatigue crack is the most common pavement cracking type.Over the past four decades,researchers have carried out numerous experiments and analyses to understand pavement cracking.This paper aims to provide an overview of fatigue cracking and discuss various fatigue test methods for characterizing asphalt concrete mixtures.The article also discusses the most common phenomenological and mechanistic models for predicting the fatigue life of asphalt concrete pavements based on different fatigue test results.The paper details the implementation of the commonly used numerical models found in numerical simulation software and their prediction ability for the fatigue life of a pavement structure.Two major flaws in current evaluation methods are the sensitivity of experimental results and the lack of reliability of some predictive models.Multiscale asphalt material characterization is the ongoing practice for determining the most appropriate performance evaluation tool.However,proceeding with future research objectives is unrealistic until the accuracy of the tests and reliability of the predictions can be verified against actual field results.This critical review of the fatigue life predictions of asphalt mixtures and pavements should help to refine or redefine the right course of action for future research.

Sensitivity analysis of longitudinal cracking on asphalt pavement using MEPDG in permafrost region

Longitudinal cracking is one of the most important distresses of asphalt pavement in permafrost regions. The sensitivity analysis of design parameters for asphalt pavement can be used to study the influence of every parameter on longitudinal cracking, which can help optimizing the design of the pavement structure. In this study, 20 test sections of Qinghai-Tibet Highway were selected to conduct the sensitivity analysis of longi- tudinal cracking on material parameter based on Mechanistic-Empirical Pavement Design Guide （MEPDG） and single factorial sensitivity analysis method. Some computer aided engineering （CAE） simulation techniques, such as the Latin hypercube sampling （LHS） technique and the multiple regression analysis are used as auxiliary means. Finally, the sensitivity spectrum of material parameter on longitudinal cracking was established. The result shows the multiple regression analysis can be used to determine the remarkable influence factor more efficiently and to process the qualitative analysis when applying the MEPDG software in sensitivity analysis of longitudinal cracking in permafrost regions. The effect weights of the three parameters on longitudinal cracking in descending order are air void, effective binder content and PG grade. The influence of air void on top layer is bigger than that on middle layer and bottom layer. The influence of effective asphalt content on top layer is bigger than that on middle layer and bottom layer, and the influence of bottom layer is slightly bigger than middle layer. The accumulated value of longitudinal cracking on middle layer and bottom layer in the design life would begin to increase when the design temperature of PG grade increased.