A Mechanistic–Empirical Model for Top–Down Cracking of Asphalt Pavements Layers (2018)

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1 CHAPTER 1. INTRODUCTION Introduction Recent studies have determined that some load-related fatigue cracks in asphalt pavement layers can be initiated at the pavement surface and propagate downward through the asphalt layer. However, this form of distress cannot entirely be explained by fatigue mechanisms used to explain cracking that initiates at the bottom of the pavement. These studies have also suggested hypotheses regarding top-down cracking mechanisms (e.g., bending-induced surface tension and shear-induced near-surface tension) and developed preliminary models for predicting crack initiation and propagation. For example, the AASHTO Mechanistic-Empirical Pavement Design Guide Manual of Practice (MEPDG) developed under NCHRP Project 01-37A provides a tentative methodology for the analysis and performance prediction of such cracking. Also, recent work completed under NCHRP Project 01-42A developed a viscoelastic continuum damage- based crack initiation model and an asphalt layer fracture mechanics-based crack propagation model. However, additional research is needed to address the issues associated with top-down cracking and to develop a calibrated, validated mechanistic-empirical model for incorporation into the MEPDG procedures. Such a model will allow a more rational analysis and design of asphalt pavements and overlays. Objective The objective of this research project is to develop a calibrated mechanistic-empirical (ME) model for predicting the load-related top-down cracking in the asphalt layer of flexible pavements, and associated computational software for incorporation into the AASHTOWare Pavement ME Design software. Research Scope and Approach The project is required the development and synthesis of eight components: (a) laboratory testing of asphalt field cores for complex modulus gradient and master curve; (b) kinetics-based modeling of long-term field aging in asphalt pavements; (c) finite element computations of the J- integral at the crack tip; (d) use of the finite element program to develop full factorial sets of pavement data to construct Artificial Neural Network (ANN) models for the J-integral at the crack tip; (e) prediction of top-down cracking due to thermal loading based on the J-integral under thermal stresses; (f) develop a top-down crack initiation model and a crack growth model under traffic loading and environmental effect; (g) generation of a cumulative damage model to predict top-down cracking propagation; and (h) development and calibration of top-down cracking prediction model. Major deliverables of this project also include computer subroutines written for incorporation into the Pavement ME Design software to predict top-down cracking in asphalt pavement layers. The programs are supported by other major deliverables, including the test and analysis methods that determine the material properties, fracture properties, and aging properties for top-down cracking in asphalt pavement layers. These are the inputs that the Pavement ME

2 Design software needs in order to accurately predict the appearance and growth of top-down cracking. The catalog of measured and collected data in electronic form is another major deliverable of this project. Summaries of these data are found in Appendices F and G. All of these properties are inputs for the finite element analysis of the J-integral for top-down cracking. Multiple runs with the finite element program over a wide range of pavement variables produce the data for constructing Artificial Neural Network (ANN) models of the J-integral at the tip of the crack, which drives the crack to propagate downward from the surface. The relationship between the existing model in the Pavement ME Design software and the new model developed in this project, called the Mechanistic-Empirical Top-Down Cracking Model, is illustrated in Figure 1.1. Figure 1.1. Compatibility of Proposed Program with AASHTOWare Pavement ME Design Organization of the Report This report is organized into six chapters:  The first chapter presents the introduction and research approach used in this research project. Traffic Material Properties Climate EICM Pavement Structure Pavement Response (σ, ε) Model: Multi-layer elastic system Pavement Distress Models Pavement Performance Predictions INPUT OUTPUT MODELS Pavement Response Model J-Integral Crack Depth, Crack Width Artificial Neural Network Pavement Distress Models Transverse, Longitudinal Stress Vertical Shear, Thermal Stress Pavement Performance Predictions Top-Down Cracking Crack Depth Extent and Severity AASHTOWare Model Top-Down Cracking Model Traffic Tire contact Pressure Material Properties Climate Temperature Model Pavement Structure

3  The second chapter presents a synthesis of current knowledge of characterizing and modeling of top-down cracking in asphalt pavements.  The third chapter presents the research plan of this project.  The fourth chapter presents the major findings. These include the approaches to determine the complex modulus gradient of field-aged asphalt mixtures. The results of the complex modulus gradient are further converted to the master curves using the time-temperature-aging-depth shift functions developed in this project. The methods to obtain the field aging characteristics of asphalt layers are provided based on the modulus gradient data and field deflection data. The kinetic aging parameters such as the aging activation energy represent the aging speed of asphalt mixtures. After obtaining material and aging properties, the pseudo J- integral based Paris’ law is the method used in this project to mechanistically predict crack initiation and propagation for top-down cracking. Two types of inputs for the pseudo J-integral based Paris’ law are provided to facilitate the computation of the design program that is developed for top-down cracking. One type of input is the J-integral, which is computed with Artificial Neural Network models using the combination of different materials, pavement structures, crack size, etc. The development of the ANN models for the J-integral is the result of extensive finite element analyses. The other type of input is the fracture parameters A’ and n’, which are calculated by the prediction model using the performance-based properties and which is explained in Chapter 4. A computer program is finally developed to incorporate all of the models to predict top-down cracking under both traffic and thermal loading.  The fifth chapter presents interpretation, appraisal, and application of the findings discussed in the fourth chapter. It explains the process to develop a computer program to design and calibrate top-down cracking as a subprogram of the AASHTOW are Pavement ME Design.  The sixth chapter presents conclusions and suggested further research. The main body of the report is written to give an overview of the approach and results of this project. More detailed discussions of the topics in the report are contained in Appendices A through O.