National Academies Press: OpenBook

Models for Predicting Reflection Cracking of Hot-Mix Asphalt Overlays (2010)

Chapter: Chapter 1 - Introduction and Research Approach

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Suggested Citation:"Chapter 1 - Introduction and Research Approach." National Academies of Sciences, Engineering, and Medicine. 2010. Models for Predicting Reflection Cracking of Hot-Mix Asphalt Overlays. Washington, DC: The National Academies Press. doi: 10.17226/14410.
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Page 1
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Suggested Citation:"Chapter 1 - Introduction and Research Approach." National Academies of Sciences, Engineering, and Medicine. 2010. Models for Predicting Reflection Cracking of Hot-Mix Asphalt Overlays. Washington, DC: The National Academies Press. doi: 10.17226/14410.
×
Page 2
Page 3
Suggested Citation:"Chapter 1 - Introduction and Research Approach." National Academies of Sciences, Engineering, and Medicine. 2010. Models for Predicting Reflection Cracking of Hot-Mix Asphalt Overlays. Washington, DC: The National Academies Press. doi: 10.17226/14410.
×
Page 3
Page 4
Suggested Citation:"Chapter 1 - Introduction and Research Approach." National Academies of Sciences, Engineering, and Medicine. 2010. Models for Predicting Reflection Cracking of Hot-Mix Asphalt Overlays. Washington, DC: The National Academies Press. doi: 10.17226/14410.
×
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1Introduction Reflection cracking is one of the primary forms of distress in hot-mix asphalt (HMA) overlays of flexible and rigid pave- ments. In addition to affecting ride quality, the penetration of water and debris into these cracks accelerates the deteriora- tion of the overlay and the underlying pavement, thus reduc- ing service life. This project developed mechanistic-based models for use in both analysis and design of HMA overlays. The product of this research will help to account for the effects of reflection cracking on performance, improving the analysis and design of HMA overlays of flexible and rigid pavements. Objective The objective of this study was to identify and develop (a) mechanistic-based models for predicting reflection crack- ing in HMA overlays of flexible and rigid pavements and (b) associated computational software for use in mechanistic- empirical procedures for overlay design and analysis. This chapter summarizes the approach that has been used to accomplish these objectives. The research plan was developed with the expectation that the reflection cracking models and associated software will ultimately be used for routine asphalt overlay thickness design and for reflection cracking perfor- mance analysis of asphalt overlay structures. The plan was also guided by the realization that reflection cracking models and associated input must be compatible with the Mechanistic- Empirical Pavement Design Guide (MEPDG) (1), since reflec- tion cracking is only part of the strategic objective of designing reliably performing asphalt overlay pavements. The body of this report describes the approach that was used, the major findings, the interpretation, appraisal and applications of the results of this study, and, finally, the conclusions and suggested further research that would be beneficial to the objectives of this research. Scope Because overlays are expected to perform differently in dif- ferent climatic zones, the Long-Term Pavement Performance (LTPP) database for the four climatic zones (Wet-Freeze, Wet- No Freeze, Dry-Freeze, and Dry-No Freeze) will be reviewed carefully to determine if there are a sufficient number of over- lay test sections of a given structural type to warrant develop- ing a set of model coefficients for that type of overlay. As a rule of thumb, a minimum of 20 test sections, all of which have begun to experience reflection cracking, are needed to develop a reliable set of calibration coefficients. The relationship between this reflection cracking model and the MEPDG software is that of a subprogram which has many of the same inputs and the same format for input screens and output. Figure 1 illustrates how this model is compatible with the MEPDG. Organization of the Report This report is organized into four chapters. The first chap- ter presents the introduction and research approach used in the research project. The second chapter presents the major findings. These include the definition of reflection cracking; a brief review of the available reflection cracking models; criteria for selection of the best presently available model; and a description of the various categories of data and algo- rithms that were used in assembling the model developed in this project. The data categories include pavement struc- ture, traffic, weather, observed distress, and materials prop- erties. The algorithm categories include methods to predict temperatures; material properties as they vary with temper- ature and loading rate; thermal stress; traffic stresses and the growth of cracks up from the cracks or joints in the old overlaid pavement. Finally, the second chapter describes how the model predictions are calibrated to the observed field data. C H A P T E R 1 Introduction and Research Approach

2This project has produced two programs: the Design Pro- gram and a Calibration Program. The Design Program is writ- ten as a subprogram to the existing MEPDG software but is capable of being run separately. The Calibration Program is set up to allow the user to generate a new set of calibration coefficients for any other combination of pavement structure- overlay-climatic zone of special interest to that user. A nar- rated instructional video has been provided for each program to take the user through the steps of entering the data, running each program, and displaying the output. An interface has been provided so that the calibration coefficients that the user may develop with the Calibration Program can be inserted into the Design Program. The Users’ Guides to the Design and Calibration Programs are in Appendices O and P, respectively. The third chapter presents interpretations, appraisals, and applications of the model that was developed and calibrated. This chapter illustrates how well the calibrated predictions of the S-shaped accumulating distress curves fit the observed dis- tress patterns. It also discusses the level of detail and amount of input data needed for the user of the Calibration Program to develop a new set of calibration coefficients. The fourth chapter presents conclusions and suggested fur- ther research. The main body of this report is written to give an accurate overview of the approach and results of this project. Much more detailed discussions of the subjects in this report are contained in Appendices A through T. These appendices are not published herein but they are available on the NCHRP Report 669 summary web page at http://www.trb.org/Main/ Blurbs/163988.aspx. Research Approach A single model that uses fracture mechanics as its basis is suf- ficient for the analysis of reflection cracking for different over- lay types. This is appropriate because the model will consider the difference in the mechanisms of crack propagation and the field calibration coefficients. Three separate mechanisms of crack propagation, thermal, traffic bending, and traffic shear- ing, were modeled using Artificial Neural Network (ANN) algorithms. Material Properties The material properties of the overlay are calculated from the design of the asphalt mix of that overlay using a set of ANN algorithms that replicate Witczak’s 1999 (2) and 2006 (3) models of asphalt mixture complex moduli. The input Traffic MaterialProperties Climate EICM Pavement Structure Pavement Response (σ, ε) Model: Multi-layer elastic Pavement Distress Models Pavement Performance Predictions INPUT OUTPUT MODELS Interlayer Existing Pavement Conditions Pavement Response Model Stress Intensity Factor (SIF) Artificial Neural Network (ANN) Pavement Distress Model Reflection Cracking (Thermal, Shearing, Bending) Pavement Performance Prediction: Reflection Cracking Extent and Severity MEPDG Model Reflection Cracking Model Figure 1. Compatibility of the MEPDG software with the reflection cracking model.

data required for these models include the properties of the binder, some gradation of the aggregates, and the volumetric composition of the mix. The binder properties may be input in any of the three MEPDG levels: Level 1: The input for this level will be the six measured values of the master curve of the binder (the glassy shear modulus, the crossover frequency, rheological index, the defining temperature, and the two time-temperature shift function coefficients). The properties of extracted binders that were measured in the Strategic Highway Research Program (SHRP) asphalt studies (4) are summarized in Appendix G. Level 2: The input will be the PG of the binder and the geo- graphical location of the project. All six binder proper- ties that were measured, tabulated, and reported in the SHRP asphalt studies for a variety of asphalt binders in each of the four principal climatic zones (4) will be used. The program will use the means of the WLF coefficients, defining temperature and crossover frequency for the principal climatic zone where the project is located and then calculate the glassy shear modulus and rheological index from the Performance Grade of the binder. Level 3: The input will be the geographical location of the project. The mean values of all six master curve proper- ties in the climatic zone where the project is located will be used. The fracture properties of the overlay mixture are derived from the input properties and the complex moduli neural network algorithms. The design method does not require lab- oratory tests of the crack growth in a mixture; it allows the user to try numerous variations of a mixture to determine which has the best resistance to reflection cracking. The mate- rial properties of the layers of the existing pavement may be input either from a Falling Weight Deflectometer measure- ment or can be assumed. The growth of cracks due to both thermal and traffic stresses is predicted using the fracture properties for predicting fatigue cracking (4). Traffic The daily traffic is input as individual axle loads and is iden- tical to what is required by the MEPDG software for the three levels of input. The user can accept standard traffic distributions that are incorporated into the MEPDG or use traffic data taken from W4 Tables. The load imposed by the tire on the pavement is assumed to result in a rectangular, rather than a circular, uni- form pressure distribution. Crack Growth and Pavement Temperature The crack growth is calculated each day taking into account the temperature calculated to be at the tip of the crack on that day. The temperature is computed using U.S. Weather Bureau data that can be accessed readily through websites (5, 6) and Appendix B of this report. The computational model of tem- perature differs from that used in the MEPDG; it calculates the temperature more accurately than by using in the Enhanced Integrated Climatic Model as part of the MEPDG. It was considered necessary to increase the accuracy of computing the pavement temperature with depth because of the rele- vance of the thermal stress contribution to the growth of a reflection crack. Computational Efficiency Computational efficiency of the software was accomplished by calculating the growth of reflection cracks by the three dif- ferent mechanisms separately and then combining the num- ber of days that each required to grow vertically all the way through the overlay. Another contributing factor to effi- ciency in running time was realized by re-programming all of the subprograms from their original language into the C# language which is used in the MEPDG. Additional effi- ciency was achieved by using ANN algorithms to speed up the frequent calculations of mixture modulus and stress intensity factors that are done each day in a simulated pave- ment life. The stress intensity factor computations were particularly useful in cutting down on the program running time instead of using finite element calculations for that purpose. The objective of computational efficiency was to reduce the overall program run time down to a minimum as a convenience to the user or this program. The actual run time for a 20 to 30 year pavement life simulation is a mat- ter of seconds and at most a few minutes, depending upon the computer that is used. Calibration to Field Data Calibration to field data recognizes that there are three degrees of severity in reflection cracking: low, medium, and severe. Some or all levels of severity may be present on a given pavement section at any time. An S-shaped curve was fit through the field data representing the total length of surface cracks at high (H), high plus medium (MH), and high plus medium plus low levels of cracking severity (LMH). The difference in the total length between any two curves gives the total length of the different levels of distress. Fig- ure 2 illustrates the three cumulative severity curves. Three sets of S-shaped curves were generated with each pavement test section; each curve has a characteristic scale and shape parameter. The scale parameter, ρ, is the number of days required for the crack length to reach 0.368 (1/e) of its max- imum length. The shape parameter, β, shows how sharply the curve is rising when it reaches the number of days given 3

4by the scale parameter, ρ. The three sets of coefficients that are developed for each type of overlay predict the number of days that a given overlay will require to reach the scale points, ρ, on the each of the three distress curves. A detailed discussion of the S-shaped curve and examples from the field data that were analyzed in this project is provided in Chapter 2, the section entitled “Reflection Cracking Amount and Severity Model.” Appendix L shows how to determine the ρ-value from field data, and makes it possible for a user to develop a set of calibration coefficients. By inserting a set of calibration coefficients into the software, an agency can develop a regional or local version of the overlay analysis model. Use in Design The reflection cracking program presented in this report is a tool for designing an overlay. The output from the program shows graphically the rate of reflection cracking length and severity increase with the number of days after construction. The program runs as a subroutine of the MEPDG software, executes a 20-year set of computations in a relatively short time, and allows the trial of a variety of mixture designs, over- lay thicknesses, and reinforcing or strain-absorbing interlay- ers to determine which combination provides the desired service life within acceptable costs. 0 20 40 60 80 100 - 2,000 4,000 6,000 8,000 10,000 No. of Days % C ra ck L en gt h β1 < 1.0 e-1 = 36.8% ρ1 ρ2 ρ3 β2 = 1.0 β3 > 1.0 Figure 2. Parameters in reflection cracking severity model.

Next: Chapter 2 - Findings »
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TRB’s National Cooperative Highway Research Program (NCHRP) Report 669: Models for Predicting Reflection Cracking of Hot-Mix Asphalt Overlays explores mechanistic-based models for predicting the extent and severity of reflection cracking in hot-mix asphalt overlays.

Appendices A through T to NCHRP Report 669 are available online. The titles of the appendices are as follows:

Appendix A: Program Flow Charts

Appendix B: Pavement Temperature Prediction

Appendix C: Categorization of Traffic Loads

Appendix D: Cumulative Axle Load Distribution as a Function of Tire Footprint Length

Appendix E: Determination of Hourly Traffic Numbers

Appendix F: Artificial Neural Network Models of Stress Intensity Factors

Appendix G: Binder and Mixture Properties

Appendix H: Fracture Properties of Asphalt Mixtures

Appendix I: Viscoelastic Thermal Stress Computation

Appendix J: Collection of Test Sections and Field Performance Data

Appendix K: Reflection Cracking Amount and Severity Model

Appendix L: Calibration of the Reflection Cracking Amount and Severity Model

Appendix M: Calibrated Parameters of the Reflection Cracking Amount and Severity Model

Appendix N: Calibration of the Computational Model to Field Data

Appendix O: User’s Guide to the Reflection Cracking Model

Appendix P: User’s Guide to the Computational Model to Field Data Calibration Program

Appendix Q: Finite Element Program to Calculate Stress Intensity Factor

Appendix R: Evaluation of Available Reflection Cracking Models

Appendix S: Sensitivity Analysis of Designing Program

Appendix T: The Comparison of Field Data and Predicting Results

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