A Mechanistic–Empirical Model for Top–Down Cracking of Asphalt Pavements Layers (2018) / Chapter Skim
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101 CHAPTER 5. INTERPRETATIONS, APPRAISAL, AND APPLICATIONS Introduction This project developed an asphalt pavement top-down cracking design program which is based on calibrating predicted top-down cracking lives to observed top-down cracking distress in asphalt pavements.
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102 mechanistic data with which to "train" the ANN algorithms for crack growth. This was done by calculating a large set of J-integral data for a variety of material and pavement structures using a two-dimensional finite element approach.
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103 defined by two parameters: ρ, the scale parameter and β, the shape parameter. The scale parameter is the number of days required for the percentage of longitudinal cracks to reach 36.8 percent of the maximum length of the cracks in the pavement surface.
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104 Figure 5.1 (a)
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105 Figure 5.1. Prediction of Calibration Coefficients Prediction of Top-Down Cracking Distress Curve With the estimated calibration coefficients, the top-down design program can be used to predict the growth of top-down cracking length given the material properties, pavement structure, traffic, and climate information.
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106 Table 5.1 Typical Pavement Sections in Different Climatic Zones Climatic Zone/ State AAD TT *
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107 (a) Pavement Sections in DF Zone (b)
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108 (c) Pavement Sections in WNF Zone (d)
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