Generalized Methodology to Develop Mechanistically Informed Asphalt Mixture Layer Coefficients for AASHTO 1993 Pavement Design Approach

Academic Article


  • This paper presents a generalized framework for determining mechanistically informed layer coefficients (a-values) for asphalt mixtures in the AASHTO empirical pavement design approach. The layer coefficients influence the layer thicknesses and consequently the structural capacity of pavements. Therefore, it is critical to determine reliable mechanistically informed a-values. A set of 18 commonly used asphalt mixtures in New Hampshire was selected for investigation including different types of hot mix and cold central plant recycled mixtures that are used as wearing, binder, and base course layers. Laboratory characterization was conducted using the complex modulus, semi-circular bend, and direct tension cyclic fatigue testing methods. The mixtures were evaluated using three performance index parameters: complex modulus rutting index parameter, rate-dependent cracking index parameter, and a new continuum damage parameter ([Formula: see text]). The measured field performance of wearing course mixtures in terms of International Roughness Index was used to back-calculate the in situ performance-based layer coefficients (aIRI-values). Using a normal distribution function, the results from performance testing were incorporated with the aIRI-values to develop mechanistically informed mix-specific layer coefficients. In addition, a typical layer coefficient at specific reliability levels for each mix category including hot mix wearing course, hot mix binder and base course as well as cold central plant recycled mix course are proposed for New Hampshire. The recommended a-values are 0.48 for hot mix wearing, 0.41 for hot mixed binder and base, and 0.28 for cold recycled base mixtures; these are approximately 25% higher than the currently used a-values in New Hampshire.
  • Authors

  • Nemati, Rasool
  • Dave, Eshan
  • Sias, Jo
  • Status

    Publication Date

  • February 2022
  • Has Subject Area

    Published In

    Digital Object Identifier (doi)

    Start Page

  • 312
  • End Page

  • 324
  • Volume

  • 2676
  • Issue

  • 2