Semiempirical, Analytical, and Computational Predictions of Dynamic Modulus of Asphalt Concrete Mixtures

Author:

Aragão Francisco T. S.1,Kim Yongrak2,Karki Pravat3,Little Dallas N.4

Affiliation:

1. W325.2 Nebraska Hall, University of Nebraska–Lincoln, Lincoln, NE 68588-0531.

2. W351 Nebraska Hall, University of Nebraska–Lincoln, Lincoln, NE 68588-0531.

3. W333.3 Nebraska Hall, Department of Civil Engineering, University of Nebraska–Lincoln, Lincoln, NE 68588-0531.

4. Department of Civil Engineering, Texas A&M University, 601 CE/TTI Building, College Station, TX 77843-3135.

Abstract

Dynamic modulus is the key property used to characterize stiffness of asphaltic mixtures in pavement performance evaluation programs such as the Guide for Mechanistic–Empirical Design of New and Rehabilitated Pavement Structures. This paper investigates various models for predicting the dynamic modulus of asphalt mixtures and compares model predictions with experimental test results. The predictions of two semi-empirical models (Witczak's model, modified Hirsch model), an analytical micromechanics model (Hashin's model), and the computational micromechanics model are compared with the dynamic modulus test results obtained from cylindrical asphalt concrete specimens. For the computational micromechanics approach, the finite element method was incorporated with laboratory tests that characterize the properties of individual mixture constituents and with a digital image analysis technique to represent detailed microstructure characteristics of asphalt concrete mixtures. All predicting models investigated in this paper are in fair agreement with the test results. Witczak's equation simulates dynamic moduli somewhat greater than laboratory test results, whereas the modified Hirsch model generally underpredicts moduli. The computational micromechanics model presents a relatively higher deviation at lower loading frequencies, but it shows better predictions because the loading frequency is higher. Hashin's analytical micromechanics model is limited to accurately predicting the dynamic modulus of the asphalt mixtures because of geometric simplifications and assumptions. With further improvements, the computational micromechanics method incorporated with the testing protocol seems attractive, because it can directly account for geometric complexity due to aggregates and inelastic mixture component properties with fewer of the required laboratory tests.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Reference33 articles.

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3. Characterization of brazilian asphalt mixtures with machine learning;Rio Oil and Gas Expo and Conference;2022-09-26

4. A nonlinear hyper-viscoelastic model for predicting recoverable behavior of largely-deformed asphalt mortar;Construction and Building Materials;2022-02

5. Numerical study of the aggregate contact effect on the complex modulus of asphalt concrete;Materials & Design;2022-01

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