Journal article
Viscoplastic modeling of asphalt mixes with the effects of anisotropy, damage and aggregate characteristics
Mechanics of materials, Vol.37(12), pp.1242-1256
2005
Handle:
https://hdl.handle.net/2376/108748
Abstract
This paper presents an approach for constitutive modeling of the viscoplastic behavior of asphalt mixes. This approach utilizes an anisotropic non-associated flow rule based on the Drucker–Prager yield surface. The selection of this yield surface is motivated by the field stress paths and material properties associated with permanent deformation at high temperatures. The efficacy of the model is demonstrated by analyzing data from compressive triaxial tests conducted at different confining pressures and strain rates for three different mixes. The model parameters are related to the experimental measurements of aggregate shape characteristics, aggregate surface energy, inherent anisotropic distribution of aggregates, and microstructure damage measured using X-ray computed tomography and image analysis techniques. Establishing the relationship between the model parameters and material properties is important in order to optimize the mix properties, and achieve desirable mix performance.
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Details
- Title
- Viscoplastic modeling of asphalt mixes with the effects of anisotropy, damage and aggregate characteristics
- Creators
- Eyad Masad - Department of Civil Engineering and Texas Transportation Institute, Texas A&M University, 3135 TAMU, College Station, TX 77843-3135, United StatesLaith Tashman - Department of Civil and Environmental Engineering, Washington State University, Pullman, WA 99164-2910, United StatesDallas Little - Department of Civil Engineering and Texas Transportation Institute, Texas A&M University, 3135 TAMU, College Station, TX 77843-3135, United StatesHussein Zbib - School of Mechanical and Materials Engineering, Washington State University, Pullman, WA 99164-2920, United States
- Publication Details
- Mechanics of materials, Vol.37(12), pp.1242-1256
- Publisher
- Elsevier Ltd
- Identifiers
- 99900547417001842
- Language
- English
- Resource Type
- Journal article