Download or read book A Study of Sand-asphalt Mixtures written by Parag Ravindran and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Asphalt bound mixtures have been put to diverse uses. The complicated nature of the material and the demanding conditions under which it is used preclude complete solutions to questions on load bearing capability under field conditions. In proportion to the quantity of its usage and in acknowledgment of modeling complexity, the material has been interrogated by many researchers using a variety of mechanical tests, and a plethora of linear viscoelastic models have been developed. Most models are intended to account for specific classes of problems. This work addresses the conspicuous absence of systematic documentation of normal forces generated as a result of shear. The normal force generated during simple shear is a clear indication of the nonlinear nature of the material. The effect of fillers (hydrated lime and limestone), air voids, aggregate gradation, asphalt source and step loading on normal force generation during torsion is experimentally investigated. Based on experimental evidence, a non-linear thermomechanical model for sand-asphalt mixtures based on the idea of multiple natural configurations is developed. The model accounts for the fact that the mixture has a natural configuration (stressfree configuration) which evolves as it is subjected to loads. Assumptions are made regarding the manner in which the material stores and dissipates energy. A key assumption is that among the various constitutive relations possible, the one that is chosen is the one that maximizes the rate of entropy production. The model that is developed accounts for the anisotropic nature of the response. The experimental results show that asphalt bound mixtures generate significant normal forces even at low rotation rates. The source of asphalt, aggregate gradation, fillers and air voids have a pronounced effect on normal stress generation. The model is corroborated against data from torsion experiments.