April 2015

Predicting complex shear modulus using artificial neural networks

Developing a predictive model for complex shear modulus of the asphalt binder is a complex technique due to several factors that affect the model’s estimating capability, such as rheological properties and test conditions. Several models were developed in this regard; some of these are linear regression models and relate to rheological properties of asphalt binder. A computational model based on artificial neural...

Author(s): Abdulhaq Hadi Abedali

April 2015

Fatigue evaluation of Iraqi asphalt binders based on the dissipated energy and viscoelastic continuum damage (VECD) approaches

Bituminous materials in roads are subjected to short-term loading each time a vehicle passes. If sufficiently high, the loading results in a loss of rigidity of the material and can, by accumulation in the long term, lead to failure. The resulting fatigue deterioration is of great importance in pavement construction and must be correctly understood in order to ensure adequate structural design. The binder property plays...

Author(s): Abdulhaq H. A. A. Al-Haddad