Multi-scale computational model for design of flexible pavement - part III: two-way coupled multi-scaling Academic Article uri icon

abstract

  • 2015 Informa UK Limited, trading as Taylor & Francis Group. A computational multi-scale procedure for designing flexible roadways is developed in this part, the third of a three-part series. In this study, a two-way coupled multi-scale algorithm was developed and utilised to predict the effects on pavement performance caused by variations in local and global design variables. The model is constructed by utilising the finite element method at two simultaneous and two-way coupled length scales, thereby creating a multi-scale algorithm that is capable of accounting for the effects of variations in design parameters on both length scales. Energy dissipation mechanisms such as viscoelasticity in the asphalt mastic, plasticity in the base layer and crack propagation in the asphalt concrete are incorporated within the model for the purpose of predicting permanent deformations in typical roadways subjected to cyclic tyre loadings. The algorithm is briefly described herein, including the experimental properties required to deploy the computational scheme for the purpose of pavement design. The algorithm is subsequently utilised to predict the effects on pavement performance of variations in design variables on the global length scale (metres) such as asphalt concrete layer thickness and base layer yield point as well as design variables on the local length scale (centimetres) such as aggregate volume fraction and asphalt mastic fracture toughness. These demonstrative examples elucidate the power of this new technology for the purpose of designing more sustainable roadways.

published proceedings

  • INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING

author list (cited authors)

  • Allen, D. H., Little, D. N., Soares, R. F., & Berthelot, C.

citation count

  • 17

complete list of authors

  • Allen, David H||Little, Dallas N||Soares, Roberto F||Berthelot, Curtis

publication date

  • April 2017