Image Processing Method to Estimate the Wearing Condition of Slurry Seal Mixtures

[2]  William G. Buttlar,et al.  Performance Evaluation of Asphalt Mixtures with Reclaimed Asphalt Pavement and Recycled Asphalt Shingles in Missouri , 2019, Transportation Research Record: Journal of the Transportation Research Board.

[3]  Mahyar Arabani,et al.  Performance evaluation of dry process crumb rubber-modified asphalt mixtures with nanomaterial , 2018 .

[4]  N. Tabatabaee,et al.  Investigating short-term and long-term binder performance of high-RAP mixtures containing waste cooking oil , 2019, Journal of Traffic and Transportation Engineering (English Edition).

[5]  M. Saghafi,et al.  Performance Evaluation of Slurry Seals Containing Reclaimed Asphalt Pavement , 2019, Transportation Research Record: Journal of the Transportation Research Board.

[6]  A. Faheem,et al.  Direct Characterization of Aging Diffusion in Asphalt Mixtures Using Micro-Indentation and Relaxation (MIR) , 2017 .

[7]  Mahyar Arabani,et al.  Laboratory investigation of hot mix asphalt containing waste materials , 2017 .

[8]  Halil Ceylan,et al.  Using X-ray computed tomography to study paving materials , 2007 .

[9]  Kim Jenkins,et al.  Finite element modelling and damage quantification of chip seals , 2017 .

[10]  H. Bahia,et al.  Development of an image-based multi-scale finite-element approach to predict mechanical response of asphalt mixtures , 2015 .

[11]  Mohammad Rashidi,et al.  Genetic programming model for estimation of settlement in earth dams , 2018 .

[12]  Performance Evaluation of the Cement Stabilized Reclaimed Materials for Use in Pavement Foundations , 2018, International Conference on Transportation and Development 2018.

[13]  Amir Hossein Alavi,et al.  New machine learning-based prediction models for fracture energy of asphalt mixtures , 2019, Measurement.

[14]  Kim Jenkins,et al.  FEM SEAL-3D: development of 3D finite element chip seal models , 2020 .