Determination of crack propagation rates of mixtures prepared with pure and polymer modified binders by image propagation method

Highways which plays important role for the growth and development of a country constitute a major part of transportation network in our country are built at high costs and in need of a serious inspection and maintenance services. Increase of vehicle and axle load, extreme loads, environmental factors, construction errors, insufficient controls damage highways before due to their service life. These damaged highways needs to be reconstructed or to have a restoration. These restorations must be completed by professionals engineers who either have good knowledge and in order highway pavement must be known well enough. In this study, hot bituminous mixtures were prepared according to the SUPERPAVE method by using pure bitumen and SBS additives. SBS contribution was used as 2%, 3% and 4%. The conditions of the mixtures were observed by applying binder experiments. It was determined that the strength of the mixtures increased with the use of additives and it was predicted that the service life of the coating would be extended with the use of additives. In this study, deep learning methods are mentioned and the state of cracks is examined with SegNet model. It is predicted that the SegNet model will be the reference model if it is used in segmentation problems.