laboratory study and investigation on significance level of fatigue phenomenon in warm mix asphalt modified with nano-silica

The present research aims to conduct laboratory assessment on fatigue phenomenon in warm mix asphalt modified with nanosilica and including reclaimed asphalt pavement materials by the aid of review on selfhealing behavior and measurement of validity of laboratory results by modeling via neural artificial network in neutral network of spss software. for this purpose, 2% weight of sasobit and 3, 5 and 7 % weights of base bitumentobitumen (85100) were added and they were stirred up by highcut mixer. then, the specimens of fourpoint flexural test were made by the reclaimed bitumen samples. the quantities of 0, 70 and 100% of reclaimed asphalt materials were utilized for aging simulation process in warm mix asphalt to build fourpoint flexural tested slabs. the findings indicate that adding nanosilica may essentially affect rising selfhealing level in warm mix asphalts. the current study intends to present a model based on neural artificial network technique to predict behavior of warm asphalt specimens including different nanomaterial contents and to compare them with the laboratory results for measurement of validity of the given model. the given results show high precision of the model at level of 0.951.