Abstract
There are several environmental factors such as temperature differential, moisture, oxidation, etc. that affect the extended life of the modified asphalt influencing its desired adhesive properties. Knowledge of the properties of asphalt adhesives can help to provide a more resilient and durable asphalt surface. In this study, a hybrid of Bayesian optimization algorithm and support vector regression approach is recommended to predict the adhesion force of asphalt. The effects of three important variables viz., conditions (fresh, wet and aged), binder types (base, 4% SB, 5% SB, 4% SBS and 5% SBS), and Carbon Nano Tube doses (0.5%, 1.0% and 1.5%) on adhesive force are taken into consideration. Real-life experimental data (405 specimens) are considered for model development. Using atomic force microscopy, the adhesive strength of nanoscales of test specimens is determined according to functional groups on the asphalt. It is found that the model predictions overlap with the experimental data with a high R2 of 90.5% and relative deviation are scattered around zero line. Besides, the mean, median and standard deviations of experimental and the predicted values are very close. In addition, the mean absolute Error, root mean square error and fractional bias values were found to be low, indicating the high performance of the developed model.
Highlights
A resilient asphalt pavement ensures smooth vehicle movement and resists the harmful effects of the environment [1,2]
The differed processes of deterioration or prolonged durability are the result of better properties due to the actions taken, which are gradually eliminated by the effects of moisture and oxidation over the life of the asphalt pavement surface
Support Vector Regression (SVR) model model developed in adhesion forces in in asThe in this thispaper paperisisused usedtotopredict predictthe the adhesion forces asphalt binders
Summary
A resilient asphalt pavement ensures smooth vehicle movement and resists the harmful effects of the environment [1,2]. The differed processes of deterioration or prolonged durability are the result of better properties due to the actions taken, which are gradually eliminated by the effects of moisture and oxidation over the life of the asphalt pavement surface. Based on this temporary solution, it can be concluded that providing properties developed over a longer time can extend the durability of asphalt surfaces. Using the pointed tip on top of the flexible support, the AFM uses the tip of the flexible support to evaluate the surface of the sample. By Hooke’s law, the support acts as spring types of support during the deflection types of movement
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