Artificial intelligent modeling and optimization of the application of aluminum oxide nanoparticles modified cement asphalt toward non-polluted sustainable environment

摘要

Due to their excellent physicochemical and structural characteristics, aluminum oxide (AL_2O_3) nanoparticles (AlNPs), a family of metal oxide nanoparti-cles, offer a variety of biological uses. Bitumen binds a high percentage (>95) of inorganic macrometer-sized particles to provide a cohesive material suitable for use in road pavement. In this study, AL_2O_3 was added to bitumen as a new bitumen modification to improve the fatigue and rutting performance of bitumen or the base cement asphalt cement (AC) at ratios of 5, 7, and 10 wt by weight of the cement AC. Rheological tests were performed on modified bitumen containing nanoparticles. An extreme learning machine (ELM) analyzes each test outcome. In this case, the properties of AC are greatly affected by the rise in AL_2O_3 concentration. In comparison to the basic AC, the modified AC's viscosity rose by 90 and 104, respectively. The outcomes also demonstrated the excellent compatibility and storage stability of both modifiers at high temperatures. A hot mix of AL_2O_3 modified bitumen was utilized to produce hot cement asphalt samples, and moisture susceptibility was assessed. As a result, the optimal nanoparticle content was chosen, and 7 AL2O3 produced the bestresults.