Research on the Mechanical Strength of Emulsified Asphalt-Cementstabilized Macadam Based on Neural Network Algorithm

Abstract

In this paper, we researched the application of mechanical strength experiment on emulsified asphalt cementstabilized macadam based on neural network algorithm. Based on the analysis of the early diseases of asphalt pavement, which uses semi-rigid base, solving the problem of semi-rigid base asphalt pavement's reflection crack, this paper proposes the research approach that uses a modified semi-rigid base, appropriate pavement structure as the point of starting. Combining with the past emulsified asphalt-cement-stabilized macadam material mixing methods, the construction technologies of cement-stabilized macadam and synchronous chip sealing, this paper has come up with a new method for modification of semi-rigid base. The unconfined compressive strength and splitting strength of the mixtures would decrease as the mixing amount of emulsified asphalt increases, and the reduction rate of compressive strength decreases as the curing age grows. The mixing amount of emulsified asphalt has almost no influence on the flexural-tensile strength at normal temperature, so it can be ignored. The experimental result shows that the emulsified asphalt cement-stabilized macadam has good performance than traditional methods.