Research on Digital Design Method of Asphalt Mixture based on Material Genome

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The data-driven material genome method is the trend of material research and development in the future, especially for the asphalt mixture with complex mesostructures and huge applications. In order to promote the method of material genome, material characterization technology, numerical study and genome data base are the key points. However, there is a lack of relevant research on the design of asphalt mixture material. In this project, the concept of material genome method is applied, the meso-scale test and characterization method, finite element method and machine learning method are used to carry out in-depth research on the digital design method of asphalt mixture based on the material genome. First of all, based on industrial CT and digital image processing technology, the method of meso-structural gene representation will be proposed, and the mesostructure model based on random gene information will be established; Secondly, based on the random meso-structural model, combined with the contact and damage parameters obtained from rheological test and digital image correlation test, the finite element model will be established to calculate the mechanical properties. At last, the database of meso-structural genome of asphalt mixture can be established, and the prediction model of mechanical properties of asphalt mixture can be established by machine learning method. This project is of great significance to promote the application of material genome method in asphalt mixture and reduce the research and development cycle and cost.