Material informatics are the theoretical core of the Materials Genome Initiative,which provides critical methods for performance improvement and new material development of asphalt mixtures composed of multiphase,random structures,and complex behaviors at multiple scales.This paper reviews the application of material informatics in the performance prediction and durability enhancement of bitumen and asphalt mixtures to promote the research and application of material informatics.First,the essential connotations of the material genome and material informatics are analyzed,and their applications in asphaltic materials are summarized.Common material data standards are then summarized.The development of multiscale characteristics and material gene databases for bitumen and asphalt mixtures is reviewed.Furthermore,research on asphalt property prediction and modified asphalt composition optimization based on the chemical composition and colloidal structure genes is introduced.The application of data mining and machine learning algorithms for predicting the mechanical and service performances of asphalt mixtures is outlined,including the mixture design indicators,dynamic modulus,high-temperature rutting resistance,fatigue resistance,low-temperature cracking resistance,and water stability.The composition and structure optimization of asphalt mixtures based on performance prediction and intelligent optimization methods are analyzed to improve the performance of the asphalt mixture.Finally,the framework of the informatics for asphalt mixture materials is discussed.The potential challenges in the asphalt mixture gene system and performance prediction using machine learning are analyzed.Potential problems for future material informatics research are also discussed.This review could provide promotion to the durability improvement of asphalt pavement materials.
维普
万方数据