Repartitioning-based aggregate generation method for fast modeling 3D mesostructure of asphalt concrete. (June 2023)

• Record Type: Journal Article
• Authors: Wei, Xin; Sun, Yiren; Gong, Hongren; Li, Yuhua; Chen, Jingyun
• Is Part Of: Computers & structures. Volume 281(2023)
• Publication Date: 2023-06
• Subjects: Asphalt concrete -- Mesostructure -- Random aggregate structure -- Voronoi diagram; Structural engineering -- Data processing -- Periodicals; Electronic data processing -- Structures, Theory of -- Periodicals; 624.171
• DOI: 10.1016/j.compstruc.2023.107010
• Languages: English
• ISSNs: 0045-7949

Abstract

Highlights: A repartitioning-based aggregate generation method of asphalt concrete is proposed. Three-dimensional mesostructures of asphalt concrete are fast generated. A stepwise partitioning method is adopted to obtain various sizes of Voronoi cells. A reshaping process is applied to Voronoi cells to yield very realistic aggregates. A classifying-picking process is used to obtain aggregates of desired gradations. Abstract: A repartitioning-based aggregate generation method is proposed to establish the three-dimensional mesostructure models of asphalt mixture. In this method, a stepwise partitioning procedure is proposed to repeatedly partition the specimen space into Voronoi cells with high variation in shape and size. The number of the Voronoi cells is determined by dividing the volume of the specimen space by the volume of a so-called equivalent sphere; in this way, the sizes of the generated Voronoi cells can be controlled around the sizes of the equivalent spheres. Also, a reshaping-classifying-picking procedure is developed and applied to the Voronoi cells to obtain very realistic aggregates with expected gradations to form final mesostructures. The effectiveness of the repartitioning-based aggregate generation method was validated by using the aggregate gradation and complex modulus test data of asphalt concrete. Compared with several recent aggregate generation methods, the proposed method can faster generate three-dimensional mesostructures with large dimension and high aggregate content. Besides, it can explain quantitatively the effects of mesostructural properties on macromechanical characteristics of asphalt concrete, thus providing an efficient and robust tool for advancing material design of asphalt concrete.