Stability prediction for asphalt mixture based on evolutional characterization of aggregate skeleton. (30th June 2021)

• Record Type: Journal Article
• Authors: Jin, Can; Wan, Xiaodong; Liu, Pengfei; Yang, Xu; Oeser, Markus
• Other Names: Wang Dawei guestEditor.; Kaliske Michael guestEditor.; Oeser Markus guestEditor.
• Is Part Of: Computer-aided civil and infrastructure engineering. Volume 36:Number 11(2021)
• Page Start: 1453
• Page End: 1466
• Publication Date: 2021-06-30
• Subjects: Civil engineering -- Data processing -- Periodicals; Computer-aided engineering -- Periodicals; 624.0285
• DOI: 10.1111/mice.12742
• Languages: English
• ISSNs: 1093-9687

Abstract

Abstract: The aggregate skeleton significantly influences the deformation resistance of asphalt mixtures. A stable skeleton has good interlocking effects and load transfer ability to resist deformation of mixtures during loading. Therefore, the methodology to accurately evaluate the morphology of aggregate skeleton based on the mechanism of load transfer inside mixtures is of great value to predict the mixture stability. The objective of this study is to predict and validate mixture stability from the perspective of evolutional morphologies of the skeleton. The methodology has three main steps, which are as follows: (1) the initial morphology of the aggregate skeleton is characterized and evaluated; (2) the topological and non‐topological evolutions of the skeleton morphology during external loading are characterized; and (3) the strain energy of the mixture and the stress distribution on contact regions in the skeleton are used to analyze and validate the prediction of the mixture's stability. Simulations of uniaxial displacement‐controlled tests of three cylindrical specimens drilled in a field‐compacted test track were conducted, and 7.5, 15, 22.5, and 30 s were selected as time points in the simulation to analyze mixture stability. Results indicate that a mixture has a better load‐bearing capacity when its initial skeleton contains more chains with higher evaluation indices, which proves the reliability of the stability prediction using the proposed method.