Mesoscopic Numerical Analysis of Concrete Damage Based on Random Aggregate Model
- DOI
- 10.2991/978-94-6463-449-5_11How to use a DOI?
- Keywords
- concrete; mesomechanics; random aggregate model; expansion factor; damage destruction
- Abstract
Concrete is defined as a three-phase composite material consisting of aggregate, mortar matrix, and interfacial transition zone (ITZ). To investigate the influence of various phases on the strength and damage of concrete, this research constructs a two-dimensional random aggregate model of concrete based on mesomechanics. In this foundation, this research further applies the plastic damage model to simulate the mechanical properties and damage of concrete beams under three-point bending. Meanwhile, this research employs the contraction-expansion factor to generate aggregates with diverse shapes, thereby exploring the influence exerted by aggregate shapes on the damage of concrete beams. Relevant research findings indicate that the mechanical properties and damage forms of concrete depend on the distribution of aggregate as well as the strength of the mortar matrix, with aggregate shapes generating a significant impact on the damage of concrete.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yawei Li AU - Lei Tian PY - 2024 DA - 2024/06/30 TI - Mesoscopic Numerical Analysis of Concrete Damage Based on Random Aggregate Model BT - Proceedings of the 2024 8th International Conference on Civil Architecture and Structural Engineering (ICCASE 2024) PB - Atlantis Press SP - 113 EP - 121 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6463-449-5_11 DO - 10.2991/978-94-6463-449-5_11 ID - Li2024 ER -