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Updated: Aug 5, 2025

Determination of Aggregate Surface Morphology at the Interfacial Transition Zone ITZ
Published on: December 16, 2019
A Numerical Study of ITZ Percolation in Polyphase Concrete Systems Considering the Synergetic Effect of Aggregate
Jianjun Lin1,2,3, Qingxin Zhao1,3, Huisu Chen2
1State Key Laboratory of Metastable Materials Science and Technology, Yanshan University, Qinhuangdao 066000, China.
Abstract:
The percolation of the interfacial transition zone (ITZ) is generally regarded as an important factor that may accelerate the penetration of aggressive agents in concrete materials, and its threshold is largely determined by the features of aggregates. In most numerical studies about ITZ percolation, both fine aggregates and coarse aggregates are assumed to be the particles of uniform shape, and their size distributions are generally strung together by a single function, which is quite different from reality. To quantify the ITZ percolation associated with the polydispersity of aggregate shapes and size gradations in a more realistic way, the two-dimensional (2D) meso-scale model of concrete is generated by simplifying coarse aggregates and fine aggregates as polygons and ovals, respectively. Moreover, the size gradations of them are also represented by two separate expressions. By combining these models with percolation theory, the percolation of ITZ in the 2D case is explicitly simulated, and the influence of aggregate shape- and size-diversities on the critical threshold ϕagg,c is studied in detail. Based on the simulated results of ϕagg,c, an empirically analytical expression is further proposed to fast predict the ITZ percolation, and its reliability is verified. The results show that the ITZ thickness, average aggregate fineness, coarse aggregate shape, and fine aggregate shapes are the four main contributing factors to the ITZ percolation. Compared with the existing literature, the proposed model here has a broader range of applications (e.g., mortar, concrete, and other granular systems) in the 2D case and can provide the larger predicted results, which may be closer to reality.
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