YIN Hai-peng, LI You-tang, LI Wu-qiang, HUANG Hua. INFLUENCE OF AGGREGATE GEOMETRIC CHARACTERISTICS ON COMPRESSIVE STRENGTH AND DAMAGE PROCESS OF PARTICLE-REINFORCED RESIN MATRIX COMPOSITE[J]. Engineering Mechanics, 2024, 41(3): 222-231. DOI: 10.6052/j.issn.1000-4750.2022.04.0296
Citation: YIN Hai-peng, LI You-tang, LI Wu-qiang, HUANG Hua. INFLUENCE OF AGGREGATE GEOMETRIC CHARACTERISTICS ON COMPRESSIVE STRENGTH AND DAMAGE PROCESS OF PARTICLE-REINFORCED RESIN MATRIX COMPOSITE[J]. Engineering Mechanics, 2024, 41(3): 222-231. DOI: 10.6052/j.issn.1000-4750.2022.04.0296

INFLUENCE OF AGGREGATE GEOMETRIC CHARACTERISTICS ON COMPRESSIVE STRENGTH AND DAMAGE PROCESS OF PARTICLE-REINFORCED RESIN MATRIX COMPOSITE

  • Aggregate geometry is vital for the mechanical properties of granular composites and is also the theoretical basis for the precise design of composites. Therefore, taking particle-reinforced resin matrix composite (PRMC) as an object, the influence of aggregate geometry on the compressive strength and damage process of PRMC is studied. A refined digital aggregate of PRMC is established by employing PFC and 3D MAX, and the effect of aggregate comprehensive geometry properties on characteristic of PRMC dynamic damage is analyzed. Then, the effect of single geometrical characteristics on the mechanical properties of PRMC by substituting circular aggregates of different particle dimensions through refining and separating the single geometrical characteristics from comprehensive geometry properties. The results show that: the geometrical properties of aggregates affect the distribution of the original micro-damage, leading to the crack propagation and determine the compression failure mode of PRMC. In addition, the results also show that the compression failure process of PRMC has typical random damage characteristics. The aggregate shape, such as edges, corners and, texture improve the compressive strength of PRMC by reducing the fluidity between aggregates, while the aggregate skeleton system needs to find the best parameter combination among fractal dimension, graded series, maximum particle size and, the ratio of maximum to minimum particle size.
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