Experimental and artificial intelligence based analysis of the flexural characteristics of hybrid fibre reinforced concrete using steel, glass and polypropylene.

Autor: Rosaline, S. J. Princess, Latha, P., Shanmugavelu, V. A., Tamilmani, A., Thayalnayaki, D., Santhosh, J.
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Zdroj: AIP Conference Proceedings; 2024, Vol. 3231 Issue 1, p1-10, 10p
Abstrakt: In-depth research on hybrid fiber-reinforced concrete (HyFRC), a substance with potential applications in structural engineering, is presented in this article. We examine the flexural characteristics of HyFRC, a composite made of steel, glass, and polypropylene fibres, with an eye towards how different fibre combinations affect the mechanical properties of concrete. To assess HyFRC's efficacy, a comprehensive experimental programme was run. At a total fibre volume fraction of 0.75%, the results demonstrated a noticeably higher compressive strength, splitting tensile strength, and flexural strength when steel and polypropylene fibres were combined. Effective fracture control allows the concrete to survive higher compressive loads, increasing compressive strength by up to 27% compared to non-fibrous control concrete. A crucial component of concrete performance, the splitting tensile strength in HyFRC was significantly increased thanks to the interaction between steel and polypropylene fibres. Along with better ductility, controlled fracture propagation, and greater strain capacity, HyFRC also shown these properties. The HyFRC also showed a significant increase in flexural strength, making it a suitable material for structural uses, particularly when combined with steel and polypropylene fibres. The features of the load-deflection demonstrated ductile behaviour, in stark contrast to the brittle failure seen in the control concrete. Concurrent with experimental study, an Artificial Neural Network (ANN) model with a remarkable total efficiency of 99.84% was developed, allowing precise predictions of flexural strength based on concrete composition. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index