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@article{180366,
author = {RISHAB},
title = {Hybrid fiber reinforcement in high-strength concrete: A comprehensive review of mechanisms, performance, and challenges},
journal = {International Journal of Innovative Research in Technology},
year = {2025},
volume = {12},
number = {1},
pages = {1191-1197},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=180366},
abstract = {High-strength concrete (HSC) is widely utilized in modern construction due to its superior compressive strength. However, its inherent brittleness, low tensile capacity, and limited ductility pose significant limitations, particularly in crack propagation and long-term durability. This review explores the effectiveness of hybrid fiber reinforcement systems combining metallic (steel) and natural (coir and palm) fibres to overcome these challenges. The synergistic effect of multiple fiber types provides enhanced crack resistance, improved energy absorption, and greater residual strength compared to mono-fiber systems. A comprehensive review of experimental studies—including M50-grade concrete specimens with fiber proportions of 0.5% steel, 0.25% coir, and 0.25% palm—demonstrates notable improvements in flexural strength, crack resistance, and post-peak ductility. The chemical treatment of natural fibers contributes to long-term durability and mitigates biodegradation risks. Furthermore, recent advancements in predictive modelling using artificial neural networks (ANNs) are discussed, showcasing their ability to accurately model complex, nonlinear behaviour in fiber-reinforced concrete systems. Despite substantial progress, a clear research gap persists in optimizing hybrid fiber combinations, evaluating their long-term structural performance, and assessing environmental impacts. This review emphasizes the potential of hybrid fiber-reinforced HSC as a sustainable and high-performance material for future structural applications.},
keywords = {High-strength concrete, hybrid fibers, steel fiber, coir fiber, palm fiber, ductility, crack resistance, flexural strength, artificial neural network, sustainable construction.},
month = {June},
}
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