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Preparation of Aligned Steel Fiber Reinforced Cementitious Composite and Its Flexural Behavior
Published on: June 27, 2018
Impact performance and probabilistic reliability of natural fiber-reinforced standard and high-strength concrete
Ajila Hexil S1, Karthikeyan Kothandapani2
1School of Civil Engineering, Vellore Institute of Technology, Chennai, India.
Abstract:
The development of sustainable high-performance concrete has increasingly emphasized the incorporation of natural fibers to improve mechanical and impact resistance. This study presents a comprehensive and novel investigation of multiple natural fibers, coconut (0.5-1.5%), flax (0.1-0.5%), jute (0.15-0.55%), and bamboo, hemp, and kenaf (0.25-1.25%), evaluated in two concrete grades (M25 and M80). In addition to experimental assessment, probabilistic reliability modeling was integrated to characterize the stochastic nature of impact behavior in natural fiber-reinforced concrete (NFRC). Repeated impact testing in accordance with ACI 544-2R demonstrated that coconut fiber at 1-1.25% provided the highest impact resistance, increasing failure counts by 65% in M25 and 83% in M80 relative to the control concrete. Kenaf (0.75-1%) and bamboo (0.5-1%) exhibited moderate improvements of up to 20%, whereas jute, flax, and hemp produced comparatively modest gains of 5-10%. Despite substantial improvements in impact resistance, compressive strength remained comparable to that of the control concrete. Ductility indices and post-cracking ratios revealed distinct post-peak deformation mechanisms governed by fiber type, including pull-out, rupture, and interfacial slip. To further quantify performance differences, a grade-fiber synergy analysis was proposed to evaluate the interaction between concrete strength and fiber efficiency across grades. The probabilistic characterization of impact resistance was performed using Weibull statistics, supplemented by bootstrap resampling and Bayesian uncertainty analysis, enabling assessment of reliability and parameter stability. The results establish a reliability-based framework for optimizing NFRC formulations to improve structural resilience under dynamic loading.
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