Bibliometric analysis reveals advancements in mechanical properties and sustainability of fiber-reinforced concrete, suggesting a growing integration with machine learning techniques.
Fiber-reinforced concrete (FRC) is a key innovation in civil engineering, providing improved mechanical properties and durability. This study uses bibliometric analysis to explore trends, advancements, and future directions in FRC research. By analyzing 292 articles from 2010 to March 2025 using VOSviewer software, the study offers a comprehensive overview of FRC applications, such as enhancing tensile strength, crack resistance, and structural sustainability. Challenges identified include cost-effectiveness, scalability, and material compatibility. The research highlights influential institutions, authors, and countries contributing to FRC advancements and examines emerging themes like machine learning (ML) integration. ML techniques, including artificial neural networks and regression models, are increasingly employed to optimize FRC formulations and improve performance predictions. Research gaps, such as the need for hybrid methodologies and interdisciplinary collaboration, are also identified. The study emphasizes the growing focus on sustainability, including the development of eco-friendly materials and the transformative potential of advanced computational techniques in FRC applications. By providing insights into global research trends and key contributions, this analysis serves as a valuable resource for researchers, practitioners, and policymakers. It underscores the importance of integrating FRC with innovative technologies to foster sustainable and efficient construction practices in civil engineering.
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Gomaa et al. (2025) studied this question.
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