Journal of Civil and Construction Engineering
https://matjournals.net/engineering/index.php/JOCCE
MAT JOURNALS PRIVATE LIMITEDen-USJournal of Civil and Construction Engineering2457-001XA Review on the Effect of Structural Performance of Cable-stayed Bridges
https://matjournals.net/engineering/index.php/JOCCE/article/view/2522
<p><em>Cable-stayed bridges have become a preferred choice for long-span crossings due to their aesthetic appeal, structural efficiency, and cost-effectiveness. The performance of these bridges is highly influenced by factors such as cable arrangement, pylon height, deck stiffness, and material properties. This review critically examines recent studies on the structural performance of cable-stayed bridges, focusing on parameters such as load-carrying capacity, deflection behavior, vibration characteristics, and durability under various environmental and loading conditions. The review highlights the influence of design configurations, stressing techniques, and construction methodologies on the overall structural behavior. Additionally, challenges related to fatigue, cable tensioning, and dynamic response are discussed to provide a comprehensive understanding of the factors affecting performance. The findings can assist engineers and researchers in optimizing design strategies and improving the safety, durability, and efficiency of future cable-stayed bridge projects. </em></p>Avinash KumarBhagwan Das
Copyright (c) 2025 Journal of Civil and Construction Engineering
2025-10-062025-10-0618Artificial Intelligence in Civil Engineering: Applications, Research Gaps, and Future Directions
https://matjournals.net/engineering/index.php/JOCCE/article/view/2542
<p><em>Artificial intelligence (AI) has emerged as a transformative technology in civil engineering, enabling predictive analytics, real-time monitoring, and automation. Unlike traditional deterministic models, AI offers data-driven approaches that enhance efficiency, accuracy, and sustainability. This study reviews the applications of AI in structural health monitoring, project management, materials research, transportation systems, and disaster management. Comparative analysis demonstrates AI’s superior performance, such as improving crack detection accuracy to over 90%, reducing project delays by 15%, and achieving ±5% accuracy in predicting concrete compressive strength. Research gaps, such as a lack of standardized datasets, model interpretability, and integration with codes, are discussed. Case studies from India and abroad provide proof of AI’s effectiveness. The findings suggest that AI can redefine civil engineering by augmenting human expertise, creating safer, smarter, and more sustainable infrastructure. </em></p>Mahadeva M.Keerthana S.
Copyright (c) 2025 Journal of Civil and Construction Engineering
2025-10-092025-10-09915