Leveraging Artificial Intelligence In Structural Engineering: Current Trends And Future Prospects

Abstract

As the field of structural engineering continually evolves, the integration of artificial intelligence (AI) emerges as a pivotal force driving innovation and efficiency. This paper provides a comprehensive overview of the current landscape of AI in structural engineering, examining its applications, challenges, and future prospects. A thorough literature review establishes the foundation, highlighting the limitations of traditional methods and the pressing need for advanced solutions. The fundamentals of AI in structural engineering are explored, elucidating key concepts such as machine learning and neural networks. Real-world applications are showcased through case studies, illustrating the transformative impact of AI on design optimization, predictive maintenance, and risk assessment. However, challenges such as data privacy and model interpretability are also discussed, underscoring the importance of ethical considerations. The paper concludes with a forward-looking perspective, identifying future directions and opportunities for further research and development. As AI continues to shape the future of structural engineering, this paper aims to contribute to the understanding of its potential, paving the way for a more resilient, sustainable, and innovative built environment.