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International Journal of Engineering & Technology Sciences
IJETS 2025, 8 pages - Article ID: IJETS-2502192112938
Revolutionizing Reinforced Concrete Design and Analysis With AI and Machine Learning: Transforming the Future of Structural Engineering
Authors
Natali Elizabeth Lascano Robalino a,
Edwin Iván Soledispa Pereira b,
Jorge Alexander Bucheli García c,d,
Jorge Oswaldo Crespo Bravo c,
Marcelo Fabian Oleas Escalante e,
Jimenez Merchan Carmita Guadalupe e,
Angel Mauricio Espinoza Cotera e
Faculty of Engineering and Applied Sciences, Information Systems Department, Central University of Ecuador, Av. Universitaria, Quito 170521, Ecuador
TERMINAL PORTUARIO DE MANTA, 130802, Manta, Ecuador
Faculty of Engineering and Applied Sciences, Civil Engineering Department, Central University of Ecuador, Av. Universitaria, Quito 170521, Ecuador
Pontifical Catholic University of Ecuador, Department of Civil Engineering, Quito - Ecuador
Faculty of Engineering, Industrial and Architecture, School of Civil Engineering, Laica Eloy Alfaro de Manabi University, Manta, Ecuador
ABSTRACT
The integration of Artificial Intelligence (AI) and Machine Learning (ML) into structural engineering is transforming traditional methods of designing and analyzing reinforced concrete. These advanced technologies enable the creation of more accurate predictive models and real-time design optimization, reducing error margins and enhancing construction efficiency. This article explores how deep neural networks and supervised and unsupervised learning algorithms are revolutionizing engineers’ approaches to complex problems such as load distribution, material strength, and structural failure estimation. Additionally, it examines case studies where AI and ML have facilitated the design of safer, more sustainable, and cost-effective structures. Automation of repetitive tasks and analysis of large experimental datasets are among the advantages these technologies bring to the civil engineering sector. However, challenges such as integration into traditional processes, the need for specialized training, and ensuring the reliability and transparency of obtained results are also identified. This article concludes that the incorporation of AI and ML in the design and analysis of reinforced concrete promises to revolutionize the future of structural engineering, offering innovative solutions tailored to the demands of sustainability and efficiency in construction.
Artificial Intelligence; Reinforced Concrete; Structural Design; Design Optimization; Structural Engineering; Predictive Analysis; Construction Efficiency.