Advances in structural engineering through artificial intelligence: methods, challenges and opportunities

Main Article Content

Małgorzata Kurcjusz
Rohan Raj Das


Keywords : artificial intelligence, machine learning, deep learning, structural engineering, design optimization, structural health monitoring
Abstract

This paper reviews recent advances in applying artificial intelligence (AI) in structural engineering, with a particular focus on methods, challenges, and opportunities. It examines how machine learning, deep learning, and evolutionary algorithms are transforming traditional design, analysis, and maintenance processes. The integration of AI with building information modelling (BIM), digital twins, and sensor-based monitoring systems is creating a more data-driven engineering environment. However, widespread adoption remains limited by issues such as data quality, model transparency, and a lack of validation frameworks. The study highlights the need for explainable models, ethical oversight, and standardised data practices to ensure the safe and reliable use of AI in structural applications.


 

Article Details

How to Cite
Kurcjusz, M., & Das, R. R. (2025). Advances in structural engineering through artificial intelligence: methods, challenges and opportunities. Acta Scientiarum Polonorum. Architectura, 24(1), 418–430. https://doi.org/10.22630/ASPA.2025.24.28
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