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VOL. 12, ISSUE 1 (2026)
Performance analysis of concrete structures using deep learning
Authors
CS Arijit Ghosh, Samir Kumar Bandyopadhyay
Abstract
This paper explores the paradigm shift from
traditional empirical and numerical methods to data-driven deep learning (DL)
approaches for assessing the performance of concrete structures. This
comprehensive guide outlines the methodology for evaluating the performance of
concrete structures using deep learning. As infrastructure ages, the need for
rapid, non-destructive, and accurate evaluation grows. We discuss the
integration of Convolutional Neural Networks (CNNs), Recurrent Neural Networks
(RNNs), and Physics-Informed Neural Networks (PINNs) in predicting compressive
strength, detecting cracks, and monitoring structural health. A case study on
bridge deck deterioration demonstrates that DL models achieve up to 96%
accuracy compared to traditional visual inspections.
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Pages:148-157
How to cite this article:
CS Arijit Ghosh, Samir Kumar Bandyopadhyay "Performance analysis of concrete structures using deep learning". International Journal of Commerce and Management Research, Vol 12, Issue 1, 2026, Pages 148-157
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