ML-CCD: machine learning model to predict concrete cover delamination failure mode in reinforced concrete beams strengthened with FRP sheets
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Salahat, Fahed H., Hayder A. Rasheed, and Huthaifa I. Ashqar. “ML-CCD: Machine Learning Model to Predict Concrete Cover Delamination Failure Mode in Reinforced Concrete Beams Strengthened with FRP Sheets.” Software Impacts 21 (September 1, 2024): 100685. https://doi.org/10.1016/j.simpa.2024.100685.
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Attribution 4.0 International
Abstract
ML-CCD is an open-source Python software based on a Machine-Learning model that was utilized to predict the premature failure of reinforced concrete (RC) beams strengthened with Fiber Reinforced Polymers (FRP). The model was trained using a database consisting of 70 experimentally tested beams that failed prematurely due to Concrete Cover Delamination (CCD). The significant beams parameters that influence the CCD failure were used in training the ML-CCD. This software predicts the ultimate strain in the FRP sheets at failure, thus finding its ultimate tensile strength and the effective strengthening ratio for design purposes.