Predicting impact response of reinforced concrete members using an AEGCN-dynamicformer network

Key Points

• Impact response of reinforced concrete members is accurately estimated using a neural network model.
• The AEGCN-dynamicformer network achieved a prediction accuracy of 92% on test datasets.
• Observational analysis demonstrates the utility of machine learning for structural performance assessment.
• Supports enhanced safety measures in construction based on impact response predictions.