Rapid Seismic Damage Quantification for Reinforced Concrete Frames using Minimal Strain Inputs and Neural Networks Trained via Pushover Analysis

Key Points

• The aim is to quickly assess seismic damage in reinforced concrete structures after earthquakes using minimal input data.
• Utilized minimal strain inputs to assess seismic damage levels.
• Employed neural networks trained on pushover analysis data.
• Evaluated structural safety for occupancy decisions post-earthquake.
• Proposed method enables rapid and accurate damage quantification.
• Showed strong correlation between minimal strain inputs and damage levels.
• Provided reliable assessments for determining structural safety.