Structural damage detection of shear frame model using parallel physics-informed neural network

Key Points

• Structural analysis reveals that a physics-informed neural network efficiently identifies shear frame damage.
• The method achieves a high detection accuracy rate of 95% across various damage scenarios.
• Analysis employs a parallel approach utilizing machine learning techniques for robust damage detection.
• Highlights the potential to improve structural monitoring systems with enhanced predictive capabilities.