An Alternative Procedure for the Description of Seismic Intensity Parameter-Based Damage Potential

This study presents an alternative statistical approach for describing the damage potential of R/C structures using various seismic intensity parameters. By employing a comprehensive set of 34 Intensity Measures (IMs) and three well-known Global Damage Indices (DIs), a correlation study was initially conducted to assess the predictive capacity of the selected IMs in estimating a structure's damage grade. Multiple regression analyses were performed to determine the most suitable IMs for damage prediction, utilizing only the highest correlated IMs with the selected DIs, employing both conventional regression models and a novel alternative approach by transforming the IMs for each predicted DI. The IMs were modified through exponentiation, using powers directly dependent on each IM's rank correlation coefficient with the respective DI. Employing the rank correlation coefficients to modify the IMs effectively amplifies the influence of those that present the highest agreement with the observed damage. The results demonstrate that energy-related and spectral-based IMs correlate highly with structural damage. The generated models exhibit high accuracy in predicting the observed damage grade, with the models based on the proposed approach showing improved performance in estimating the sustained damage grade while maintaining computational efficiency in terms of their computational time and results' accuracy.