Seismic damage indices (SDIs) quantify damages in civil structures at local or global level due to seismic activities with the help of various demand and capacity parameters. Conventionally, SDI estimation requires complex and computationally demanding nonlinear time-history analysis (NTA) to find the values of the demand parameters. Nowadays, buildings are equipped with sensors to monitor their responses during seismic activity. Therefore, a novel method utilizing such recorded floor-displacement data of reinforced concrete (RC) plane frames along with local and global capacity-based parameters to predict combined global damage index (GDI) is presented here. Two different GDI formulas, depending on the type of capacity parameters, are developed following the proposed method. Multilinear regression analysis is performed to develop the proposed formulas such that they can predict the GDIPA\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$GDI_{\textrm{PA}}$$\end{document} calculated from hysteresis energy-based weighted average of modified Park and Ang local damage indices. The application of the new method does not need dynamic responses of RC frames obtained from NTA. However, for establishing the new method in the present study, the output of NTAs for different RC frames due to several design spectrum-compatible ground motions are used for training and validation. Also, the explicit expressions for the regression coefficients are provided in terms of some structural properties (e.g., fundamental period, total height) and local soil type for wider applicability. It has been found that the estimated GDI values using the proposed method can satisfactorily represent global damage states based on the limiting values of GDIPA\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$GDI_{\textrm{PA}}$$\end{document} for the RC frames.

A novel method is proposed for predicting the combined global damage index through newly developed formulae utilizing recorded floor-displacement data, local and global capacity-based parameters for 3D RC buildings. Multilinear regression analysis is performed to develop the new formulae for predicting the global damage index obtained from modified Park and Ang-type 3D local damage indices. Further, explicit expressions for the global damage coefficients of the new formulae are developed as a function of structural properties and soil type for wider applicability of the formulae. The computed global damage indices are found to represent the damage states of RC buildings satisfactorily.