Ground motion parameters and damage correlation in plan irregular L-shape steel structure with BRB

Abstract

Irregularly designed structures frequently experience greater damage compared to regular buildings as a result of elevated torsional reactions and stress concentration, as indicated by evaluations of damage carried out subsequent to past seismic events. The irregularities in the plan configuration provide significant issues for building seismic design. One example of an irregularity is the re-entrant corners found in L-shaped structures, which can lead to early collapse by causing stress concentration from abrupt changes in stiffness and torsional response amplification. More than ever, a thorough investigation into the relationship between the issue of ground motion parameters (GMPs) and Damage is required because of the complex way that L-shaped buildings respond to earthquakes. The current study examines the relationship between a large number of commonly used GMPs and the associated damage for three-, six-, nine-, and twelve-story 3D buildings—that is, low-, mid, and high-rise structures—with asymmetric L-shaped plan layouts. The system of lateral load resistance that was used was Buckling Restrained Brace Frames (BRBFs). To assess a building's seismic performance, 15 bidirectional earthquake ground motions were applied using Nonlinear Time History Analysis (NTHA) for incident angles of 0°, 45°, 135°, 225°, and 315°. The structural response is reported in terms of the average and maximum inter-story drift as well as the total Park-Ang damage index. The relationship between GMPs and structural damage was then investigated using Pearson's correlation coefficient. The results indicate that the highest link with damage measurements is found for 3- and 6-story structures when looking at the spectral acceleration at the fundamental period, Sa(T1). However, PGD and SMV exhibit a stronger correlation than other GMPs for structures with nine and twelve stories. Additionally, Classification and Regression Trees (CART) is a decision tree algorithm used for predictive modeling. In this study suggested using CART (Classification and Regression Trees) algorithms to estimate the link between GMPs and Damage Indices. The findings demonstrate the ability of CART algorithms to extract the rules and correlations governing earthquake damage.