Inelastic Response of High-Rise Buildings under Strong Winds: Accuracy of Reduced-Order Building Model and Influence of Biaxial Response Interaction

This study examined the accuracy of a reduced-order building model approach for inelastic response analysis of tall buildings under simultaneous actions of both alongwind and crosswind loadings. The reduced-order model was established following the modal pushover analysis procedure. The inelastic building response was represented by fundamental modes in principal directions. The hysteretic relationships of generalized restoring forces and displacements were determined by static modal pushover analysis using nonlinear finite element model with distributed plasticity. These relations were then represented by a biaxial hysteresis model, which leads to state-space equations of the building motion with a reduced-order building model that can be solved by response history analysis or by statistical linearization approach. A comprehensive analysis of response statistics of a 60-story building, including time-varying mean, standard deviation, kurtosis, and peak factors at different wind speeds was carried out using the reduced-order building model and computationally more demanding finite element model. The results demonstrate the accuracy of the reduced-order building model. The statistical linearization approach based on Gaussian response assumption can also offer quite accurate estimations, although it can be further improved by considering the non-Gaussian probability distribution of response caused by yielding. The interaction of inelastic alongwind and crosswind responses was addressed. The challenges faced in the estimation of time-varying mean component of inelastic response were also highlighted.

Automated summary

This study examined the accuracy of a reduced-order building model approach for inelastic response analysis of tall buildings under simultaneous actions of both alongwind and crosswind loadings. The results demonstrate the accuracy of the reduced-order building model and highlight the challenges faced in the estimation of time-varying mean component of inelastic response.