Exploring structural sustainability of tall buildings subject to seismic loads

This research explores the interplay between architectural form and tall building response to seismic loads using advanced computational methods and artificial intelligence-driven strategies. The main objective of the investigation is to optimize the design process, emphasizing cost reduction, structural efficiency, and carbon footprint while exploring various building forms. Understanding building performance is in fact crucial for cost reduction, as structural elements represent a significant percentage of the total construction expense. The research stems from a simplified seismic simulation approach during the form-finding stage, to explore diverse building forms and guide the choices in the early design phase. A significant gap in the field is claimed to be the absence of parametric seismic tools for the proposed activity. To bridge this gap, a unified workflow is here proposed by connecting architectural software with seismic simulation tools based on the OpenSees software. Additionally, the lack of a comprehensive tall buildingspecific seismic dataset is a critical issue; to speed up the numerical simulations, a surrogate modeling approach is employed. Specifically, the study investigates parameters influencing the architectural form of tall buildings with outer diagrids, including tapered, twisted, and curvilinear morphing from base to the top. The dynamic response to the vertical static loads and lateral seismic excitations is assessed under different ground motion scenarios and a dataset of 1000 models is selected to establish the surrogate predictive model. The dataset comprises time-histories of (inter-story) displacements and forces with a focus on critical structural components. Using a NN surrogate modeling algorithm, this research elucidates the intricate relationships between architectural choices and structural behavior, offering valuable guidance to design professionals while preserving their creative freedom.