City Research Online

Abstract

Robustness is an important factor in determining structures’ ability to withstand accidental extreme events. However, assessment of structural safety typically does not take probabilistic factors into account, which results in disregarding uncertainties even when extreme conditions are considered. The are limited studies in the literature, highlighting the need for fragility risk assessment of the impact of inter-module connections (IMCs) and building height of steel modular building systems (MBSs) subjected to progressive collapse scenario.
The purpose of this study is to investigate the robustness of steel modular building systems (MBSs) under progressive collapse scenarios that vary in connection type and building height. A nonlinear static pushdown analysis was carried out on five, ten, and fifteen-story MBSs with bolt and post-tensioned rod IMCs, focusing on column removal during the analysis using OpenSees software. Results showed that taller structures are more robust due to their increased redundancy while they exhibit greater resistance to collapse than lower structures. Fragility analysis can be utilised to predict the probability of progressive collapse in case of local damage. With the derived fragility functions, the probability of progressive collapse is quantified for different IMCs and building heights. By optimising connection types and building configurations, the results provide new insights into designing safer modular buildings.

Publication Type:	Article
Additional Information:	This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher Keywords:	Steel modular building systems; Robustness; Fragility; Progressive collapse; Pushdown analysis; Probabilistic demand model
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) T Technology > TH Building construction
Departments:	School of Science & Technology School of Science & Technology > Engineering
SWORD Depositor:	Symplectic Administrator

Export

Downloads