Quantification of structural redundancy and robustness

Abstract

Historical collapse events are testament to the inherent dangers of non-robust structures. Designing robust structures is vital to ensure that localised damage events, such as the failure of a single structural element, do not lead to catastrophic disproportionate collapse. While the advent of robustness research can be dated to the collapse of the Ronan Point building in 1968, the quantification of robustness remains an active and important research field. The importance of developing effective robustness assessment methods is emphasized by a number of factors. One issue is the growing problem of inspecting, maintaining and ensuring the safety of ageing infrastructure. Older structures are more likely to be non-redundant and are more susceptible to structural defects. Another factor is the pursuit of greater efficiency and design optimisation, which has eliminated traditional design conservatism and many undocumented factors of safety. As a result, modern buildings may be more vulnerable to unforeseen conditions during their service life. The objective of quantifying robustness highlights the need for a new system-oriented perspective on structural performance to complement traditional component-based design. There is, as of yet, no single framework that incorporates all the essential aspects in an explicit, transparent and quantitative manner leading to a comprehensive outcome in terms of quantification of the structural robustness. This thesis focuses primarily on the quantification of redundancy and robustness, with the view that the capacity of a structure to withstand a damage event is an inherent property of the structure, which can be considered complementary to other commonly discussed structural properties, such as strength and ductility. Hence, a comprehensive unified framework for redundancy quantification is proposed, which builds upon existing strength-based measures. The role of structural uncertainties in the quantification of robustness is investigated, with a focus on the importance of the sequence of events which precede the collapse of a structure. Directly incorporating structural uncertainties into robustness quantification typically requires computationally expensive methods such as Monte Carlo simulations. Moreover, such collapse analyses are susceptible to numerical instabilities, further complicating the simulation of multiple collapse scenarios. To address these issues, a novel incremental elastic analysis method is proposed in this thesis, which analyses the full load-displacement relationship of a structure and additionally, has an inbuilt capacity to incorporate structural variability and thus output a spectrum of possible response outcomes.