Structural robustness is associated with several definitions depending on context. In the field of structural engineering, the Eurocodes define structural robustness as “the ability of a structure to withstand events like fire, explosions, impact or the consequences of human error, without being damaged to an extent disproportionate to the original cause”. Such a definition clearly involves concepts of local and global failures. This PhD work proposes a methodology to quantify structural robustness in a probabilistic way and to assess the impact of local failures on global failures. The main objective of this PhD is to quantify the gap between local and global failures by introducing several robustness indices proposed for undamaged and damaged structures. To qualify and quantify the relationships between the performance of the different structural components and the overall structural performance, it is necessary to introduce a system-level analysis which simultaneously considers concepts of local failure modes and global failure events. An inner approach is introduced to determine significant failure sequences and to characterize stochastically dominant failure paths identified by using branch-and-bound, β-unzipping, and mixed β-unzipping with bounding methods. These methods enable to determine significant failure paths with reasonable computational times. In particular, the path with the largest probability of occurrence is considered as the reference failure path. An outer approach is also proposed which identifies global failure without using an event-tree search (and, consequently, without analyzing the order in the failure sequence). This concept characterizes an overall and simultaneous failure of different components without determining the chronology in the failure event. In both cases, the goal is to provide a general and widely applicable framework for qualifying and quantifying the robustness level of new and existing structures through the introduction of methodologies and indices
