An approach is developed to build multivariate probabilistic seismic demand models (PSDMs) of multicomponent structures based on the coupling of multiple‐stripe analysis and Gaussian mixture models. The proposed methodology is eminently flexible in terms of adopted assumptions, and a classic highway bridge in Eastern Canada is used to present an application of the new approach and to investigate its impact on seismic fragility analysis. Traditional PSDM methods employ lognormal distribution and linear correlation between pairs of components to fit the seismic response data, which may lead to poor statistical modeling. Using ground motion records rigorously selected for the investigated site, data are generated via response history analysis, and appropriate statistical tests are then performed to show that these hypotheses are not always valid on the response data of the case‐study bridge. The clustering feature of the proposed methodology allows the construction of a multivariate PSDM with refined fitting to the correlated response data, introducing low bias into the fragility functions and mean annual frequency of violating damage states, which are crucial features for decision making in the context of performance‐based seismic engineering.

Rubber-based seismic isolation has been demonstrated to be one of the most effective measures to protect structural elements from damage during earthquakes and a viable option to retrofit existing structures with poor seismic detailing. The main constituent of these isolation units is rubber, a material that is subject to stiffening when exposed to low air temperatures. In the case of isolated highway bridges, thermal stiffening might reduce the efficiency of isolators, transferring higher forces to the substructure. Assessment of the seismic response of retrofitted structures using rubber isolators in cold regions is thus necessary. Accordingly, in this study, the effect of low temperatures on the seismic performance of a highway bridge retrofitted with natural rubber (NR) isolators is quantified using a probabilistic framework based on fragility surfaces. From the component- and system-level surfaces, it is revealed that the effects of cold temperatures on highway bridges retrofitted with elastomeric isolators may be negligible, depending on the configuration of lateral restraining structures. However, when isolators are able to perform their function without impediment, their thermal stiffening might be significantly detrimental to the bridge’s substructure, mainly affecting bent columns.