Developing Fragility Surfaces for More Accurate Seismic Vulnerability Assessment of Masonry Buildings

Abstract eng:
Usual methods for the vulnerability assessment of buildings often result in fragility curves, with respect to one intensity-measure parameter like PGA or spectral displacement. However, the seismic loading is very complex and describing it with one parameter may result in neglecting other significant characteristics of the ground motion [1]. Thus, this study proposes a methodology to develop fragility surfaces, which express the probability of damage with respect to more than one parameter, in order to better account for uncertainties related to the hazard description. The proposed methodology is applied to a model of a two-story unreinforced masonry building (real structure tested on a shaking table by [2]) and the following steps are carried out: • modeling the structure with TREMURI code [3] and static pushover analysis; • developing a set of models with an aleatory distribution of mechanical properties; • based on Latin hypercube sampling, performing hundreds of dynamic analyses (using real and synthetic accelerograms) and assessing the damage level from each analysis; • studying the ground-motion parameters: clustering methods and correlation analyses help to select the appropriate couple of variables to use in the fragility surfaces; • applying the kernel estimation of density in order to get a non-parametrical distribution of damage probability and interpolation into fragility surfaces; The proposed framework permits us to choose a couple of ground-motion parameters that are well correlated to the dynamic response of the studied building and, in the same time, are less inter-correlated. The obtained uncorrelated intensity-measures are then used to build unbiased two-variables fragility functions, based on the couple of parameters (PGD and PGA). A comparison between the one-parameter fragility curve and ”slices” of the fragility surface shows that the use of a second ground-motion parameter delivers a clearer definition of the vulnerability: the different ”slices” can be seen as confidence intervals that can be of great help to public planners, especially in the case of very low probabilities for instance (i.e., extreme events). 1

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