Assessment of the lognormality assumption of seismic fragility curves using non-parametric representations

B Sudret (1, 2) , C Mai (2) , K Konakli (2)

1 GdR MASCOT-NUM - Méthodes d'Analyse Stochastique des Codes et Traitements Numériques
2 Chair of Risk, Safety and Uncertainty Quantification [ETH Zurich]

Fragility curves are commonly used in civil engineering to estimate the vulnerability of structures to earthquakes. The probability of failure associated with a prescribed criterion (e.g. the maximal interstorey drift ratio exceeding a prescribed threshold) is represented as a function of the intensity of the earthquake ground motion (e.g. peak ground acceleration or spectral acceleration). The classical approach consists in assuming a lognormal shape of the fragility curves. In this paper, we introduce two non-parametric approaches to establish the fragility curves without making any assumption, namely the binned Monte Carlo simulation approach and kernel density estimation. As an illustration, we compute the fragility curves of a 3-storey steel structure, accounting for the nonlinear behavior of the system. The curves obtained with the proposed approaches are compared with each other and with those obtained using the classical lognormal assumption. It is shown that the lognormal curves differ significantly from their non-parametric counterparts

Mots clés: earthquake engineering; fragility curves; lognormal assumption; non-parametric approach; kernel density estimation; epistemic uncertainty

Domaines: Génie civil

B Sudret, C Mai, K Konakli. Assessment of the lognormality assumption of seismic fragility curves using non-parametric representations . 2017. ⟨hal-01432508⟩