Gentile, R; Galasso, C; (2022) Efficient loss analysis through surrogate probabilistic seismic demand models. In: Proceedings of the The 13th International Conference on Structural Safety and Reliability (ICOSSAR 2021). (pp. pp. 1-10). ICOSSAR

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Abstract

This paper discusses a recently-proposed statistical model mapping the parameters controlling the dynamic behaviour of inelastic single-degree-of-freedom (SDoF) systems (i.e. force-displacement capacity curve, hysteretic behaviour) and the parameters of their probabilistic seismic demand model (PSDM, i.e. conditional distribution of an engineering demand parameter given a ground-motion intensity measure). This metamodel allows rapidly deriving fragility curves of equivalent SDoF systems. The model involves Gaussian Process (GP) regressions trained using 10,000 SDoF systems analysed via cloud-based non-linear timehistory analysis (NLTHA) using natural ground motions. A 10-fold cross validation is used to test the GP regressions, predicting the PSDM of both the SDoF database and eight realistic reinforced concrete (RC) frames, benchmarking the results against NLTHA. Error levels are deemed satisfactory for practical applications, especially considering the low required modelling effort and analysis time. Two possible applications of the proposed metamodel are briefly discussed: direct loss-based seismic design and portfolio risk modelling with dynamic representations of exposure and vulnerability modules.

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