A probabilistic framework for Bayesian inference combined with extreme values of Gaussian processes is proposed to assess the maximum of the response of an uncertain structure instrumented with sensors and subject to a stochastic load. The framework is applied to the analysis of the inter-story drift of a multi-story shear-type building under seismic hazard using measurements collected by accelerometers. A cascade of two dynamic systems is proposed to model the stochastic ground motion and the response of the structure. We present an approximate analytical solution to estimate the distribution of the maximum response, and verify the accuracy and limitations of this solution against simulation results. Finally, robustness of the proposed framework to system uncertainties, including uncertainties in the structural characteristics, ground characteristics, and input motion parameters, is investigated.

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two dynamic systems sensors stochastic load bayesian inference measurements multistory sheartype building uncertain structure approximate analytical solution seismic hazard probabilistic framework cascade the structural characteristics ground characteristics and input motion extreme values of gaussian processes uncertainties

Matteo Pozzi,Iris Tien, Armen Der Kiureghian,.Probabilistic framework for assessing maximum structural response based on sensor measurements. 61 (0),43-56.

Matteo Pozzi,Iris Tien, Armen Der Kiureghian,"Probabilistic framework for assessing maximum structural response based on sensor measurements" 61

Matteo Pozzi,Iris Tien, Armen Der Kiureghian,"Probabilistic framework for assessing maximum structural response based on sensor measurements"