Abstract

SummarySeismic structural responses recorded in instrumented buildings during an earthquake are used to provide insights into the demands placed on neighboring, noninstrumented buildings, using a framework to interpolate structural response demands across buildings. The interbuilding interpolation model relies on the spatial and structural correlations of responses in coregionally located buildings subjected to a seismic event. A dataset of response demands for a portfolio of reinforced concrete moment frame buildings is generated by performing nonlinear response history analyses on structural models using ground motions recorded from historical scenario earthquakes. The dataset is used to characterize the correlation between seismic demands across different buildings. Semivariograms are used to model spatial and structural correlations and then incorporated into a kriging algorithm, which forms the basis of the interpolation models. The effect of several model and dataset attributes and assumptions, for example, using intensity‐measure‐based versus engineering demand parameter‐based semivariograms, and size of training dataset relative to portfolio, on the overall performance are evaluated along with the limitations of the proposed model.

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