Report GIRS 2022-11: Uncertainty and Sensitivity Analysis of Ground-Motions Simulation at Un-Instrumented Sites Using Gaussian Process Regression

By: Aidin Tamhidi, Nicolas M. Kuehn, and Yousef Bozorgnia
DOI: 10.34948/N39G6W

Abstract: Earthquake ground motion time series plays a critical role in the performance assessment of the structures, especially when nonlinear response history analysis for a specific structural system is required. The number of currently available recording instruments is sparse. Therefore, it is necessary to have a reliable methodology to construct the ground motion time series at the desired target un-instrumented sites. Using the Gaussian Process Regression (GPR), we recently presented an approach for generating ground motion time series at target sites where there are no available recording sensors.