Non-linear dynamic analyses (NDAs) are widely used in engineering practice to evaluate the seismic performance of geotechnical structures affected by liquefaction or cyclic softening. The quality of results from an NDA study depends on several technical and nontechnical factors. Validation, wherein a numerical prediction is compared to its physical counterpart, can assess the ability of an NDA to capture the various metrics of the response and potentially provide guidance toward improving the prediction. This study investigates select methodologies and validation metrics commonly used in signal processing problems to assess their effectiveness in capturing discrepancies between experimental and simulation results for a specific response of interest. Three simple problems are initially evaluated to analyze the metrics' capabilities and identify necessary modifications. Then, the metrics are applied to nine sets of experimental and simulation time series, focusing on one response of interest (pore water pressure). It is found that cross-correlation successfully captures the lag in the initiation of liquefaction triggering, while Russell's error metric captures magnitude and phase discrepancies.
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Mivehchi et al. (2024) studied this question.
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