Peak ground acceleration and other ground motion intensity measures at liquefaction field case history sites
Dataset Award Winner

About the Webinar

The state of practice for assessing liquefaction triggering relies on semi-empirical models that use the peak ground acceleration (PGA) at the ground surface and the earthquake magnitude (M) to represent the seismic demand leading to liquefaction or lack thereof. PGAs at liquefaction case history sites from past earthquakes were estimated using various methods, including taking the value from the closest station. These methods might fail to account for differences in the wave paths between the liquefaction site and the station, as well as site effects.

This webinar discusses a DesignSafe dataset of ground motion intensity measures (IMs) computed at liquefaction case history sites based on a consistent approach that addresses the limitations of legacy PGAs. The framework used in this study computes IMs at liquefaction sites from the Next Generation Liquefaction database using Kriging interpolation and spatial correlation models developed using Bayesian inference. Ground motion models and data from the Next Generation Attenuation projects, and other technical literature are used to facilitate these calculations.

The DesignSafe dataset consists of ground motion intensity measures (PGA, peak ground velocity, Arias intensity, and cumulative absolute velocity) along with the spatial correlation models used for the IM computation, and gmKriger, a Python- based tool that can be used to compute ground motion intensity measures at any sites of interest not currently on NGL. The dataset and an example application will be presented. The observed discrepancies between the legacy and newly estimated PGAs at liquefaction case history sites will also be discussed.

Presenter

Renmin Pretell is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Nevada, Reno (UNR). Renmin earned his Ph.D. and M.S. from the University of California Davis. Before UNR, Renmin was a postdoctoral scholar with the Garrick Institute for the Risk Sciences at the University of California, Los Angeles, and has also worked as a consulting engineer with Golder Associates at the Lima and Denver offices. Renmin’s research areas aim to advance the performance assessment of geotechnical systems and infrastructure by integrating data, numerical simulations, and analytics. His research interests include seismic site response and ground motions, soil spatial variability and subsurface uncertainty, mine tailings, and soil liquefaction.