Group , Poster #053, Earthquake Engineering Implementation Interface (EEII)

Impacts of CyberShake on Risk Assessments for Distributed Infrastructure Systems

Yajie Lee, Christine Goulet, ZhengHui Hu, Kevin R. Milner, Scott Callaghan, & Ronald T. Eguchi
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Poster Presentation

2021 SCEC Annual Meeting, Poster #053, SCEC Contribution #11438 VIEW PDF
In characterizing the system-level seismic risk of a spatially-distributed infrastructure network, empirical ground motion models (GMMs) are typically used to quantify the spatially correlated ground motion hazard. One current weakness of such empirical GMMs is that they are typically developed from global datasets representing “average” source, path attenuation, and site response characteristics of global earthquakes, and are associated with large variability reflecting a variety of crustal structures and conditions. Such differences in median and variability for a specific region can lead to poorly centered and wider than necessary distributions of the risk metrics.

The Sout...
hern California Earthquake Center CyberShake platform was designed as the first probabilistic seismic hazard analysis (PSHA) model using physics-based earthquake simulations. Provided that the simulations have been properly validated, they should, in theory, capture the source, path, and site effects of a specific region. For this work, we build on a recent comprehensive probabilistic seismic risk analysis (PSRA) study of the underground water pipeline network for the City of Los Angeles, where the system-level performance (measured by the expected number of pipeline repairs, repair cost, and repair time) was established as a function of exceedance probability based on a large set of earthquake simulations using the NGA-West2 GMMs. By repeating this study using the events and ground motions from the CyberShake simulations, we are exploring the impact of this region-specific PSHA models on seismic risk assessments of distributed infrastructure. Our results show that using the same set of earthquake ruptures and pipe fragility models, CyberShake simulations result in significantly lower estimates of system-level risks than those computed from empirical GMMs at relatively long return periods. More specifically, at a 500-year return period, the expected number of pipeline repairs computed from CyberShake is about 26% lower than that from empirical GMMs. At a 2,500-year return period, the reduction reaches 41%. While a reduction was expected, more work is needed to fully understand the sources of these differences.
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