Fully probabilistic seismic displacement analysis of spatially distributed slopes using spatially correlated vector intensity measures

Abstract

SUMMARY Earthquake‐induced slope displacement is an important parameter for safety evaluation and earthquake design of slope systems. Traditional probabilistic seismic hazard analysis usually focuses on evaluating slope displacement at a particular location, and it is not suitable for spatially distributed slopes over a large region. This study proposes a computationally efficient framework for fully probabilistic seismic displacement analysis of spatially distributed slope systems using spatially correlated vector intensity measures (IMs). First, a spatial cross‐correlation model for three key ground motion IMs, that is, peak ground acceleration (PGA), Arias intensity, and peak ground velocity, is developed using 2686 ground motion recordings from 11 recent earthquakes. To reduce the computational cost, Monte Carlo simulation and data reduction techniques are utilized to generate spatially correlated random fields for the vector IMs. The slope displacement hazards over the region are further quantified using empirical predictive equations. Finally, an illustrative example is presented to highlight the importance of the spatial correlation and the advantage of using spatially correlated vector IMs in seismic hazard analysis of spatially distributed slopes. Copyright © 2013 John Wiley & Sons, Ltd.

Ground‐Motion Prediction Models for Arias Intensity and Cumulative Absolute Velocity for Japanese Earthquakes Considering Single‐Station Sigma and Within‐Event Spatial Correlation

“…Moreover, they can be used to estimate I A and CAV values simultaneously at multiple sites for a given earthquake scenario (Foulser-Piggott and Stafford, 2012;Du and Wang, 2013a). The latter extension is important to assess earthquake hazard and risk of spatially distributed infrastructure systems (Du and Wang, 2013b). Japan is situated in a highly active seismic region influenced by complex interaction of tectonic plates.…”

Geotechnical Engineering Slope Monitoring Based on Internet of Things

“…Du and Wang [5] explored the Newmark displacement model and applied it for analyzing the probabilistic seismic slope displacement hazard. Lin and others [6] focused on the Zigbee-based Internet of Things (IoTs) in 3D terrains.…”

A procedure to select ground-motion time histories for deterministic seismic hazard analysis from the Next Generation Attenuation (NGA) database

“…Various subsets of the database have been used to develop GMPE models for various ground-motion intensities in earthquake engineering (e.g., Du and Wang, 2013;Foulser-Piggott and Stafford, 2012). Figure 5 shows the moment magnitude-rupture distance distribution of the ground motions in the NGA database.…”

“…The DGML has the broad capability to search for ground-motion time histories in the library database on the basis of response spectral shape, characteristics of the recordings in terms of earthquake magnitude and type of faulting distance, site characteristics, duration, and presence of velocity pulses in nearfault time histories. These ground-motion intensity measures have been found to be important in liquefaction and seismic assessment of a variety of geotechnical systems (Du and Wang, 2014;Wang, 2015a, b, 2017;Wang and Wei, 2016;Wang, 2015, 2016;Zhang and Wang, 2016). The DGML Search Engine window is shown in Fig.…”