A Fully Probabilistic Framework for Spatially Distributed Slope Systems Considering Spatial Cross-correlations of Vector Intensity Measures

Earthquake-induced slope displacement is an important parameter for safety evaluation and earthquake design of slope systems. Traditional probabilistic seismic hazard analysis (PSHA) usually focuses on evaluating slope displacement at a particular location, and it is not suitable for spatially distributed slopes. This study proposes a computational efficient framework for fully probabilistic seismic displacement analysis of spatially distributed slope systems using spatially correlated vector intensity measures. First, a spatial cross-correlation model for three key ground motion intensity measures, i.e., peak ground acceleration (PGA), Arias intensity (Ia) and peak ground velocity (PGV) is developed. Monte Carlo simulation and data reduction techniques are utilized to generate spatially-correlated random fields for the vector intensity measures. 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 intensity measures.

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