Abstract
This paper investigates the spatial correlation of response spectral accelerations from a set of broadband physics-based ground motion simulations generated for the Norcia (Central Italy) area by means of the SPEED software. We produce several ground-motion scenarios by varying either the slip distribution or the hypocentral location as well as the magnitude to systematically explore the impact of such physical parameters on spatial correlations. We extend our analysis to other ground-motion components (vertical, fault-parallel, fault-normal) in addition to the more classic geometric mean to highlight possible ground-motion directionality and therefore identify specific spatial correlation features. Our analyses provide useful insights on the role of slip heterogeneities as well as the relative position between hypocentre and slip asperities on the spatial correlation. Indeed, we found a significant variability in terms of both range and sill among the considered case studies, suggesting that the spatial correlation is not only period-dependent, but also scenario-dependent. Finally, our results reveal that the isotropy assumption may represent an oversimplification especially in the near-field and thus it may be unsuitable for assessing the seismic risk of spatially-distributed infrastructures and portfolios of buildings.
Highlights
Standard tools for Probabilistic Seismic Hazard Assessment (PSHA) estimate the ground motion due to an earthquake by means of Ground Motion Models (GMMs), which provide the median and the associated aleatory variability of ground motion Intensity Measures (IMs) as a function of source, path and site parameters for a given site
We compute experimental semivariograms using the data from both simulations and observations and compare them to assess the capability of 3D Physics-Based ground motion Simulations (3D PBSs) and ANN2BB to generate spatially correlated ground motion fields accounting for the actual correlation structure
34 out of 36 location selected in the numerical model have a constant Vs30 equal to 1700 m/s, whereas the Engineering Strong Motion database (ESM) stations feature different Vs30 with an average of about 650 m/s (Fig. 8d); most of the simulated data are located on homogeneous hard rock that undeniably makes the ground motion more correlated
Summary
Standard tools for Probabilistic Seismic Hazard Assessment (PSHA) estimate the ground motion due to an earthquake by means of Ground Motion Models (GMMs), which provide the median and the associated aleatory variability of ground motion Intensity Measures (IMs) as a function of source, path and site parameters for a given site. Schiappapietra and Douglas (2020) provide a thorough literature review, critically exploring the main facets of spatial correlation that need to be addressed Among these aspects, they reported dependence on: (1) the estimation approach; (2) the fitting method; (3) the earthquake magnitude (Mw); (4) the vibration period; (5) local site-effects; and (6) ground motion prediction models. 3D PBSs embody physical and sufficiently accurate models of the seismic source, path and local-site effects to provide region-specific earthquake ground motion predictions These estimates are, reliable only in the low-frequency spectrum (up to 1–1.5 Hz) due to the current limitations in: (1) computational capabilities and (2) detailed knowledge of the geological medium that would enable modelling the propagation of short wavelengths. Its main advantage lies on its capability to generate realistic broadband ground motion waveforms by means of a novel approach based on Artificial Neural Networks (Paolucci et al 2018)
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