scholarly journals Spatial Correlation of EArthquake Ground Motion Based on Dense Array Records.

1995 ◽  
pp. 185-197
Author(s):  
Hirokazu Nakamura ◽  
Fumio Yamazaki
Keyword(s):  
Spatial Correlation ◽  
Ground Motion ◽  
Earthquake Ground Motion ◽  
Dense Array

On the design of a dense array to extract rotational components of earthquake ground motion

2016 ◽  
Vol 15 (3) ◽  
pp. 827-860 ◽  
Author(s):  
Dhiman Basu ◽  
Andrew S. Whittaker ◽  
Michael C. Constantinou
Keyword(s):  
Ground Motion ◽  
Earthquake Ground Motion ◽  
Dense Array ◽  
Rotational Components

scholarly journals Spatial correlation of broadband earthquake ground motion in Norcia (Central Italy) from physics-based simulations

2021 ◽  
Author(s):  
Erika Schiappapietra ◽  
Chiara Smerzini
Keyword(s):  
Spatial Correlation ◽  
Ground Motion ◽  
Near Field ◽  
Geometric Mean ◽  
Central Italy ◽  
Earthquake Ground Motion ◽  
Physical Parameters ◽  
Spatial Correlations ◽  
Ground Motion Scenarios ◽  
The Impact

AbstractThis 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.

scholarly journals Assessment of the uncertainty in spatial-correlation models for earthquake ground motion due to station layout and derivation method

2021 ◽  
Author(s):  
Erika Schiappapietra ◽  
John Douglas
Keyword(s):  
Maximum Likelihood ◽  
Least Squares ◽  
Spatial Correlation ◽  
Ground Motion ◽  
Weighted Least Squares ◽  
Correlation Structure ◽  
Estimation Methods ◽  
Lower Percentage ◽  
Earthquake Ground Motion ◽  
Spatial Correlation Structure

AbstractThe evaluation of the aggregate risks to spatially distributed infrastructures and portfolios of buildings requires quantification of the estimated shaking over a region. To characterize the spatial dependency of ground motion intensity measures (e.g. peak ground acceleration), a common geostatistical tool is the semivariogram. Over the past decades, different fitting approaches have been proposed in the geostatistics literature to fit semivariograms and thus characterize the correlation structure. A theoretically optimal approach has not yet been identified, as it depends on the number of observations and configuration layout. In this article, we investigate estimation methods based on the likelihood function, which, in contrast to classical least-squares methods, straightforwardly define the correlation without needing further steps, such as computing the experimental semivariogram. Our outcomes suggest that maximum-likelihood based approaches may outperform least-squares methods. Indeed, the former provides correlation estimates, that do not depend on the bin size, unlike ordinary and weighted least-squares regressions. In addition, maximum-likelihood methods lead to lower percentage errors and dispersion, independently of both the number of stations and their layout as well as of the underlying spatial correlation structure. Finally, we propose some guidelines to account for spatial correlation uncertainty within seismic hazard and risk assessments. The consideration of such dispersion in regional assessments could lead to more realistic estimations of both the ground motion and corresponding losses.

Network analysis of earthquake ground motion spatial correlation: A case study with the san jacinto seismic nodal array

2021 ◽  
Author(s):  
Yixiao Sheng ◽  
Qingkai Kong ◽  
Gregory C Beroza
Keyword(s):  
Spatial Correlation ◽  
Ground Motion ◽  
Strong Motion ◽  
Earthquake Ground Motion ◽  
Graph Analytics ◽  
Motion Data ◽  
Large N ◽  
Aftershock Sequences ◽  
Weak Constraints

Summary The spatial correlation of earthquake ground motion intensity can be measured from strong motion data; however, the data used in past studies is sparsely sampled in space, and only the inter-station distance was considered as a correlation variable. These limitations mean that we have only weak constraints on the true correlation structure of ground motion and that potentially important aspects of spatial correlation are unconstrained. In this study, we combine a large-N seismic array and graph analytics to explore this issue at a local scale using small local and regional earthquakes. Our result suggests site conditions, and how they interact with the incident seismic wavefield, strongly condition the spatial correlation of ground motion. Future progress in characterizing ground motion spatial variability will require dense wavefield measurements, either through nodal deployments, or perhaps distributed acoustic sensing (DAS) measurements, of seismic wavefields. Aftershock sequences of major earthquakes would provide particularly data-rich targets of opportunity.

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