scholarly journals Investigating the spatial correlations in univariate random fields of peak ground velocity and peak ground displacement considering anisotropy

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Morteza Abbasnejadfard ◽  
Morteza Bastami ◽  
Afshin Fallah
Keyword(s):  
Random Fields ◽  
Peak Ground Velocity ◽  
Sufficient Evidence ◽  
Spatial Correlations ◽  
Ground Displacement ◽  
Earthquake Intensity ◽  
Intensity Measures ◽  
Correlation Models ◽  
Local Soil ◽  
Spatially Distributed

AbstractThe results of seismic risk assessment of spatially distributed infrastructure systems are significantly influenced by spatial correlation of earthquake intensity measures (IM). The assumption of isotropy is a basis for most of the existing correlation models of earthquake IMs. In this study, the isotropy assumption of intra-event residuals of peak ground velocity (PGV) and peak ground displacement (PGD) is investigated by implementing a nonparametric statistical test. Using recorded IMs of 9 earthquakes, it is concluded that there is not sufficient evidence to support the assumption of isotropy in general, and the set of intra-event residuals of PGV and PGD should be considered as the realization of anisotropic random fields. Investigations show that the anisotropy properties of intra-event residuals of PGV and PGD are related to anisotropy properties of local soil characteristics indicated by average shear wave velocity of soil profile from the 30 m depth to the surface (Vs30). Finally, predictive models are proposed based on obtained results in order to simulate the correlated univariate random fields of PGV and PGD considering anisotropy.

Investigation of anisotropic spatial correlations of intra-event residuals of multiple earthquake intensity measures using latent dimensions method

2020 ◽  
Vol 222 (2) ◽  
pp. 1449-1469
Author(s):  
Morteza Abbasnejadfard ◽  
Morteza Bastami ◽  
Afshin Fallah
Keyword(s):  
Anisotropy Ratio ◽  
Covariance Model ◽  
Spatial Correlations ◽  
Earthquake Intensity ◽  
Intensity Measures ◽  
Covariance Functions ◽  
Cross Covariance ◽  
Spatially Distributed ◽  
Covariance Models ◽  
Anisotropy Direction

SUMMARY Considering spatial correlation of multiple earthquake intensity measures (IMs) is of particular importance in loss assessment of spatially distributed assets. This subject has been investigated in previous studies under the assumption of isotropy. Considering the fact that the assumption of isotropy is not valid in general, the present study employs a non-separable covariance model based on latent dimensions method to investigate anisotropic properties of spatial correlations and cross-correlations of intra-event residuals of multiple earthquake IMs. This method leads to the generation of valid covariance matrix in order to model anisotropic spatially distributed multivariate random fields. Two sets of IMs are considered in this study; the first set consists of peak ground intensity values (acceleration, velocity, and displacement), and the second set consists of spectral accelerations at three different periods. Data of 10 earthquake events in California and Japan are utilized in this study to estimate parameters of marginal and cross-covariance models. Moreover, parameters of covariance model of regional site condition, which is considered as average shear wave velocity of top 30 m of soil profile (Vs30), are obtained in order to investigate the effect of local sited conditions on spatial correlations of IMs. It is shown that maximum range and anisotropy ratio of covariance models of intra-event residuals of IMs are correlated with those of Vs30 values. Also, it is observed that the anisotropy direction of residuals of IMs is consistent with anisotropy direction of Vs30 values. Finally, predictive models are proposed to obtain marginal and cross-covariance functions for different earthquake IMs considering anisotropy.

scholarly journals A framework for quantifying hydrologic effects of soil structure across scales

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Sara Bonetti ◽  
Zhongwang Wei ◽  
Dani Or
Keyword(s):  
Soil Texture ◽  
Land Surface ◽  
Soil Structure ◽  
Pedotransfer Functions ◽  
Small Scale ◽  
Spatial Correlations ◽  
Surface Parameterization ◽  
Exchange Processes ◽  
Local Soil ◽  
Spatially Distributed

AbstractEarth system models use soil information to parameterize hard-to-measure soil hydraulic properties based on pedotransfer functions. However, current parameterizations rely on sample-scale information which often does not account for biologically-promoted soil structure and heterogeneities in natural landscapes, which may significantly alter infiltration-runoff and other exchange processes at larger scales. Here we propose a systematic framework to incorporate soil structure corrections into pedotransfer functions, informed by remote-sensing vegetation metrics and local soil texture, and use numerical simulations to investigate their effects on spatially distributed and areal averaged infiltration-runoff partitioning. We demonstrate that small scale soil structure features prominently alter the hydrologic response emerging at larger scales and that upscaled parameterizations must consider spatial correlations between vegetation and soil texture. The proposed framework allows the incorporation of hydrological effects of soil structure with appropriate scale considerations into contemporary pedotransfer functions used for land surface parameterization.

Correlations of spectral accelerations in the Chilean subduction zone

2020 ◽  
Vol 36 (2) ◽  
pp. 788-805 ◽  
Author(s):  
Gabriel Candia ◽  
Alan Poulos ◽  
Juan Carlos de la Llera ◽  
Jorge G.F. Crempien ◽  
Jorge Macedo
Keyword(s):  
Subduction Zone ◽  
Subduction Zones ◽  
Peak Ground Velocity ◽  
Data Sets ◽  
Correlation Model ◽  
Crustal Earthquakes ◽  
Correlation Models ◽  
Spatially Distributed ◽  
Soil Site ◽  
Spectral Accelerations

The correlation between spectral accelerations is key in the construction of conditional mean spectra, the computation of vector-valued seismic hazard, and the assessment of seismic risk of spatially distributed systems, among other applications. Spectral correlations are highly dependent on the earthquake database used, and thus, region-specific correlation models have been developed mainly for earthquakes in western United States, Europe, Middle East, and Japan. Correlation models based on global data sets for crustal and subduction zones have also become available, but there is no consensus about their applicability on a specific region. This study proposes a new correlation model for 5% damped spectral accelerations and peak ground velocity in the Chilean subduction zone. The correlations obtained were generally higher than those observed from shallow crustal earthquakes and subduction zones such as Japan and Taiwan. The study provides two illustrative applications of the correlation model: (1) computation of conditional spectra for a firm soil site located in Santiago, Chile and (2) computation of bivariate hazard for spectral accelerations at two structural periods.

scholarly journals Peak Ground Acceleration (PGA) and Peak Ground Velocity (PGV) Analyze for Microzonation of Earthquake Hazard Area: Case Study in West Nusa Tenggara

2021 ◽  
Vol 873 (1) ◽  
pp. 012046
Author(s):  
T Razin ◽  
K Khatimah ◽  
Y Annisa ◽  
A Hamzah ◽  
M F I Massinai
Keyword(s):  
Peak Ground Acceleration ◽  
Earthquake Damage ◽  
Peak Ground Velocity ◽  
Risk Level ◽  
Soil Conditions ◽  
Earthquake Intensity ◽  
Ground Acceleration ◽  
Tectonic Zone ◽  
Local Soil ◽  
Earthquake Data

Abstract The Lombok region is located around a complex tectonic zone with an Indo-Australian oceanic crust transition zone with Australian continental crust in the west and Sundanese arc in the east. This complexity makes some area in West Nusa Tenggara have a high level of earthquake vulnerability and to determine the potential level of seismic damage risk this study was conducted by analyzing Peak Ground Acceleration (PGA) and Peak Ground Velocity (PGV) using earthquake data since 2000 - March 2020 with an intensity more than M4.5. Earthquake data are analyzed using the Yin-Min Yu formula to get the relationship between Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), and earthquake intensity, so areas with risk level of earthquake damage can be mapped as preliminary earthquake mitigation schemes. The results of the study show that the highest PGA value in West Nusa Tenggara is 74.73 gal at the bedrock and when it on the surface, the PGA value can increase due to amplification of local soil conditions. Likewise PGV value about 32.21 gal where this maximum value is located in East Lombok Regency and North Lombok Regency. According to the classification of PGA and PGV values, the study area has a potential high-risk level of earthquake damage.

Correlation of spectral acceleration values of vertical and horizontal ground motion pairs

2020 ◽  
Vol 36 (4) ◽  
pp. 2112-2128
Author(s):  
Mohsen Kohrangi ◽  
Athanasios N Papadopoulos ◽  
Paolo Bazzurro ◽  
Dimitrios Vamvatsikos
Keyword(s):  
Ground Motion ◽  
Peak Ground Acceleration ◽  
Correlation Coefficients ◽  
Peak Ground Velocity ◽  
Coefficient Estimates ◽  
Ground Acceleration ◽  
Intensity Measures ◽  
Correlation Models ◽  
Horizontal Ground Motion ◽  
S Peak

We present correlation coefficient estimates between a number of ground motion intensity measures ( IMs), as measured from the NGA-West2 database, with focus on the correlation of vertical–vertical and vertical–horizontal ground motion components. The IMs considered include spectral accelerations with periods from 0.01 to 10 s, peak ground acceleration, peak ground velocity, and significant duration (for 5%–75% and 5%–95% definitions). To facilitate their use, parametric equations are also fitted to the correlation models. Finally, the dependence of the obtained correlation coefficients to magnitude, distance, and Vs30 is evaluated.

Comparison of Nonlinear Spatial Correlation Models by the Influence of the Data Augmentation to the Classification Risk

2002 ◽  
Vol 7 (1) ◽  
pp. 31-42
Author(s):  
J. Šaltytė ◽  
K. Dučinskas
Keyword(s):  
Spatial Correlation ◽  
Random Fields ◽  
Data Augmentation ◽  
Gaussian Random Fields ◽  
Classification Rule ◽  
Numerical Comparison ◽  
First Order ◽  
Bayesian Risk ◽  
Correlation Models

The Bayesian classification rule used for the classification of the observations of the (second-order) stationary Gaussian random fields with different means and common factorised covariance matrices is investigated. The influence of the observed data augmentation to the Bayesian risk is examined for three different nonlinear widely applicable spatial correlation models. The explicit expression of the Bayesian risk for the classification of augmented data is derived. Numerical comparison of these models by the variability of Bayesian risk in case of the first-order neighbourhood scheme is performed.

scholarly journals The Effects of Earthquake Significant Duration D595 to the Earthquake Intensity Measures and the Inelastic Response of SDOF Reinforced Concrete Structure

2019 ◽  
Vol 280 ◽  
pp. 01005
Author(s):  
Widodo Pawirodikromo
Keyword(s):  
Spectral Response ◽  
Damage Index ◽  
Structural Response ◽  
Strong Relationship ◽  
Seismic Intensity ◽  
Reinforced Concrete Structure ◽  
Earthquake Intensity ◽  
Intensity Measures ◽  
Earthquake Frequency

The concept of seismic intensity measures has long beendiscussed and has been collected by researchers among whom are by [1-6]. However, the effect of earthquake duration on the structural response hasnot received attention from the researcher so it has not been seen in the listof the existing seismic intensity measures. In the spectral response, forexample, it has been accommodated peak value and earthquake frequencycontent but has not accommodated the duration of the earthquake. Theeffect of earthquake duration on a response, damage or collapse capacity ofthe structure has been done by the researchers [7-10]. The spectrallyequivalent approach/control has been used by [9,10]., while the collapsecapacity approach is cursed by [8]. The use of the classification of theearthquake frequency content as independent variables has been suggestedby [7]. In this study, the classification of earthquake frequency (lowfrequency), earthquake duration as the independent variable and peakacceleration control have been used. Single degree of Freedom (SDOF)structures excited by 15-earthquakes with effective durations varyingbetween te = 6.34 to 30.18 s have been used. The results showed that notall seismic intensity measure used had a strong relationship with effectiveduration. The earthquake effective duration has a positive relationship withthe damage index but the relationship is relatively weak

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