Analyzing the effect of anisotropic spatial correlations of earthquake intensity measures on the result of seismic risk and resilience assessment of the portfolio of buildings and infrastructure systems

2021 ◽  
Author(s):  
Morteza Abbasnejadfard ◽  
Morteza Bastami ◽  
Afshin Fallah ◽  
Alireza Garakaninezhad
Keyword(s):  
Seismic Risk ◽  
Risk And Resilience ◽  
Spatial Correlations ◽  
Earthquake Intensity ◽  
Intensity Measures ◽  
Infrastructure Systems ◽  
Resilience Assessment

scholarly journals A PERFORMANCE-BASED COASTAL ENGINEERING FRAMEWORK

2020 ◽  
pp. 16
Author(s):  
Catalina Gonzalez-Duenas ◽  
Jamie E. Padgett
Keyword(s):  
Coastal Engineering ◽  
Coastal Communities ◽  
Time Varying ◽  
Risk And Resilience ◽  
Probabilistic Framework ◽  
Coastal Structures ◽  
Coastal Regions ◽  
Infrastructure Systems ◽  
Inform Decision Making ◽  
Resilience Assessment

Coastal regions are exposed to both chronic and punctuated hazards, such as sea level rise and hurricane events, that can jeopardize entire coastal communities. Therefore, to effectively assess the risk and resilience of coastal communities subjected to multi-hazard environments, evaluation of the capacity of individual structures and infrastructure systems to withstand the different time-varying demands imposed in coastal settings is of paramount importance. This study proposes a comprehensive probabilistic framework for the design, risk and resilience assessment of coastal structures. The methodology also provides useful tools to inform decision-making, facilitate recovery efforts and improve resource allocation.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/8SI3Dw30yes

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 ROAD NETWORK ANALYSIS FOR RISK AND RESILIENCE ASSESSMENT FRAMEWORK OF ROAD INFRASTRUCTURE SYSTEMS

2020 ◽  
Author(s):  
SILVIA IENTILE ◽  
FRANZSIKA SCHMIDT ◽  
CHRISTOPHE CHEVALIER ◽  
ANDRE ORCESI ◽  
LUCAS ADELAIDE ◽  
...  
Keyword(s):  
Network Analysis ◽  
Road Network ◽  
Risk And Resilience ◽  
Assessment Framework ◽  
Road Infrastructure ◽  
Infrastructure Systems ◽  
Resilience Assessment

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.

SEISMIC RISK AND RESILIENCE ASSESSMENT OF INDUSTRIAL FACILITIES: CASE STUDY ON A BLACK CARBON PLANT

2020 ◽  
Author(s):  
George Karagiannakis
Keyword(s):  
Seismic Risk ◽  
Numerical Models ◽  
Fragility Curves ◽  
Human Life ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Risk And Resilience ◽  
Industrial Plants ◽  
Plant Equipment

This paper deals with state of the art risk and resilience calculations for industrial plants. Resilience is a top priority issue on the agenda of societies due to climate change and the all-time demand for human life safety and financial robustness. Industrial plants are highly complex systems containing a considerable number of equipment such as steel storage tanks, pipe rack-piping systems, and other installations. Loss Of Containment (LOC) scenarios triggered by past earthquakes due to failure on critical components were followed by severe repercussions on the community, long recovery times and great economic losses. Hence, facility planners and emergency managers should be aware of possible seismic damages and should have already established recovery plans to maximize the resilience and minimize the losses. Seismic risk assessment is the first step of resilience calculations, as it establishes possible damage scenarios. In order to have an accurate risk analysis, the plant equipment vulnerability must be assessed; this is made feasible either from fragility databases in the literature that refer to customized equipment or through numerical calculations. Two different approaches to fragility assessment will be discussed in this paper: (i) code-based Fragility Curves (FCs); and (ii) fragility curves based on numerical models. A carbon black process plant is used as a case study in order to display the influence of various fragility curve realizations taking their effects on risk and resilience calculations into account. Additionally, a new way of representing the total resilience of industrial installations is proposed. More precisely, all possible scenarios will be endowed with their weighted recovery curves (according to their probability of occurrence) and summed together. The result is a concise graph that can help stakeholders to identify critical plant equipment and make decisions on seismic mitigation strategies for plant safety and efficiency. Finally, possible mitigation strategies, like structural health monitoring and metamaterial-based seismic shields are addressed, in order to show how future developments may enhance plant resilience. The work presented hereafter represents a highly condensed application of the research done during the XP-RESILIENCE project, while more detailed information is available on the project website https://r.unitn.it/en/dicam/xp-resilience.

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