Modelling exposure and vulnerability from post-earthquake survey data with risk-oriented taxonomies: AeDES form, GEM taxonomy and EMS-98 typologies

Nicodemo, Giuseppe; Pittore, Massimiliano; Masi, Angelo; Manfredi, Vincenzo

doi:10.1016/j.ijdrr.2020.101894

Cited by 21 publications

(7 citation statements)

References 15 publications

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“…This harmonization has been addressed by data standards with taxonomic attributes. This is the case for FEMA 154 (2002), the SASPARM 2.0 project (Grigoratos et al 2016), CARTIS (Polese et al 2020); and initiatives for data collection of post-earthquake damage such as AeDES (Baggio et al 2007;Nicodemo et al 2020). Recently, Kechidi et al (2021) presented a comprehensive comparison between census-based (using mapping schemes) and survey-based (inspecting a sample) exposure models for risk assessment.…”

Section: Bottom-up Approach: Individual Building Observationsmentioning

confidence: 99%

Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models

Zapata

Pittore

Cotton

et al. 2022

Bull Earthquake Eng

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In seismic risk assessment, the sources of uncertainty associated with building exposure modelling have not received as much attention as other components related to hazard and vulnerability. Conventional practices such as assuming absolute portfolio compositions (i.e., proportions per building class) from expert-based assumptions over aggregated data crudely disregard the contribution of uncertainty of the exposure upon earthquake loss models. In this work, we introduce the concept that the degree of knowledge of a building stock can be described within a Bayesian probabilistic approach that integrates both expert-based prior distributions and data collection on individual buildings. We investigate the impact of the epistemic uncertainty in the portfolio composition on scenario-based earthquake loss models through an exposure-oriented logic tree arrangement based on synthetic building portfolios. For illustrative purposes, we consider the residential building stock of Valparaíso (Chile) subjected to seismic ground-shaking from one subduction earthquake. We have found that building class reconnaissance, either from prior assumptions by desktop studies with aggregated data (top–down approach), or from building-by-building data collection (bottom–up approach), plays a fundamental role in the statistical modelling of exposure. To model the vulnerability of such a heterogeneous building stock, we require that their associated set of structural fragility functions handle multiple spectral periods. Thereby, we also discuss the relevance and specific uncertainty upon generating either uncorrelated or spatially cross-correlated ground motion fields within this framework. We successively show how various epistemic uncertainties embedded within these probabilistic exposure models are differently propagated throughout the computed direct financial losses. This work calls for further efforts to redesign desktop exposure studies, while also highlighting the importance of exposure data collection with standardized and iterative approaches.

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Section: Bottom-up Approach: Individual Building Observationsmentioning

confidence: 99%

Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models

Zapata

Pittore

Cotton

et al. 2022

Bull Earthquake Eng

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“…Generation of analytical fragility curves In order to identify building classes and typologies (steps 1-2), the knowledge of the attributes mainly affecting seismic vulnerability and its distribution over a building stock are crucial aspects in large-scale vulnerability studies [6,7]. In this context, several sources of information are available in Italy (e.g., ISTAT census data [8], post-earthquake inspections [9], interviewbased surveys [10]), each one characterized by different quality and accuracy of data. According to the 2011 ISTAT census of population and houses [8], the Italian building stock amounts to about 12 million buildings, most of them are masonry structures (more than 7 million) while about 4 million are RC ones.…”

Section: Methodsmentioning

confidence: 99%

Role of Design Level and Infill Arrangement on the Seismic Fragility Curves of Italian Rc Existing Buildings

Masi¹,

Manfredi²,

Nicodemo³

et al. 2021

Proceedings of the 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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Assessing the seismic vulnerability of existing buildings is a fundamental step in order to define mitigation programs in prone earthquake areas. In Italy, in 2019 the National Department of Civil Protection supported an ongoing research project involving its "Center of Competence" on seismic risk, ReLUIS (Network of University Laboratories for Earthquake Engineering), with the cooperation of Eucentre (European Centre for Training and Research in Earthquake Engineering) to update the 2018 version of the National Risk Assessment. In this context, new fragility curves are being derived by using different approaches, whose results will be properly combined. In the paper, the purposely set up methodology for deriving analytical fragility curves through Non-Linear Dynamic Analyses (NLDAs) has been described. Further, results relevant to some Italian Reinforced Concrete (RC) building types have been shortly presented and analyzed, emphasizing the role of some key parameters affecting seismic vulnerability such as design level and infill arrangement.

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“…This is the case of FEMA-154 (FEMA 154, 2002); the SASPARM 2.0 project (Grigoratos et al 2016); CARTIS (e.g. Zuccaro and Cacace 2015;Polese et al 2020); some initiatives for data collection of postearthquake damage such as AeDES (Baggio et al 2007;Nicodemo et al 2020); and focus on historical buildings (e.g. Jiménez, et al 2018).…”

Section: Bottom-up Approach: Individual Building Observationsmentioning

confidence: 99%

Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models

Zapata¹,

Pittore²,

Cotton³

et al. 2021

Preprint

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In seismic risk assessment the sources of uncertainty associated to building exposure modelling have not received as much attention as other components related to hazard and vulnerability. We are introducing that the degree of knowledge of a building portfolio can be described within a Bayesian probabilistic approach to acknowledge the epistemic uncertainty of its composition (i.e. proportions per building class). We are investigating the impact of such uncertainty on earthquake loss models through a novel approach based on an exposure-oriented logic tree arrangement and scenario-based seismic risk simulations. We have found that the building class reconnaissance either from prior assumptions by desktop studies with aggregated data (top-down approach) or from building-by-building data collection (bottom-up approach), plays a fundamental role in statistical modelling of exposure. We successively show that the selection of the basic set of building classes is a major contribution to the uncertainties in the loss estimations given their dependence on specific fragility functions. If the set of fragility functions handle multiple spectral periods, cross-correlated ground motion fields are required for the vulnerability assessment which ultimately control the variability of the losses. When the exposure composition is poorly known due to, for instance, simplifications and assumptions over aggregated data, its absolute contribution to the loss uncertainties has been found to be larger than the one imposed by the spatially distributed cross-correlated ground motion fields. This work invites to redesign desktop exposure studies, while it also highlights the importance of a standardized iterative approach to exposure data collection and modelling.

show abstract

Modelling exposure and vulnerability from post-earthquake survey data with risk-oriented taxonomies: AeDES form, GEM taxonomy and EMS-98 typologies

Cited by 21 publications

References 15 publications

Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models

Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models

Role of Design Level and Infill Arrangement on the Seismic Fragility Curves of Italian Rc Existing Buildings

Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models

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