The Global Earthquake Model Physical Vulnerability Database

Yepes-Estrada, Catalina; Silva, Vítor; Rossetto, Tiziana; D’Ayala, Dina; Ιωάννου, Ιωάννα; Meslem, Abdelghani; Crowley, Helen

doi:10.1193/011816eqs015dp

Cited by 77 publications

(44 citation statements)

References 31 publications

(49 reference statements)

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“…Vulnerability curves are generally empirically derived using loss data, usually collected through insurance claims or governmental reports. A database of fragility and vulnerability functions can be found in the OpenQuake platform (Yepes-Estrada et al, 2016;Martins and Silva, 2018). We used these vulnerability functions to directly model fatalities and repair costs, where the loss ratio for the former would be the ratio of fatalities to exposed population, and for the latter the ratio would be that of repair cost to cost of replacement for a given building typology.…”

Section: Building Fragility and Vulnerability Modelsmentioning

confidence: 99%

Contrasting seismic risk for Santiago, Chile, from near-field and distant earthquake sources

Hussain

Elliott

Silva

et al. 2020

Nat. Hazards Earth Syst. Sci.

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Abstract. More than half of all the people in the world now live in dense urban centres. The rapid expansion of cities, particularly in low-income nations, has enabled the economic and social development of millions of people. However, many of these cities are located near active tectonic faults that have not produced an earthquake in recent memory, raising the risk of losing hard-earned progress through a devastating earthquake. In this paper we explore the possible impact that earthquakes can have on the city of Santiago in Chile from various potential near-field and distant earthquake sources. We use high-resolution stereo satellite imagery and imagery-derived digital elevation models to accurately map the trace of the San Ramón Fault, a recently recognised active fault located along the eastern margins of the city. We use scenario-based seismic-risk analysis to compare and contrast the estimated damage and losses to the city from several potential earthquake sources and one past event, comprising (i) rupture of the San Ramón Fault, (ii) a hypothesised buried shallow fault beneath the centre of the city, (iii) a deep intra-slab fault, and (iv) the 2010 Mw 8.8 Maule earthquake. We find that there is a strong magnitude–distance trade-off in terms of damage and losses to the city, with smaller magnitude earthquakes in the magnitude range of 6–7.5 on more local faults producing 9 to 17 times more damage to the city and estimated fatalities compared to the great magnitude 8+ earthquakes located offshore in the subduction zone. Our calculations for this part of Chile show that unreinforced-masonry structures are the most vulnerable to these types of earthquake shaking. We identify particularly vulnerable districts, such as Ñuñoa, Santiago, and Providencia, where targeted retrofitting campaigns would be most effective at reducing potential economic and human losses. Due to the potency of near-field earthquake sources demonstrated here, our work highlights the importance of also identifying and considering proximal minor active faults for cities in seismic zones globally in addition to the more major and distant large fault zones that are typically focussed on in the assessment of hazard.

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Section: Building Fragility and Vulnerability Modelsmentioning

confidence: 99%

Contrasting seismic risk for Santiago, Chile, from near-field and distant earthquake sources

Hussain

Elliott

Silva

et al. 2020

Nat. Hazards Earth Syst. Sci.

Self Cite

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“…Controlling the level of damage in a structure consists primarily in controlling its maximum response. Damage indices establish analytical relationships between the maximum and/or cumulative response of structural components and the level of damage they exhibit [38,[187][188][189][190][191]. A performance-based numerical methodology is possible if, through the use of damage indices, limits can be established to the maximum and cumulative response of the structure, as a function of the desired performance of the building for the different levels of the design ground motion.…”

Section: Damage Indexmentioning

confidence: 99%

Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects

et al. 2019

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A methodology aiming to predict the vulnerability of masonry structures under seismic action is presented herein. Masonry structures, among which many are cultural heritage assets, present high vulnerability under earthquake. Reliable simulations of their response to seismic stresses are exceedingly difficult because of the complexity of the structural system and the anisotropic and brittle behavior of the masonry materials. Furthermore, the majority of the parameters involved in the problem such as the masonry material mechanical characteristics and earthquake loading characteristics have a stochastic-probabilistic nature. Within this framework, a detailed analytical methodological approach for assessing the seismic vulnerability of masonry historical and monumental structures is presented, taking into account the probabilistic nature of the input parameters by means of analytically determining fragility curves. The emerged methodology is presented in detail through application on theoretical and built cultural heritage real masonry structures. leading to a final approval (or rejection) of the decisions already taken for repair or strengthening of the existing structure. Step 8: Explanatory ReportThe last step, as a result of the proposed methodology, includes the detailed "Explanatory Report", where all the collected information, the diagnosis, including the safety evaluation, and any decision to intervene should be fully detailed. This document is essential for eventual future analyses and interventions' measures in the structure. Computational and Mathematical AspectsIn this section, the most basic analytical constitutive laws and numerical models required for the successful implementation of the proposed methodology are presented in detail. In particular, the finite element model for the macro-modeling of masonry structures, the failure criteria, the damage indices, the performance levels and the mathematical background of fragility curves are presented.

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“…Fragility functions can be derived empirically, through expert elicitation or analytically using theory and numerical models. A damage to loss model describes the relationship between the probable damage state and corresponding monetary loss for an asset (e.g., Yepes et al, 2016). Vulnerability functions estimate loss directlythey describe the amount of damage expected due to a given level of hazard intensity (e.g.…”

Section: Vulnerability Schemamentioning

confidence: 99%

Data schemas for multiple hazards, exposure and vulnerability

Murnane

Allegri

Bushi³

et al. 2019

DPM

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Purpose Using risk-related data often require a significant amount of upfront work to collect, extract and transform data. In addition, the lack of a consistent data structure hinders the development of tools that can be used with more than one set of data. The purpose of this paper is to report on an effort to solve these problems through the development of extensible, internally consistent schemas for risk-related data. Design/methodology/approach The consortia coordinated their efforts so the hazard, exposure and vulnerability schemas are compatible. Hazard data can be provided as either event footprints or stochastic catalogs. Exposure classes include buildings, infrastructure, agriculture, livestock, forestry and socio-economic data. The vulnerability component includes fragility and vulnerability functions and indicators for physical and social vulnerability. The schemas also provide the ability to define uncertainties and allow the scoring of vulnerability data for relevance and quality. Findings As a proof of concept, the schemas were populated with data for Tanzania and with exposure data for several other countries. Research limitations/implications The data schema and data exploration tool are open source and, if widely accepted, could become widely used by practitioners. Practical implications A single set of hazard, exposure and vulnerability schemas will not fit all purposes. Tools will be needed to transform the data into other formats. Originality/value This paper describes extensible, internally consistent, multi-hazard, exposure and vulnerability schemas that can be used to store disaster risk-related data and a data exploration tool that promotes data discovery and use.

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The Global Earthquake Model Physical Vulnerability Database

Cited by 77 publications

References 31 publications

Contrasting seismic risk for Santiago, Chile, from near-field and distant earthquake sources

Contrasting seismic risk for Santiago, Chile, from near-field and distant earthquake sources

Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects

Data schemas for multiple hazards, exposure and vulnerability

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