Seismic risk analysis of urban non-engineered buildings: application to an informal settlement in Mérida, Venezuela

Castillo, Ana; Almansa, Francisco López; Pujades, L. G.

doi:10.1007/s11069-011-9805-9

Cited by 17 publications

(10 citation statements)

References 20 publications

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“…3and (5):The presented formulation is very effective and clear for the risk analysis of residential building stocks in a town or a wide region, as testified by many applications of the method after its proposal (e.g. Castillo et al 2011;Cherif et al 2017;Cosenza et al 2018;Lestuzzi et al 2016;Maio et al 2018;Neves et al 2012). Buildings should be grouped into homogeneous sub-types, on the base of the available information.…”

Section: The Macroseismic Methodsmentioning

confidence: 92%

The heuristic vulnerability model: fragility curves for masonry buildings

Lagomarsino

Cattari

Ottonelli

2021

Bull Earthquake Eng

115

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In the framework of seismic risk analyses at large scale, among the available methods for the vulnerability assessment the empirical and expert elicitation based ones still represent one of most widely used options. In fact, despite some drawbacks, they benefit of a direct correlation to the actual seismic behaviour of buildings and they are easy to handle also on huge stocks of buildings. Within this context, the paper illustrates a macroseismic vulnerability model for unreinforced masonry existing buildings that starts from the original proposal of Lagomarsino and Giovinazzi (Bull Earthquake Eng 4(4):445–463, 2006) and has further developed in recent years. The method may be classified as heuristic, in the sense that: (a) it is based on the expertise that is implicit in the European Macroseismic Scale (EMS98), with fuzzy assumptions on the binomial damage distribution; (b) it is calibrated on the observed damage in Italy, available in the database Da.D.O. developed by the Italian Department of Civil Protection (DPC). This approach guarantees a fairly well fitting with actual damage but, at the same time, ensures physically consistent results for both low and high values of the seismic intensity (for which observed data are incomplete or lacking). Moreover, the method provides a coherent distribution between the different damage levels. The valuable data in Da.D.O. allowed significant improvements of the method than its original version. The model has been recently applied in the context of ReLUIS project, funded by the DPC to support the development of Italian Risk Maps. To this aim, the vulnerability model has been applied for deriving fragility curves. This step requires to introduce a correlation law between the Macroseismic Intensity (adopted for the calibration of the model from a wide set of real damage data) and the Peak Ground Acceleration (at present, one of most used instrumental intensity measures); this conversion further increases the potential of the macroseismic method. As presented in the paper, the first applications of the model have produced plausible and consistent results at national scale, both in terms of damage scenarios and total risk (economic loss, consequences to people).

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Section: The Macroseismic Methodsmentioning

confidence: 92%

The heuristic vulnerability model: fragility curves for masonry buildings

Lagomarsino

Cattari

Ottonelli

2021

Bull Earthquake Eng

115

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“…This last method has been applied to assess the seismic risk of important cities as Nice, Bitola, Catania, Barcelona, Thessaloniki, etc. (Brgm, 2004;Milutinovic et al, 2004;Spence & Brun, 2006;Kappos et al, 2008;Castillo et al, 2011;Pitiliakis et al, 2006Athmani et al, 2015;Guardiola-Víllora & Basset-Salom, 2015;Ruiz et al, 2015;Lestuzzi et al, 2016;Cherif et al, 2016;Faccioli et al, 2004;ICC/CIMNE, 2004;Kostov et al, 2004.…”

Section: Vulnerability Index Methods (Vim) To Assess Seismic Risk Scenmentioning

confidence: 99%

A probabilistic approach for seismic risk assessment based on vulnerability functions. Application to Barcelona

Aguilar-Meléndez

Pujades

Barbat

et al. 2018

Bull Earthquake Eng

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Nowadays, different risks are frequently assessed to take actions to increase the resilience in cities. The present work is mainly related to the probabilistic assessment of seismic risk of buildings in urban areas. Particularly, we described the main characteristics of the VIM_P which is considered as the probabilistic version of the Vulnerability Index Method (VIM). The VIM_P requires essential information to compute seismic risk of buildings in urban areas: a) results of seismic hazard of the site where the studied buildings are located (frequency of exceedance vs macroseismic intensities), and; b) basic data of the structure of the studied buildings to classify each building into a structural typology. The seismic vulnerability computed in the VIM_P for each building is represented by probability density functions beta type, which describe the probability distribution of a vulnerability index. In the VIM_P the seismic risk of buildings is computed through the convolution of the seismic hazard and the seismic vulnerability, considering a semi-empirical damage function. The seismic risk computed is expressed in terms of annual frequencies of exceedance of damage grades. Additionally, to show the applicability of the VIM_P, we assessed the seismic risk of 69982 dwelling buildings of Bara)

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“…The material of a building is an important determinant its physical vulnerability to damage by a flood or earthquake. Table 1 highlights four commonly used building materials in developing countries or informal urbanized areas (i.e., earthen‐structures, wood frames, bamboo, and masonry), the first three of which are commonly used in rural areas of less‐developed countries (Castillo et al., 2011). The use of soil makes the buildings very prone to both flood (Siddique & Schwarz, 2012) and earthquake damages (Holliday et al., 2012).…”

Section: Asynergies Of Building‐level Drr Measuresmentioning

confidence: 99%

The Asynergies of Structural Disaster Risk Reduction Measures: Comparing Floods and Earthquakes

et al. 2021

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Traditionally, building-level risk reduction measures aim to address the risk of a single hazard type, for instance, through building codes (Cutter et al., 2015; Daniell, 2015; Shreve & Kelman, 2014). However, many countries face the risk of multiple disasters (Cutter et al., 2015; De Ruiter et al., 2020). Floods and earthquakes are often the hazard types with the highest economic damages, especially in developing countries (Zorn, 2018), and their damages are likely to continue to increase in the future (Bilham, 2009; Cutter et al., 2015; Winsemius et al., 2016). The increase in the damages in the future is due to both a projected increase in the frequency of (climate-driven) hazards (in the case of floods), and also due to increasing exposure in vulnerable areas (Balica et al., 2015). This is expected to continue in the future, with projections estimating that the world's population will have doubled between 1950 and 2050, which requires the construction of an additional 1 billion housing units (Bilham, 2009). Moreover, social inequalities cause developing countries and the poor to suffer disproportionally from the impacts of natural hazards (

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Seismic risk analysis of urban non-engineered buildings: application to an informal settlement in Mérida, Venezuela

Cited by 17 publications

References 20 publications

The heuristic vulnerability model: fragility curves for masonry buildings

The heuristic vulnerability model: fragility curves for masonry buildings

A probabilistic approach for seismic risk assessment based on vulnerability functions. Application to Barcelona

The Asynergies of Structural Disaster Risk Reduction Measures: Comparing Floods and Earthquakes

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