Buildings Vulnerability Assessment and Damage Seismic Scenarios at Urban Scale: Application to Chlef City (Algeria)

Boutaraa, Zohra; Negulescu, Caterina; Arab, Ahmed; Sedan, Olivier

doi:10.1007/s12205-018-0961-2

Cited by 21 publications

(10 citation statements)

References 27 publications

(26 reference statements)

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“…The vulnerability model defined in the European macroseismic scale (EMS-98 [11]) serves as the basis for the macroseismic model (LM1) methodology, and it is derived from Giovinazzi and Lagomarsino [93,97] to examine the seismic response of a particular urban area [98]. Buildings are classified into 23 groups by the LM1, on the bases of the structural material and the building type, as is shown in Table 7 [99]. Moreover, each building type can be divided into three subclasses: low-rise, mid-rise, and high-rise.…”

Section: The Risk-ue Projectmentioning

confidence: 99%

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Conventional RVS Methods for Seismic Risk Assessment for Estimating the Current Situation of Existing Buildings: A State-of-the-Art Review

Bektaş

Kegyes-Brassai

2022

Sustainability

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Developments in the field of earthquake engineering over the past few decades have contributed to the development of new methods for evaluating the risk levels in buildings. These research methods are rapid visual screening (RVS), seismic risk indexes, and vulnerability assessments, which have been developed to assess the levels of damage in a building or its structural components. RVS methods have been proposed for the rapid pre- and/or post-earthquake screening of existing large building stock in earthquake-prone areas on the basis of sidewalk surveys. The site seismicity, the soil type, the building type, and the corresponding building characteristic features are to be separately examined, and the vulnerability level of each building can be identified by employing the RVS methods. This study describes, evaluates, and compares the findings of previous investigations that utilized conventional RVS methods within a framework. It also suggests the methods to be used for specific goals and proposes prospective enhancement strategies. Furthermore, the article discusses the time-consuming RVS methods (such as FEMA 154, which requires from 15 to 30 min, while NRCC requires one hour), and provides an overview of the application areas of the methods (pre-earthquake: FEMA 154, NRCC, NZEE, etc.; postearthquake: GNDT, EMS, etc.). This review of the traditional RVS methods offers a comprehensive guide and reference for field practitioners (e.g., engineers, architects), and recommends enhancement techniques (e.g., machine learning, fuzzy logic) for researchers to be used in future improvements.

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Section: The Risk-ue Projectmentioning

confidence: 99%

“…where P β (k) are the discrete probability values for each damage grade shown in Equation (7). The macroseismic model (LM1) of the RISK-UE has been used by Boutaraa et al [99] to assess the buildings of Chlef City in Algeria.…”

Section: The Risk-ue Projectmentioning

confidence: 99%

Conventional RVS Methods for Seismic Risk Assessment for Estimating the Current Situation of Existing Buildings: A State-of-the-Art Review

Bektaş

Kegyes-Brassai

2022

Sustainability

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“…Both of them are well known and are not detailed in this paper. Considering the historical database of intensities (SISFRANCE, BRGM), the field inventory data that we have and the experience acquired on the validation of the simulated damages with observed damages (Douglas et al 2015;Boutaraa et al 2018), we decided to apply RISK-UE methodology LM1 (the one based on relation between the intensity, the vulnerability index and beta damage distribution) for earthquake damage calculation. The decision to use RISK-UE methodology LM1 is also supported by studies made by others teams, for example Lestuzzi et al (2016) that conclude that "There are significant differences in global results between LM1 (empirical method) and LM2 methods (mechanical method).…”

Section: Earthquake and Tsunami Damage Calculationmentioning

confidence: 99%

Adjustability of exposed elements by updating their capacity for resistance after a damaging event: application to an earthquake–tsunami cascade scenario

et al. 2020

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The 2011 Great East Japan earthquake and tsunami remind us once again that these types of cascade event can occur and cause considerable damage. The scientific community realizes the need for rapid theoretical and practical progress on cascade events to provide field teams with the necessary tools and information for action during these types of events. The earthquake damage scenario for Martinique and Guadeloupe islands (French West Indies) has already been performed within the framework of French governmental projects, but these areas, in the vicinity of the French West Indies subduction zone, are also subject to tsunami events. In this study, we propose to perform a combined scenario in which an earthquake is followed by a tsunami, as it could arrive one day, considering the seismic characteristics and potential of such a subduction zone. The vulnerability of the buildings is defined considering local specific information based on several years of field inventories and inspections and is later classified into one of the 36 model building types of HAZUS. The calculation of the damages due to tsunamis follows the HAZUS methodologies. The main novelty of our study is the calculation of damage due to the two phenomena occurring one after the other, not in parallel, as is calculated in the existing literature. Therefore, for the calculation of the damages due to the second event (i.e. the tsunami), the vulnerability characteristics of the initial structure are reduced, considering the damage state of the construction after the first event (i.e. the earthquake). Hence, in our case, this calculation approach allows us to update the number of exposed elements and their changed vulnerabilities considering the damages due to the earthquake, since certain structures are already damaged by the earthquake before the arrival of the tsunami wave. The results coming from our study and our manner of treating the cascading hazards are putting into perspective with the Hazus method for combining damages coming from earthquake and the damages coming from consequently tsunami. The results expressed as the sum of the damages in both most damaged states, Extensive and Complete, are more or less in the same range of values for both studies (our study and HAZUS 2017). However, a trend of having more percentage of complete damages (and hence, less the Extensive damages) with our method than the ones obtained with the Hazus combination can be important information for crisis managing. This is a first result for the French West Indies territory, but anyway, more studies should be carried out in order to check this trend and eventually to confirm and validate this issue for others territories with others bathymetries, vulnerabilities and seismological features.

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“…Erdik (2017) proposed an earthquake risk assessment methodology considering and combining three main factors, such as earthquake hazard, fragility/vulnerability, and inventory of assets exposed to hazard. Boutaraa et al (2018) proposed "RISK-UE" method for the seismic vulnerability assessment at Chlef City (Algeria). Lestuzzi et al (2017) improved the RISK-UE LM2 method for more accurate seismic damage of URM buildings with stiff floors and RC shear wall buildings.…”

Section: Introductionmentioning

confidence: 99%

Seismic Building Damage Prediction From GIS-Based Building Data Using Artificial Intelligence System

Hansapinyo

Latcharote

Limkatanyu

2020

Front. Built Environ.

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The estimation of seismic damage to buildings is complicated due to the many sources of uncertainties. This study aims to develop a new approach using an artificial intelligence system called adaptive neuro-fuzzy inference system (ANFIS) model to predict the damage of buildings at urban scale considering input uncertainties. First, the study performed seismic damage evaluation of buildings utilizing the capacity spectrum method (CSM) to obtain a set of 57,648 training data from a combination of three main parameters, i.e., 6 earthquake magnitudes, 8 structural types, and 1,201 distances. Next, the data was used to develop a practical ANFIS model for the seismic damage prediction. The variables of the fuzzy system are earthquake magnitudes, structural types, and distance between epicenter and building. To validate the applicability of the proposed model, analyses of spatial seismic building damage under five possible earthquakes in Chiang Mai Municipality were performed by using the proposed methodology. From the comparison of the damaged urban area, small discrepancies between the CSM and the ANFIS results could be observed. It should be noted that the proposed ANFIS model can predict the seismic building damage reasonably well compared with the CSM. Using the method proposed herein, it is possible to create damage scenarios for earthquake-prone areas where only a few seismic data are available, such as developing countries.

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Buildings Vulnerability Assessment and Damage Seismic Scenarios at Urban Scale: Application to Chlef City (Algeria)

Cited by 21 publications

References 27 publications

Conventional RVS Methods for Seismic Risk Assessment for Estimating the Current Situation of Existing Buildings: A State-of-the-Art Review

Conventional RVS Methods for Seismic Risk Assessment for Estimating the Current Situation of Existing Buildings: A State-of-the-Art Review

Adjustability of exposed elements by updating their capacity for resistance after a damaging event: application to an earthquake–tsunami cascade scenario

Seismic Building Damage Prediction From GIS-Based Building Data Using Artificial Intelligence System

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