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A simplified vulnerability model for the extensive liquefaction risk assessment of buildings.

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Title: A simplified vulnerability model for the extensive liquefaction risk assessment of buildings.
Authors: Paolella, Luca1 (AUTHOR) luca.paolella@unicas.it, Spacagna, Rose Line1 (AUTHOR), Chiaro, Gabriele2 (AUTHOR), Modoni, Giuseppe1 (AUTHOR)
Source: Bulletin of Earthquake Engineering. Aug2021, Vol. 19 Issue 10, p3933-3961. 29p.
Subject Terms: *Sustainable urban development, *Risk assessment, *Urbanization, *Epistemic uncertainty, *Prediction models
Geographic Terms: Christchurch (N.Z.)
Abstract: The quantitative assessment of natural risks offers a rational strategy to protect communities, undertake cost effective mitigation and plan the organic and sustainable development of urban systems. For cascade events such as earthquake-induced liquefaction, assessment implies to characterize and reconstruct the areal distribution of seismic hazard, subsoil susceptibility, physical vulnerability, economic and social relevance of structures and to combine all factors in a unitary predictive model. Considering that aleatory variability and epistemic uncertainty affect the characteristic variables and their mutual correlation, it is also necessary to quantify their influence on the prediction. Within this framework, a vulnerability model is proposed to comprehensively assess the physical damage of buildings in an urban system. A chain method is formulated combining calculation schemes recently introduced in the literature with ad hoc numerical analyses. The effectiveness of the method is tested comparing prediction with the effects observed in the city of Christchurch during the 22nd February 2011 earthquake. The unprecedented documentation available after this earthquake enables to validate different components of the model and disclose the importance of possible disregarded factors. A geostatistical methodology is proposed throughout the paper to process data, quantify and govern the different uncertainty factors. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 151400684
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: A simplified vulnerability model for the extensive liquefaction risk assessment of buildings.
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  Data: <searchLink fieldCode="AR" term="%22Paolella%2C+Luca%22">Paolella, Luca</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> luca.paolella@unicas.it</i><br /><searchLink fieldCode="AR" term="%22Spacagna%2C+Rose+Line%22">Spacagna, Rose Line</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chiaro%2C+Gabriele%22">Chiaro, Gabriele</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Modoni%2C+Giuseppe%22">Modoni, Giuseppe</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Bulletin+of+Earthquake+Engineering%22">Bulletin of Earthquake Engineering</searchLink>. Aug2021, Vol. 19 Issue 10, p3933-3961. 29p.
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  Data: *<searchLink fieldCode="DE" term="%22Sustainable+urban+development%22">Sustainable urban development</searchLink><br />*<searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br />*<searchLink fieldCode="DE" term="%22Urbanization%22">Urbanization</searchLink><br />*<searchLink fieldCode="DE" term="%22Epistemic+uncertainty%22">Epistemic uncertainty</searchLink><br />*<searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Christchurch+%28N%2EZ%2E%29%22">Christchurch (N.Z.)</searchLink>
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  Label: Abstract
  Group: Ab
  Data: The quantitative assessment of natural risks offers a rational strategy to protect communities, undertake cost effective mitigation and plan the organic and sustainable development of urban systems. For cascade events such as earthquake-induced liquefaction, assessment implies to characterize and reconstruct the areal distribution of seismic hazard, subsoil susceptibility, physical vulnerability, economic and social relevance of structures and to combine all factors in a unitary predictive model. Considering that aleatory variability and epistemic uncertainty affect the characteristic variables and their mutual correlation, it is also necessary to quantify their influence on the prediction. Within this framework, a vulnerability model is proposed to comprehensively assess the physical damage of buildings in an urban system. A chain method is formulated combining calculation schemes recently introduced in the literature with ad hoc numerical analyses. The effectiveness of the method is tested comparing prediction with the effects observed in the city of Christchurch during the 22nd February 2011 earthquake. The unprecedented documentation available after this earthquake enables to validate different components of the model and disclose the importance of possible disregarded factors. A geostatistical methodology is proposed throughout the paper to process data, quantify and govern the different uncertainty factors. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=151400684
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      – Type: doi
        Value: 10.1007/s10518-020-00911-2
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      – Code: eng
        Text: English
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        PageCount: 29
        StartPage: 3933
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      – SubjectFull: Sustainable urban development
        Type: general
      – SubjectFull: Risk assessment
        Type: general
      – SubjectFull: Urbanization
        Type: general
      – SubjectFull: Epistemic uncertainty
        Type: general
      – SubjectFull: Prediction models
        Type: general
      – SubjectFull: Christchurch (N.Z.)
        Type: general
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      – TitleFull: A simplified vulnerability model for the extensive liquefaction risk assessment of buildings.
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            NameFull: Spacagna, Rose Line
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            NameFull: Chiaro, Gabriele
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            NameFull: Modoni, Giuseppe
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            – D: 01
              M: 08
              Text: Aug2021
              Type: published
              Y: 2021
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              Value: 19
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              Value: 10
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