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Disruption index, DI: an approach for assessing seismic risk in urban systems (theoretical aspects)

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Abstract

Urban systems are characterized by very complex interactions. After an earthquake, a wide variety of services, networks and urban facilities may be unavailable to the public during the system failure and recovery processes, thereby causing disruptions in the basic social needs of the affected area. After a disaster, communities face several challenges. For example, the lack of education may impose population migrations, or malfunctions in the electricity distribution system can produce electrical power outages of varying duration with respect to time and space, which generates consequences in the water distribution system, transportation, communications, etc. A methodology called the Disruption index (DI), based on graph theory, includes these multiple interdependencies. It has been developed to estimate the dysfunction of some fundamental dimensions of urban systems on a broad level, starting with the physical damages directly suffered by the exposed assets, proceeding to the impacts that each node has on the functional performance of the nodes depending on them, until reaching the top node. This paper presents the fundamental theory to support the DI concept. The DI provides the likely impacts and consequences of an earthquake in an urban area to fulfill hazard mitigation and provide civil protection agencies and local and state governments with a new decision-making instrument to reduce or prevent severe and recurrent impacts. The DI concept can also be extended to other natural and man-made disasters and may be used as a tool for optimizing the resources of the system components.

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Notes

  1. The authors also mention dimensions like “criteria”, “objectives” or “concerns”.

  2. Field Missions include the Azores (Oliveira et al. 2012), China (Costa et al. 2010), Italy (Proença and Ferreira 2009), Haiti (Oliveira and Ferreira 2010) and Spain (Ferreira 2011).

  3. A topological order of a directed graph [G] is an ordering of its vertices as \(\hbox {v}_{1}\), \(\hbox {v}_{2}\), ..., \(\hbox {v}_\mathrm{n}\) such that, for every edge e(\(\hbox {v}_\mathrm{i}\), \(\hbox {v}_\mathrm{j})\) starting at vertex \(\hbox {v}_\mathrm{i}\) and ending at vertex \(\hbox {v}_\mathrm{j}\), we have i \(<\)j.

  4. “System 1 operates automatically and quickly, with little or no effort and no sense of voluntary control. System 2 allocates attention to the effortful mental activities that demand it, including complex computations (...)”.

References

  • Andrews JD, Beeson S (2003) Birnbaum’s measure of component importance for noncoherent systems. IEEE Trans Reliab 52(2):213–219

    Article  Google Scholar 

  • Apostolakis GE, Lemon DM (2005) A screening methodology for the identification and ranking of infrastructure vulnerabilities due to terrorism. Risk Anal 25(2):361–376

    Article  Google Scholar 

  • Bana e Costa CA, Beinat E (2005) Model-structuring in public decision-aiding. LSEOR 05(79)

  • Bilham R (2009) The seismic future of cities. Bull Earthq Eng 7:839–887

    Article  Google Scholar 

  • Cardona O (2005) System of indicators for disaster risk management: Instituto de Estudios Ambientales. Universidad Nacional de Colombia, Manizales

    Google Scholar 

  • Carreño ML, Cardona OD, Barbat AH (2007) Urban seismic risk evaluation: a holistic approach. Nat Hazards 40(1):137–172

    Article  Google Scholar 

  • Carreño ML, Cardona OD, Barbat AH (2012) New methodology for urban seismic risk assessment from a holistic perspective. Bull Earthq Eng 10:547–565. doi:10.107/s10518-011-9302-2

    Article  Google Scholar 

  • Costa A, Ferreira MA, Oliveira CS (2010) O grande sismo de Sichuan: impactos e lições para o futuro. In: Proceedings Sísmica 2010–8\(^{o}\) Congresso Nacional de Engenharia Sísmica. Aveiro, Portugal (in portuguese)

  • Davidson RA, Shah HC (1997) An urban earthquake disaster risk index. Stanford University, Stanford, CA

    Google Scholar 

  • Dueñas-Osorio L, Graig JI, Goodno BJ (2007) Seismic response of critical interdependent networks. Earthq Eng Struct Dyn 36:285–306

    Article  Google Scholar 

  • Ferreira MA (2011) Field mission to Lorca, Spain (personal communication)

  • Ferreira, MA (2012) Risco sísmico em sistemas urbanos. Ph.D. Thesis. Instituto Superior Técnico, Universidade Técnica de Lisboa. 295 pp (in portuguese)

  • Kahneman D (2012) Thinking fast and slow. Penguin

  • Keeney R, Raiffa H (1976) Decisions with multiple objectives: preferences and value tradeoffs. Willey, New York

  • Kunreuther H, Novemsky N, Kahneman D (2001) Making low probabilities useful. Risk Uncertain 23(2):103–120

    Google Scholar 

  • Masure P, Lutoff C (2008) Urban system exposure to natural disasters: an integrated approach. In: Oliveira CS, Roca A, Goula X (eds) Assessing and managing earthquake risk. Springer, Berlin, pp 239–260

  • Michaud D, Apostolakis GE (2006) A methodology for ranking the elements of water-supply networks. J Infrastruct Syst 12(4):230–242

    Article  Google Scholar 

  • Mota de Sá F, Ferreira MA, Oliveira CS (2013) Disruption index, DI: a tool for prioritizing (optimizing) mitigating policies (in preparation)

  • Oliveira CS, Ferreira MA (2010) The fragile state of education in Haiti. CELE Exchange. J OECD Centre for Effective Learning Environments. November http://www.oecd.org/document/43/0,3343,en_2649_35961311_46152683_1_1_1_1,00.html

  • Oliveira CS, Ferreira MA (2012) The concept of a disruption index: application to the overall impact of the July 9, 1998 Faial earthquake (Azores islands). Bull Earthq Eng 10:7–25. doi:10.1007/s10518-011-9333-8

  • Patterson SA, Apostolakis GE (2005) Identification of critical locations across multiple infrastructures for terrorist actions. Integrated Approaches to Failure in Complex Networks, University of Glasgow, Paper presented at the Safeguarding National Infrastructures

  • Perrow C (1999) Normal accidents: living with high-risk technologies. Princeton University Press, New Jersey

  • Phillips LD (2006) Decision conferencing: operational research group. Department of Management, London School of Economics and Political Science

  • Proença JM, Ferreira MA (2009) L’Aquila, Italy, earthquake hit educational buildings. CELE Exchange. J OECD Centre for Effective Learning Environments. October http://www.oecd.org/document/30/0,3343,en_2649_35961311_43726110_1_1_1_1,00.html

  • Roy B (1985) Méthodologie multicritère d’aide à la décision. Paris, Economica

  • Scawthorn C (2011) Disaster casualties—accounting for economic impacts and diurnal variation. In: Spence R, So E, Scawthorn C (eds) Human casualties in earthquakes. Progress in modelling and mitigation, vol 29. Springer, Berlin, pp 322

  • UPStrat-MAFA (2012) Urban disaster prevention strategies using macroseismic fields and fault sources (UPStrat-MAFA-EU Project Num. 230301/2011/613486/SUB/A5), DG ECHO Unit A5

  • Ventura CE, García HJ, Martí JM (2010) Understanding interdependencies among critical infrastructures. Paper presented at the 9th U.S. National and 10th Canadian Conference on Earthquake Engineering, Toronto, Ontario, Canada

  • Zio E, Podofillini L (2003) Importance measures of multi-state components in multi-state systems. Int J Reliab Safety Eng 10(3):289–310

    Article  Google Scholar 

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Acknowledgments

The preparation of this paper was supported in part by FCT PhD grants SFRH/BD/29980/2006 (Mónica Amaral Ferreira) and SFRH/BD/71198/2010 (Francisco Mota de Sá) and was co-financed by the EU—Civil Protection Financial Instrument in the framework of the European Project ”Urban disaster Prevention Strategies using MAcroseismic Fields and FAult Sources” (UPStrat-MAFA-Num. 230301/2011/613486/SUB/A5), DG ECHO Unit A5. Special acknowledge to Dr. Gaetano Zonno from INGV, Italy, for all his support and to Prof. Ragnar Sigbjörnsson from University of Iceland, for all support and important suggestions made. We thank Prof. Sancho Oliveira from ISCTE for revising some computational aspects.

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Authors and Affiliations

  1. Department of Civil Engineering, Architecture and Georesources, Instituto Superior Técnico, University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon, Portugal

    M. A. Ferreira, F. Mota de Sá & C. S. Oliveira

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  1. M. A. Ferreira
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  2. F. Mota de Sá
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  3. C. S. Oliveira
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Correspondence to M. A. Ferreira.

Appendix: Description of levels of criteria

Appendix: Description of levels of criteria

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Ferreira, M.A., Mota de Sá, F. & Oliveira, C.S. Disruption index, DI: an approach for assessing seismic risk in urban systems (theoretical aspects). Bull Earthquake Eng 12, 1431–1458 (2014). https://doi.org/10.1007/s10518-013-9578-5

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