Data on lifeline system service restoration is seldom exploited for the calibration of performance prediction models or for response comparisons across systems and events. This study explores utility restoration curves after the 2010 Chilean earthquake through a time series method to quantify coupling strengths across lifeline systems. When consistent with field information, cross-correlations from restoration curves without significant lag times quantify operational interdependence, whereas those with significant lags reveal logistical interdependence. Synthesized coupling strengths are also proposed to incorporate cross-correlations and lag times at once. In the Chilean earthquake, coupling across fixed and mobile phones was the strongest per region followed by coupling within and across telecommunication and power systems in adjacent regions. Unapparent couplings were also revealed among telecommunication and power systems with water networks. The proposed methodology can steer new protocols for post-disaster data collection, including anecdotal information to evaluate causality, and inform infrastructure interdependence effect prediction models.
Get full access to this article
View all access options for this article.
References
1.
AdachiT., and EllingwoodB., 2008. Serviceability of earthquake-damaged water systems: Effects of electrical power availability and power backup systems on system vulnerability, Reliability Engineering and System Safety93, 78–88.
2.
AranedaJ. C., RudnickH., MocarquerS., and MiquelP., 2010. Lessons from the 2010 Chilean earthquake and its impact on electric supply, Proceedings of the 2010 International Conference on Power Systems Technology (Powercon 2010), Hangzhou, China, 24–28 October 2010.
3.
BalducelliC., BolognaS., Di PietroA., and VicoloG., 2005. Analysing interdependencies of critical infrastructures using agent discrete event simulation. Int. J. of Emerg. Management2, 306–318.
4.
BarrientosS., 2010. Terremoto Cauquenes 27 Febrero 2010, Informe Técnico Actualizado a Mayo 27 de 2010, Servicio Sismológico, Departamento de Geofísica, Universidad de Chile, http://www.sismologia.cl/informes/INFORME_TECNICO.pdf (accessed June 2010).
5.
BarkerK., and HaimesY., 2009. Assessing uncertainty in extreme events: Applications to risk-based decision making in interdependent infrastructure sectors, Rel. Eng. and Syst. Saf.94, 819–829.
6.
BonneauA., and O'RourkeT. D., 2009. Water Supply Performance During Earthquakes and Extreme Events, Report No. MCEER-03 0009, MCEER, University at Buffalo, Buffalo, NY.
7.
BrownT., BeyelerW., and BartonD., 2004. Assessing infrastructure interdependencies: The challenge of risk analysis for complex adaptive systems, Int. J. of Crit. Infrast.1, 108–117.
8.
ChangS., McDanielsT., and BeaubienC., 2009. Societal impacts of infrastructure failure interdependencies: building an empirical knowledge based, Proc. of the 2009 TCLEE Conference, Oakland, CA, 28 June–1 July 2009, 693–702.
9.
Dueñas-OsorioL., CraigJ. I., and GoodnoB. J., 2007a. Seismic response of critical interdependent networks, Earthquake Engineering and Structural Dynamics36, 285–306.
10.
Dueñas-OsorioL., CraigJ. I., GoodnoB. J., and BostromA., 2007b. Interdependent response of networked systems, Journal of Infrastructure Systems13, 185–194.
HaimesY. Y., and JiangP., 2001. Leontief-Based Model of Risk in Complex Interconnected Infrastructures, ASCE Journal of Infrastructure Systems7, 1–12.
13.
HaimesY. Y., HorowitzB. M., LambertJ. H., SantosJ. R., LianC., and CrowtherK. G., 2005. Inoperability input-output model for interdependent infrastructure sectors. I: Theory and methodology, ASCE Journal of Infrastructure Systems11, 67–79.
14.
HernándezI., and Dueñas-OsorioL., 2011. Time sequential response evolution of interdependent lifeline systems, Earthquake Spectra27, 23–43.
15.
Institute for Electrical and Electronics Engineers (IEEE), 2005. IEEE Recommended Practice for Seismic Design of Substations, IEEE Standard 693, IEEE Power Engineering Society.
16.
KimY., SpencerB., ElnashaiA., and SongJ., 2009. Seismic performance assessment of interdependent lifeline systems, International Journal of Engineering under Uncertainty: Hazards, Assessment, and Mitigation1, 173–181.
17.
McDanielsT., ChangS., PetersonK., MikawozJ., and ReedD., 2007. Empirical framework for characterizing infrastructure failure interdependencies, Journal of Infrast. Systems13, 175–184.
18.
MendoncaD., and WallaceW. A., 2006. Impacts of the 2001 World Trade Center attack on New York City critical infrastructures, ASCE Journal of Infrastructure Systems12, 260–270.
19.
MinX., and Dueñas-OsorioL., 2010. Design of interdependent interfaces for lifeline systems using response surface inverse reliability methods, Proceedings of the 9th U.S. National and 10th Canadian Conference on Earthquake Engineering, Toronto, Canada, 25–29 July 2010.
20.
O'RourkeT., 2007. Critical infrastructure, interdependencies and resilience, The Bridge37, 22–29.
21.
OuyangM., and Dueñas-OsorioL., 2011. An approach to design interface topologies across interdependent urban infrastructure systems, Reliability Eng. and Syst. Safety96, 1462–1473.
22.
OuyangM., HongL., ZijunM., Ming-HuiY., and FeiQ., 2009. A methodological approach to analyze vulnerability of interdependent infrastructures, Sim. Mod. Pract. and Theory17, 817–828.
23.
ParkJ., NojimaN., and ReedD., 2006. Nisqually earthquake electric utility analysis, Earthquake Spectra22, 491–509.
24.
ReedD., KapurK., and ChristieR. D., 2009. Methodology for assessing the resilience of networked infrastructure, IEEE Systems Journal3, 174–180.
25.
RinaldiS., PeerenboomJ., and KellyT., 2001. Identifying, understanding, and analyzing critical infrastructures interdependencies, IEEE Control Systems Magazine21, 11–25.
26.
RokneddinK., GhoshJ., Dueñas–OsorioL., and PadgettJ. E., 2011. Bridge retrofit prioritization for aging transportation networks subject to seismic hazards, Structure and Infrastructure Engineering, doi: 10.1080/15732479.2011.654230.
27.
RosatoV., TiriticcoF., IssacharofL., De PorcellinisS., and SetolaR., 2008. Modeling interdependent infrastructures using interacting dynamical models, Int. J. of Crit. Inf.4, 63–79.
28.
RueggJ., RudloffA., VignyC., MadariagaR., de ChabalierJ., CamposJ., KauselE., BarrientosS., and DimitrovD., 2009. Interseismic strain accumulation measured by GPS in the seismic gap between Constitución and Concepción in Chile, Phys. of the Earth and Plan. Int.175, 78–85.
29.
SantosJ. R., and HaimesY. Y., 2004. Modeling the demand reduction input-output (I-O) inoperability due to terrorism of interconnected infrastructures, Risk Analysis24, 1437–1451.
30.
SatumtiraG., and Dueñas-OsorioL., 2010. Synthesis of modeling and simulation methods on critical infrastructure interdependencies research, in Sustainable Infrastructure Systems: Simulation, Imaging, and Intelligent Engineering, GopalakrishnanK., and PeetaS. (Eds.), Springer, New York, 300 pp.
31.
ShumwayR. H., and StofferD. S., 2006. Time Series Analysis and Its Applications, Springer, New York, 596 pp.
32.
SvendsenN., and WolthusenS., 2007. Connectivity models of interdependency in mixed-type critical infrastructure networks, Information Security Technical Report12, 44–55.
Universidad de Chile, 2010. Informe de últimos sismos sensibles, Servicio Sismológico, Departamento de Geofísica, Universidad de Chile, http://www.sismologia. (accessed June 2010).
U.S. Department of Homeland Security (DHS), 2003. The National Strategy for the Physical Protection of Critical Infrastructures and Key Assets, Government Printing Office, Washington D.C.
WangY., 2006. Seismic Performance Evaluation of Water Supply Systems, Ph.D. Thesis, Cornell University.
39.
WuJ., and Dueñas-OsorioL., 2012. Calibration and validation of a seismic damage propagation model for interdependent infrastructure systems, Earthquake Spectra, in press.
