Abstract

Critical infrastructure systems are interdependent to ensure normal operations for supporting a national economy and social well-being. In the wake of a disaster, such interdependencies may introduce additional vulnerability and cause cascading failures. Therefore, understanding interdependencies and assessing their impact are essential to mitigate such adverse consequences and to enhance disaster resilience in the long term. There have been various models developed to capture dependencies and interdependencies across infrastructure systems. However, problems of inconsistent usage and a lack of technical guidance hinder practical applications of interdependency models. Therefore, this study presents a new classification of interdependency models based on the following implementation methods: dependency tables, interaction rules, and data-driven approaches. For every class of interdependency model, fundamental assumptions and detailed implementation methods are described, with discussion of appropriate application areas, advantages, and limitations. This study also compares different types of models to facilitate analysts in choosing models based on their needs. Due to the intrinsic complexity of dependencies and interdependencies, there are many challenging modeling issues; this study discusses future research directions to address such challenges.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

No data, models, or code were generated or used during the study.

Acknowledgments

This work is part of the Probabilistic Resilience Assessment of Interdependent Systems (PRAISys) project (www.praisys.org). The support from the National Science Foundation through Grant CMMI-1541177 is gratefully acknowledged. The opinions and conclusions presented in this paper are those of the authors and do not necessarily reflect the views of the sponsoring institution.

References

Almoghathawi, Y., K. Barker, and L. A. Albert. 2019. “Resilience-driven restoration model for interdependent infrastructure networks.” Reliab. Eng. Syst. Saf. 185: 12–23. https://doi.org/10.1016/j.ress.2018.12.006.
Anderson, C. W., J. R. Santos, and Y. Y. Haimes. 2007. “A risk-based input–output methodology for measuring the effects of the August 2003 Northeast blackout.” Econ. Syst. Res. 19 (2): 183–204. https://doi.org/10.1080/09535310701330233.
Applegate, C., and I. Tien. 2019. “Framework for probabilistic vulnerability analysis of interdependent infrastructure systems.” J. Comput. Civ. Eng. 33 (1): 04018058. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000801.
ATC (Applied Technology Council). 1985. Earthquake damage evaluation for California. Redwood City, CA: ATC.
Aung, Z. Z., and K. Watanabe. 2009. “A framework for modeling interdependencies in Japan’s critical infrastructures.” In Proc., Int. Conf. on Critical Infrastructure Protection (ICCIP2009), 243–257. Berlin: Springer.
Barbosa-Filho, H., M. Barthelemy, G. Ghoshal, C. R. James, M. L. T. Louail, R. Menezes, J. J. Ramasco, F. Simini, and M. Tomasini. 2018. “Human mobility: Models and applications.” Phys. Rep. 734: 1–74. https://doi.org/10.1016/j.physrep.2018.01.001.
Barker, K., J. H. Lambert, C. W. Zobel, A. H. Tapia, J. E. Ramirez-Marquez, L. Albert, C. D. Nicholson, and C. Caragea. 2017. “Defining resilience analytics for interdependent cyber-physical-social networks.” Sustainable Resilient Infrastruct. 2 (2): 59–67. https://doi.org/10.1080/23789689.2017.1294859.
Barton, D. C., E. E. Edison, D. A. Schoenwald, R. G. Cox, and R. K. Reinert. 2004. Simulating economic effects of disruptions in the telecommunications infrastructure. Albuquerque, NM: Sandia National Laboratories.
Barton, D. C., E. E. Edison, D. A. Schoenwald, K. L. Stamber, and R. K. Reinert. 2000. Aspen-EE: An agent-based model of infrastructure interdependency. Albuquerque, NM: Sandia National Laboratories.
Basu, D. C., R. Pryor, T. Quint, and T. Arnold. 1996. ASPEN: A microsimulation model of the economy. Albuquerque, NM: Sandia National Laboratories.
Basu, N., R. Pryor, and T. Quint. 1998. “ASPEN: A micosimulation model of the economy.” Comput. Econ. 12 (3): 223–241. https://doi.org/10.1023/A:1008691115079.
Bayram, I. S., G. Michailidis, M. Devetsikiotis, and F. Granelli. 2013. “Electric power allocation in a network of fast charging stations.” IEEE J. Sel. Areas Commun. 31 (7): 1235–1246. https://doi.org/10.1109/JSAC.2013.130707.
BEA (Bureau of Economic Analysis). 2020. “BEA data.” Accessed February 1, 2020. https://www.bea.gov/data.
Beaumont, P. M. 1990. “Supply and demand interaction in integrated econometric and input-output models.” Int. Reg. Sci. Rev. 13 (1–2): 167–181. https://doi.org/10.1177/016001769001300111.
Bigger, J. E., M. G. Willingham, F. Krimgold, and L. Mili. 2009. “Consequences of critical infrastructure interdependencies: Lessons from the 2004 hurricane season in Florida.” Int. J. Crit. Infrastruct. 5 (3): 199–219. https://doi.org/10.1504/IJCIS.2009.024871.
Bocchini, P., and D. M. Frangopol. 2011a. “Generalized bridge network performance analysis with correlation and time-variant reliability.” Struct. Saf. 33 (2): 155–164. https://doi.org/10.1016/j.strusafe.2011.02.002.
Bocchini, P., and D. M. Frangopol. 2011b. “A stochastic computational framework for the joint transportation network fragility analysis and traffic flow distribution under extreme events.” Probab. Eng. Mech. 26 (2): 182–193. https://doi.org/10.1016/j.probengmech.2010.11.007.
Bocchini, P., and D. M. Frangopol. 2012a. “Optimal resilience- and cost-based post-disaster intervention prioritization for bridges along a highway segment.” J. Bridge Eng. 17 (1): 117–129. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000201.
Bocchini, P., and D. M. Frangopol. 2012b. “Restoration of bridge networks after an earthquake: Multi-criteria intervention optimization.” Earthquake Spectra 28 (2): 427–455. https://doi.org/10.1193/1.4000019.
Bocchini, P., D. M. Frangopol, T. Ummenhofer, and T. Zinke. 2014. “Resilience and sustainability of civil infrastructure: Toward a unified approach.” J. Infrastruct. Syst. 20 (2): 04014004. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000177.
Bromley, J., N. A. Jackson, O. J. Clymer, A. M. Giacomello, and F. V. Jensen. 2005. “The use of Hugin to develop Bayesian networks as an aid to integrated water resource planning.” Environ. Modell. Software 20 (2): 231–242. https://doi.org/10.1016/j.envsoft.2003.12.021.
Bruneau, M., S. E. Chang, R. T. Eguchi, G. C. Lee, T. D. O’Rourke, A. M. Reinhorn, M. Shinozuka, K. Tierney, W. A. Wallace, and D. von Winterfeldt. 2003. “A framework to quantitatively assess and enhance the seismic resilience of communities.” Earthquake Spectra 19 (4): 733–752. https://doi.org/10.1193/1.1623497.
Bush, B., L. Dauelsberg, R. Leclaire, D. Powell, S. Deland, and M. Samsa. 2005. Critical infrastructure protection decision support system (CIP/DSS) project overview. Santa Fe, NM: Los Alamos National Laboratory.
Campbell, J. Y., and J. H. Cochrane. 1999. “By force of habit: A consumption-based explanation of aggregate stock market behavior.” J. Pol. Econ. 107 (2): 205–251. https://doi.org/10.1086/250059.
Casalicchio, E., E. Galli, and S. Tucci. 2008. “Modeling and simulation of complex interdependent systems: A federated agent-based approach.” In Critical information infrastructure security, 72–83. Berlin: Springer.
Cavdaroglu, B., E. Hammel, J. E. Mitchell, T. C. Sharkey, and W. A. Wallace. 2013. “Integrating restoration and scheduling decisions for disrupted interdependent infrastructure systems.” Ann. Oper. Res. 203 (1): 279–294. https://doi.org/10.1007/s10479-011-0959-3.
Chambers, R. G. 1984. “Agricultural and financial market interdependence in the short run.” Am. J. Agric. Econ. 66 (1): 12–24. https://doi.org/10.2307/1240611.
Chang, S. E., T. McDaniels, J. Fox, R. Dhariwal, and H. Longstaff. 2014. “Toward disaster-resilient cities: Characterizing resilience of infrastructure systems with expert judgments.” Risk Anal. 34 (3): 416–434. https://doi.org/10.1111/risa.12133.
Chang, S. E., T. L. McDaniels, and D. A. Reed. 2005. “Mitigation of extreme events: Electric power outage and infrastructure failure interactions.” In The economic impacts of terrorist attacks, edited by H. W. Richardson, P. Gordon, and I. J. E. Moore, 70–90. Northampton, MA: Edward Elgar.
Chou, C. C., and S.-M. Tseng. 2010. “Collection and analysis of critical infrastructure interdependency relationships.” J. Comput. Civ. Eng. 24 (6): 539–547. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000059.
Cimellaro, G. P., D. Solari, and M. Bruneau. 2014. “Physical infrastructure interdependency and regional resilience index after the 2011 Tohoku earthquake in Japan.” Earthquake Eng. Struct. Dyn. 43 (12): 1763–1784. https://doi.org/10.1002/eqe.2422.
Coates, G., C. Li, S. Ahilan, N. Wright, and M. Alharbi. 2019. “Agent-based modeling and simulation to assess flood preparedness and recovery of manufacturing small and medium-sized enterprises.” Eng. Appl. Artif. Intell. 78 (Feb): 195–217. https://doi.org/10.1016/j.engappai.2018.11.010.
Codetta-Raiteri, D. 2005. “The conversion of dynamic fault trees to stochastic Petri nets, as a case of graph transformation.” Electron. Notes Theor. Comput. Sci. 127 (2): 45–60. https://doi.org/10.1016/j.entcs.2005.02.005.
Crooks, A. T. 2010. “Constructing and implementing an agent-based model of residential segregation through vector GIS.” Int. J. Geogr. Inf. Sci. 24 (5): 661–675. https://doi.org/10.1080/13658810903569572.
Crowther, K. G., and Y. Y. Haimes. 2005. “Application of the inoperability input–output model (IIM) for systemic risk assessment and management of interdependent infrastructures.” Syst. Eng. 8 (4): 323–341. https://doi.org/10.1002/sys.20037.
Data.gov. 2018. “Open government.” Accessed December 1, 2019. https://www.data.gov/open-gov/.
Di Giorgio, A., and F. Liberati. 2011. “Interdependency modeling and analysis of critical infrastructures based on dynamic Bayesian networks.” In Proc., 19th Mediterranean Conference on Control & Automation (MED). New York: IEEE. https://doi.org/10.1109/MED.2011.5983016.
Dong, S., T. Yu, H. Farahmand, and A. Mostafavi. 2020. “Probabilistic modeling of cascading failure risk in interdependent channel and road networks in urban flooding.” Sustainable Cities Soc. 62 (Nov): 102398. https://doi.org/10.1016/j.scs.2020.102398.
Dudenhoeffer, D. D., M. R. Permann, and M. Manic. 2006a. “CIMS: A framework for infrastructure interdependency modeling and analysis.” In Proc., 2006 Winter Simulation Conf., edited by L. F. Perrone, F. P. Wieland, J. Liu, B. G. Lawson, D. M. Nicol, and R. M. Fujimoto, 478–485. New York: IEEE.
Dudenhoeffer, D. D., M. R. Permann, S. Woolsey, R. Timpany, C. Miller, and M. Manic. 2006b. “Interdependency modeling and emergency response.” In Proc., 2007 Summer Computer Simulation Conf. (SCSC ‘07), 1230–1237. New York: Association for Computing Machinery.
Dueñas-Osorio, L., J. I. Craig, and B. J. Goodno. 2007. “Seismic response of critical interdependent networks.” Earthquake Eng. Struct. Dyn. 36 (2): 285–306. https://doi.org/10.1002/eqe.626.
Dueñas-Osorio, L., and A. Kwasinski. 2012. “Quantification of lifeline system interdependencies after the 27 February 2010 Mw 8.8 offshore Maule, Chile, earthquake.” Supplement, Earthquake Spectra 28 (S1): 581–603. https://doi.org/10.1193/1.4000054.
Dueñas-Osorio, L., and S. M. Vemuru. 2009. “Cascading failures in complex infrastructure systems.” Struct. Saf. 31 (2): 157–167. https://doi.org/10.1016/j.strusafe.2008.06.007.
Elwood, S. K. 2001. “Oil-price shocks: Beyond standard aggregate demand/aggregate supply analysis.” J. Econ. Educ. 32 (4): 381–386. https://doi.org/10.1080/00220480109596116.
Fagiolo, G., A. Moneta, and P. Windrum. 2007. “A critical guide to empirical validation of agent-based models in economics: Methodologies, procedures, and open problems.” Comput. Econ. 30 (3): 195–226. https://doi.org/10.1007/s10614-007-9104-4.
Farmer, J. D., and D. Foley. 2009. “The economy needs agent-based modelling.” Nature 460 (7256): 685–686. https://doi.org/10.1038/460685a.
Forrester, J. 1958. “Industrial dynamics: A major breakthrough for decision makers.” Harv. Bus. Rev. 36 (4): 37–66.
Fortino, G., A. Garro, and W. Russo. 2005. “A discrete-event simulation framework for the validation of agent-based and multi-agent systems.” In Proc., WOA 2005: Dagli Oggetti agli Agenti. 6th AI*IA/TABOO Joint Workshop “From Objects to Agents”: Simulation and Formal Analysis of Complex Systems, 75–84. Bologna, Italy: Pitagora Editrice Bologna.
Franchina, L., M. Carbonelli, L. Gratta, M. Crisci, and D. Perucchini. 2011. “An impact-based approach for the analysis of cascading effects in critical infrastructures.” Int. J. Crit. Infrastruct. 7 (1): 73–90. https://doi.org/10.1504/IJCIS.2011.038958.
Ghaneshvar, R. C. N. 2019. “Machine learning approach to model interdependent network performance.” M.S. thesis, Dept. of Data Science and Analytics, Univ. of Oklahoma.
Gonzalez, A. D., L. Dueñas-Osorio, M. Sánchez-Silva, and A. L. Medaglia. 2016. “The interdependent network design problem for optimal infrastructure system restoration.” Comput.-Aided Civ. Infrastruct. Eng. 31 (5): 334–350.
Greenlaw, S. A., and D. Shapiro. 2014. “The aggregate demand/supply model.” Chap. 24 in Principles of economics. Houston: Openstax.
Guidotti, R., H. Chmielewski, V. Unnikrishnan, P. Gardoni, T. McAllister, and J. van de Lindt. 2016. “Modeling the resilience of critical infrastructure: The role of network dependencies.” Sustainable Resilient Infrastruct. 1 (3–4): 153–168. https://doi.org/10.1080/23789689.2016.1254999.
Guidotti, R., P. Gardoni, and Y. Chen. 2017. “Network reliability analysis with link and nodal weights and auxiliary nodes.” Struct. Saf. 65 (Mar): 12–26. https://doi.org/10.1016/j.strusafe.2016.12.001.
Haimes, Y. Y., B. M. Horowitz, J. H. Lambert, J. R. Santos, C. Lian, and K. G. Crowther. 2005a. “Inoperability input-output model for interdependent infrastructure sectors. I: Theory and methodology.” J. Infrastruct. Syst. 11 (2): 67–79. https://doi.org/10.1061/(ASCE)1076-0342(2005)11:2(67).
Haimes, Y. Y., B. M. Horowitz, J. H. Lambert, J. R. Santos, C. Lian, and K. G. Crowther. 2005b. “Inoperability input-output model for interdependent infrastructure sectors. II: Case studies.” J. Infrastruct. Syst. 11 (2): 80–92. https://doi.org/10.1061/(ASCE)1076-0342(2005)11:2(80).
Haimes, Y. Y., and P. Jiang. 2001. “Leontief-based model of risk in complex interconnected infrastructures.” J. Infrastruct. Syst. 7 (1): 1–12. https://doi.org/10.1061/(ASCE)1076-0342(2001)7:1(1).
Haraguchi, M., and S. Kim. 2016. “Critical infrastructure interdependence in New York city during Hurricane Sandy.” Int. J. Disaster Resilience Built Environ. 7 (2): 133–143. https://doi.org/10.1108/IJDRBE-03-2015-0015.
Hasan, S., and G. Foliente. 2015. “Modeling infrastructure system interdependencies and socioeconomic impacts of failure in extreme events: Emerging R&D challenges.” Nat. Hazards 78 (3): 2143–2168. https://doi.org/10.1007/s11069-015-1814-7.
Heglund, J., K. M. Hoplinson, and H. T. Tran. 2021. “Social sensing: Towards social media as a sensor for resilience in power systems and other critical infrastructures.” Sustainable Resilient Infrastruct. 6 (1–2): 94–106. https://doi.org/10.1080/23789689.2020.1719728.
HIFLD (Homeland Infrastructure Foundation-Level Data). 2018. “HIFLD open data.” Accessed May 30, 2018. https://hifld-geoplatform.opendata.arcgis.com/.
Hollings, C. S. 1973. “Resilience and sustainability of ecological systems.” Ann. Rev. Ecol. Syst. 4 (1): 1–23.
Hossain, N. U. I., R. Jaradat, S. Hosseini, M. Marufuzzaman, and R. K. Buchanan. 2019. “A framework for modeling and assessing system resilience using a Bayesian network: A case study of an interdependent electrical infrastructure system.” Int. J. Crit. Infrastruct. Prot. 25 (Jun): 62–83. https://doi.org/10.1016/j.ijcip.2019.02.002.
Hwang, S., M. Park, H.-S. Lee, S. Lee, and H. Kim. 2015. “Postdisaster interdependent built environment recovery efforts and the effects of governmental plans: Case analysis using system dynamics.” J. Constr. Eng. Manage. 141 (3): 04014081. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000939.
Johansen, C., and I. Tien. 2018. “Probabilistic multi-scale modeling of interdependencies between critical infrastructure systems for resilience.” Sustainable Resilient Infrastruct. 3 (1): 1–15. https://doi.org/10.1080/23789689.2017.1345253.
Johansson, J., and H. Hassel. 2010. “An approach for modelling interdependent infrastructures in the context of vulnerability analysis.” Syst. Saf. 95 (12): 1335–1344. https://doi.org/10.1016/j.ress.2010.06.010.
Kang, C., Y. Liu, D. Guo, and K. Qin. 2015. “A generalized radiation model for human mobility: Spatial scale, searching direction and trip constraints.” PLoS One 10 (11): e0143500. https://doi.org/10.1371/journal.pone.0143500.
Karakoc, D. B., Y. Almoghathawi, K. Barkera, A. D. González, and S. Mohebbi. 2019. “Community resilience-driven restoration model for interdependent infrastructure networks.” Int. J. Disaster Risk Reduct. 38 (Aug): 101228. https://doi.org/10.1016/j.ijdrr.2019.101228.
Karamlou, A., and P. Bocchini. 2016. “Sequencing algorithm with multiple-input genetic operators: Application to disaster resilience.” Eng. Struct. 117 (Jun): 591–602. https://doi.org/10.1016/j.engstruct.2016.03.038.
Karamlou, A., and P. Bocchini. 2017a. “From component damage to system-level probabilistic restoration functions for a damaged bridge.” J. Infrastruct. Syst. 23 (3): 04016042. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000342.
Karamlou, A., and P. Bocchini. 2017b. “Functionality fragility surface.” Earthquake Eng. Struct. Dyn. 46 (10): 1687–1709. https://doi.org/10.1002/eqe.2878.
Kelly, R. A., et al. 2013. “Selecting among five common modelling approaches for integrated environmental assessment and management.” Environ. Modell. Software 47 (Sep): 159–181. https://doi.org/10.1016/j.envsoft.2013.05.005.
Kelly, S. 2015. “Estimating economic loss from cascading infrastructure failure: A perspective on modelling interdependency.” Infrastruct. Complexity 2 (1): 1–13. https://doi.org/10.1186/s40551-015-0010-y.
Kim, J., V. Sridhara, and S. Bohacek. 2009. “Realistic mobility simulation of urban mesh networks.” Ad Hoc Networks 7 (2): 411–430. https://doi.org/10.1016/j.adhoc.2008.04.008.
Kizhakkedath, A., K. Tai, M. S. Sim, R. Lee, K. Tiong, and J. Lin. 2013. “An agent-based modeling and evolutionary optimization approach for vulnerability analysis of critical infrastructure networks.” In Proc., Asian Simulation Conf. (AsiaSim2013), edited by G. Tan, G. K. Yeo, S. J. Turner, and Y. M. Teo, 176–187. New York: Springer.
Koliou, M., J. W. van de Lindt, T. P. McAllister, B. R. Ellingwood, M. Dillard, and H. Cutlerd. 2020. “State of the research in community resilience: Progress and challenges.” Sustainable Resilient Infrastruct. 5 (3): 131–151. https://doi.org/10.1080/23789689.2017.1418547.
Kuang, S., and B. D. Davison. 2020. “Learning class-specific word embeddings.” J. Supercomput. 76 (10): 8265–8292. https://doi.org/10.1007/s11227-019-03024-z.
Laugé, A., J. Hernantes, and J. M. Sarriegi. 2015. “Critical infrastructure dependencies: A holistic, dynamic and quantitative approach.” Int. J. Crit. Infrastruct. Prot. 8 (Jan): 16–23. https://doi.org/10.1016/j.ijcip.2014.12.004.
LeClaire, R. J., and G. B. Hirsch. 2009. “Learning environment simulator: A tool for decision makers and first responders.” In Proc., 27th Int. System Dynamics Conf. LA-UR-09-01792. Washington, DC: USDOE.
LeClaire, R. J., and G. O’Reilly. 2005. “Leveraging a high fidelity switched network model to inform a system dynamics model of the telecommunications infrastructure.” In Proc., 23rd Int. System Dynamics Conf., LA-UR-05-1855. Albany, NY: System Dynamics Society.
Lee, B. H. Y., and P. Waddell. 2010. “Residential mobility and location choice: A nested logit model with sampling of alternatives.” Transportation 37 (4): 587–601. https://doi.org/10.1007/s11116-010-9270-4.
Lee, E. E., II, J. E. Mitchell, and W. A. Wallace. 2007. “Restoration of services in interdependent infrastructure systems: A network flows approach.” IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 37 (6): 1303–1317. https://doi.org/10.1109/TSMCC.2007.905859.
Lee, W. S., D. L. Grosh, F. A. Tillamn, and C. H. Lie. 1985. “Fault tree analysis, methods, and applications—A review.” IEEE Trans. Reliab. 34 (3): 194–203. https://doi.org/10.1109/TR.1985.5222114.
Leontief, W. W. 1951. “Input-output economics.” Sci. Am. 185 (4): 15–21. https://doi.org/10.1038/scientificamerican1051-15.
Lian, C., and Y. Y. Haimes. 2006. “Managing the risk of terrorism to interdependent infrastructure systems through the dynamic inoperability input–output model.” Syst. Eng. 9 (3): 241–258. https://doi.org/10.1002/sys.20051.
Lifeline Council. 2014. Lifelines interdependency study: The city and county of San Francisco. San Francisco, CA: Lifeline Council.
Links, J. M., et al. 2018. “Copewell: A conceptual framework and system dynamics model for predicting community functioning and resilience after disasters.” Disaster Med. Public Health Preparedness 12 (1): 127–137. https://doi.org/10.1017/dmp.2017.39.
Liu, K., C. Zhai, and Y. Dong. 2021. “Optimal restoration schedules of transportation network considering resilience.” Struct. Infrastruct. Eng. 17 (8): 1141–1154. https://doi.org/10.1080/15732479.2020.1801764.
Liu, M., and W. Xu. 2013. “The approach for critical infrastructure sectors classification using the inoperability input-output model (IIM).” In Proc., 6th Int. Conf. on Information Management, Innovation Management and Industrial Engineering (ICIII2013). New York: IEEE. https://doi.org/10.1109/ICIII.2013.6703668.
Logi, F., and S. G. Ritchie. 2002. “A multi-agent architecture for cooperative inter-jurisdictional traffic congestion management.” Transp. Res. Part C Emerging Technol. 10 (5): 507–527. https://doi.org/10.1016/S0968-090X(02)00033-5.
Lopez, C., J. R. Marti, and S. Sarkaria. 2018. “Distributed reinforcement learning in emergency response simulation.” IEEE Access 6: 67261–67276. https://doi.org/10.1109/ACCESS.2018.2878894.
Luiijf, E., A. Nieuwenhuijs, M. Klaver, M. van Eeten, and E. Cruz. 2008. “Empirical findings on critical infrastructure dependencies in Europe.” In Critical information infrastructure security, 302–310. Berlin: Springer.
Ma, L., V. Christou, and P. Bocchini. 2019. “Probabilistic simulation of power transmission systems affected by hurricane events based on fragility and AC power flow analyses.” In Proc., 13th Int. Conf. on Applications of Statistics and Probability in Civil Engineering (ICASP13). Seoul: Seoul National Univ.
Macal, C. M. 2016. “Everything you need to know about agent-based modelling and simulation.” J. Simul. 10 (2): 144–156. https://doi.org/10.1057/jos.2016.7.
Makowsky, M. 2006. “An agent-based model of mortality shocks, intergenerational effects, and urban crime.” J. Artif. Soc. Social Simul. 9 (2): 1–7.
McDaniels, T., S. Chang, K. Peterson, J. Mikawoz, and D. Reed. 2007. “Empirical framework for characterizing infrastructure failure interdependencies.” J. Infrastruct. Syst. 13 (3): 175–184. https://doi.org/10.1061/(ASCE)1076-0342(2007)13:3(175).
McPherson, T. N., and M. Witkowski. 2005. “Modeling urban water demand within a GIS using a population mobility model.” In Proc., World Water and Environmental Resource Congress 2005. Reston, VA: ASCE. https://doi.org/10.1061/40792(173)33.
Mendonça, D., and W. A. Wallace. 2006. “Impacts of the 2001 World Trade Center attack on New York city critical infrastructures.” J. Infrastruct. Syst. 12 (4): 260–270. https://doi.org/10.1061/(ASCE)1076-0342(2006)12:4(260).
Messner, S., and L. Schrattenholzer. 2000. “Message–macro: Linking an energy supply model with a macroeconomic module and solving it iteratively.” Energy 25 (3): 267–282. https://doi.org/10.1016/S0360-5442(99)00063-8.
Min, H. S. J., W. Beyeler, T. Brown, Y. J. Son, and A. T. Jones. 2007. “Toward modeling and simulation of critical national infrastructure interdependencies.” IIE Trans. 39 (1): 57–71. https://doi.org/10.1080/07408170600940005.
Minato, N., and R. Morimoto. 2017. “Dynamically interdependent business model for airline–airport coexistence.” J. Air Transp. Manage. 64 (Part B): 161–172. https://doi.org/10.1016/j.jairtraman.2016.08.002.
Mitsova, D., A.-M. Esnard, A. Sapat, and B. S. Lai. 2018. “Socioeconomic vulnerability and electric power restoration timelines in Florida: The case of Hurricane Irma.” Nat. Hazards 94 (2): 689–709. https://doi.org/10.1007/s11069-018-3413-x.
Mitsova, D., A. Sapat, A.-M. Esnard, and A. J. Lamadrid. 2020. “Evaluating the impact of infrastructure interdependencies on the emergency services sector and critical support functions using an expert opinion survey.” J. Infrastruct. Syst. 26 (2): 04020015. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000548.
Morrison, P. A. 1973. “Theoretical issues in the design of population mobility models.” Environ. Plann. 5 (1): 125–134.
Nivolianitou, Z. S., V. N. Leopoulos, and M. Konstantinidou. 2004. “Comparison of techniques for accident scenario analysis in hazardous systems.” J. Loss Prev. Process Ind. 17 (6): 467–475. https://doi.org/10.1016/j.jlp.2004.08.001.
North, M. J. 2001a. “Multi-agent social and organizational modeling of electric power and natural gas markets.” Comput. Math. Organ. Theory 7 (4): 331–337. https://doi.org/10.1023/A:1013406317362.
North, M. J. 2001b. “Smart II: The spot market agent research tool version 2.0.” Nat. Resour. Environ. Issues 8 (1): 11.
North, M. J. 2001c. “Toward strength and stability: Agent-based modeling of infrastructure markets.” Soc. Sci. Comput. Rev. 19 (3): 307–323. https://doi.org/10.1177/089443930101900306.
Nývlt, O., and M. Rausand. 2012. “Dependencies in event trees analyzed by Petri nets.” Reliab. Eng. Syst. Saf. 104 (Aug): 45–57. https://doi.org/10.1016/j.ress.2012.03.013.
OpenStreet. 2020. “Open infrastructure map.” Accessed May 20, 2020. https://openinframap.org/.
Orsi, M. J., and J. R. Santos. 2010. “Incorporating time-varying perturbations into the dynamic inoperability input-output model.” IEEE Trans. Syst. Man Cybern. Part A Syst. Humans 40 (1): 100–106. https://doi.org/10.1109/TSMCA.2009.2030587.
Ouyang, M. 2014. “Review on modeling and simulation of interdependent critical infrastructure systems.” Reliab. Eng. Syst. Saf. 121 (Jan): 43–60. https://doi.org/10.1016/j.ress.2013.06.040.
Ouyang, M. 2017. “A mathematical framework to optimize resilience of interdependent critical infrastructure systems under spatially localized attacks.” Eur. J. Oper. Res. 262 (3): 1072–1084. https://doi.org/10.1016/j.ejor.2017.04.022.
Ouyang, M., and Z. Wang. 2015. “Resilience assessment of interdependent infrastructure systems: With a focus on joint restoration modeling and analysis.” Reliab. Eng. Syst. Saf. 141 (Sep): 74–82. https://doi.org/10.1016/j.ress.2015.03.011.
Pederson, P., D. Dudenhoeffer, S. Hartley, and M. Permann. 2006. Critical infrastructure interdependency modeling: A survey of US and international research. Idaho Falls, ID: Idaho National Laboratory.
Permann, M. R. 2007. “Genetic algorithms for agent-based infrastructure interdependency modeling and analysis.” In Proc., 2007 Spring Simulation Multiconference—Volume 2, (SpringSim ‘07), 169–177. San Diego, CA: Society for Computer Simulation International.
Pilkington, S. F., and H. N. Mahmoud. 2020. “Interpreting the socio-technical interactions within a wind damage–artificial neural network model for community resilience.” R. Soc. Open Sci. 7 (11): 200922. https://doi.org/10.1098/rsos.200922.
PPD (Presidential Policy Directive). 2013. “Presidential policy directive/ppd-21—Critical infrastructure security and resilience.” Accessed May 30, 2018. https://obamawhitehouse.archives.gov/the-press-office/2013/02/12/presidential-policy-directive-critical-infrastructure-security-and-resil.
Rao, K. D., V. Gopika, V. V. S. S. Rao, H. S. Kushwaha, A. K. Verma, and A. Srividya. 2009. “Dynamic fault tree analysis using Monte Carlo simulation in probabilistic safety assessment.” Reliab. Eng. Syst. Saf. 94 (4): 872–883. https://doi.org/10.1016/j.ress.2008.09.007.
Rathje, E. M., et al. 2017. “DesignSafe: New cyberinfrastructure for natural hazards engineering.” Nat. Hazard. Rev. 18 (3): 06017001. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000246.
Rinaldi, S., J. Peerenboom, and T. Kelly. 2001. “Identifying, understanding, and analyzing critical infrastructure interdependencies.” IEEE Control Syst. 21 (6): 11–25. https://doi.org/10.1109/37.969131.
Rinaldi, S. M. 2004. “Modeling and simulating critical infrastructures and their interdependencies.” In Proc., 37th Annual Hawaii International Conf. on System Sciences. New York: IEEE. https://doi.org/10.1109/HICSS.2004.1265180.
Rong, M., C. Han, and L. Liu. 2010. “Critical infrastructure failure interdependencies in the 2008 Chinese winter storms.” In Proc., 2010 Int. Conf. on Management and Service Science. Wuhan, China: IEEE. https://doi.org/10.1109/ICMSS.2010.5576239.
Rose, A. 1995. “Input-output economics and computable general equilibrium models.” Struct. Change Econ. Dyn. 6 (3): 295–304. https://doi.org/10.1016/0954-349X(95)00018-I.
Rose, A., and S. Y. Liao. 2005. “Modeling regional economic resilience to disasters: A computable general equilibrium analysis of water service disruptions.” J. Reg. Sci. 45 (1): 75–112. https://doi.org/10.1111/j.0022-4146.2005.00365.x.
Rose, A., G. Oladosu, and S. Y. Liao. 2007. “Business interruption impacts of a terrorist attack on the electric power system of Los Angeles: Customer resilience to a total blackout.” Risk Anal. 27 (3): 513–531. https://doi.org/10.1111/j.1539-6924.2007.00912.x.
Roy, K. C., S. Hasan, and P. Mozumder. 2020. “A multilabel classification approach to identify hurricane-induced infrastructure disruptions using social media data.” Comput.-Aided Civ. Infrastruct. Eng. 35 (12): 1387–1402. https://doi.org/10.1111/mice.12573.
Santella, N., L. J. Steinberg, and K. Parks. 2009. “Decision making for extreme events: Modeling critical infrastructure interdependencies to aid mitigation and response planning.” Rev. Policy Res. 26 (4): 409–422. https://doi.org/10.1111/j.1541-1338.2009.00392.x.
Santos, J. R. 2005. “Inoperability input-output modeling of disruptions to interdependent economic systems.” Syst. Eng. 9 (1): 20–34. https://doi.org/10.1002/sys.20040.
Santos, J. R., and Y. Y. Haimes. 2004. “Modeling the demand reduction input-output (I-O) inoperability due to terrorism of interconnected infrastructures.” Risk Anal. 24 (6): 1437–1451. https://doi.org/10.1111/j.0272-4332.2004.00540.x.
Santos, J. R., Y. Y. Haimes, and J. G. Voeller. 2008. “Input–output modeling for interdependent infrastructure sectors.” In Wiley handbook of science and technology for homeland security. Hoboken, NJ: Wiley.
Sharkey, T. C., B. C. Cavdaroglu, H. Nguyen, J. Holman, J. E. Mitchell, and W. A. Wallace. 2015. “Interdependent network restoration: On the value of information sharing.” Eur. J. Oper. Res. 244 (1): 309–321. https://doi.org/10.1016/j.ejor.2014.12.051.
Sharkey, T. C., S. G. Nurre, H. Nguyen, J. H. Chow, J. E. Mitchell, and W. A. Wallace. 2016. “Identification and classification of restoration interdependencies in the wake of Hurricane Sandy.” J. Infrastruct. Syst. 22 (1): 04015007. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000262.
Shinozuka, M., Y. Murachi, X. Dong, Y. Zhou, and M. J. Orlikowski. 2003. “Effect of seismic retrofit of bridges on transportation networks.” Earthquake Eng. Eng. Vibr. 2 (2): 169–179. https://doi.org/10.1007/s11803-003-0001-0.
Singh, A. N., M. P. Gupta, and A. Ojha. 2014. “Identifying critical infrastructure sectors and their dependencies: An Indian scenario.” Int. J. Crit. Infrastruct. Prot. 7 (2): 71–85. https://doi.org/10.1016/j.ijcip.2014.04.003.
Sun, J., and Z. Zhang. 2020. “A post-disaster resource allocation framework for improving resilience of interdependent infrastructure networks.” Transp. Res. Part D Transp. Environ. 85 (Aug): 102455. https://doi.org/10.1016/j.trd.2020.102455.
Sun, W., P. Bocchini, and B. D. Davison. Forthcoming. “Quantitative models for interdependent functionality and recovery of critical infrastructure systems.” Chap. 4 in Objective resilience: Objective processes, manual of practice, edited by M. Ettouney, 147. Reston, VA: ASCE.
Sun, W., P. Bocchini, and B. D. Davison. 2019. “Comparing decision models for disaster restoration of interdependent infrastructures under uncertainty.” In Proc., 13th Int. Conf. on Applications of Statistics and Probability in Civil Engineering (ICASP13). Seoul: Seoul National Univ.
Sun, W., P. Bocchini, and B. D. Davison. 2020a. “Applications of artificial intelligence for disaster management.” Nat. Hazards 103 (3): 2631–2689. https://doi.org/10.1007/s11069-020-04124-3.
Sun, W., P. Bocchini, and B. D. Davison. 2020b. “Model for estimating the impact of interdependencies on system recovery.” J. Infrastruct. Syst. 26 (3): 04020031. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000569.
Sun, W., P. Bocchini, and B. D. Davison. 2020c. “Policy-based disaster recovery planning model for interdependent infrastructure systems under uncertainty.” Struct. Infrastruct. Eng. 17 (4): 555–578. https://doi.org/10.1080/15732479.2020.1843504.
Sun, W., P. Bocchini, and B. D. Davison. 2020d. “Resilience metrics and measurement methods for transportation infrastructure: The state of the art.” Sustainable Resilient Infrastruct. 5 (3): 168–199. https://doi.org/10.1080/23789689.2018.1448663.
Sutley, E. J., and S. Hamideh. 2018. “An interdisciplinary system dynamics model for post-disaster housing recovery.” Sustainable Resilient Infrastruct. 3 (3): 109–127. https://doi.org/10.1080/23789689.2017.1364561.
Tang, A., J. Ou, A. Wen, and X. Tao. 2004. “Lifeline systems interaction and their seismic performance assessment.” In Proc., 13th World Conf. on Earthquake Engineering (13WCEE). Vancouver, BC, Canada: World Conferences on Earthquake Engineering.
Teodorescu, H.-N. L. 2015. “Defining resilience using probabilistic event trees.” Environ. Syst. Decis. 35 (2): 279–290. https://doi.org/10.1007/s10669-015-9550-9.
Thurner, L., A. Scheidler, F. Schäfer, J.-H. Menke, J. Dollichon, F. Meier, S. Meinecke, and M. Braun. 2018. “Pandapower—An open-source Python tool for convenient modeling, analysis, and optimization of electric power systems.” IEEE Trans. Power Syst. 33 (6): 6510–6521. https://doi.org/10.1109/TPWRS.2018.2829021.
Tien, I., and A. Der Kiureghian. 2016. “Algorithms for Bayesian network modeling and reliability assessment of infrastructure systems.” Reliab. Eng. Syst. Saf. 156 (Dec): 134–147. https://doi.org/10.1016/j.ress.2016.07.022.
Tøndel, I. A., J. Foros, S. S. Kilskar, P. Hokstad, and M. G. Jaatun. 2018. “Interdependencies and reliability in the combined ICT and power system: An overview of current research.” Appl. Comput. Inf. 14 (1): 17–27. https://doi.org/10.1016/j.aci.2017.01.001.
van Hillegersberg, J., H. Moonen, T. Verduijn, and J. Becker. 2004. “Agent technology in supply chains and networks: An exploration of high potential future applications.” In Proc., IEEE/WIC/ACM Int. Conf. on Intelligent Agent Technology (IAT2004), 267–272. New York: IEEE. https://doi.org/10.1109/IAT.2004.1342954.
Vazquez-Prokopec, G. M., et al. 2013. “Using GPS technology to quantify human mobility, dynamic contacts and infectious disease dynamics in a resource-poor urban environment.” PLoS One 8 (4): e58802. https://doi.org/10.1371/journal.pone.0058802.
Vugrin, E. D., M. A. Turnquist, and N. J. Brown. 2014. “Optimal recovery sequencing for enhanced resilience and service restoration in transportation networks.” Int. J. Crit. Infrastruct. 10 (3–4): 218–246. https://doi.org/10.1504/IJCIS.2014.066356.
Wallace, W. A., D. Mendonça, and E. E. Lee. 2003. “Managing disruptions to critical interdependent infrastructures in the context of the 2001 World Trade Center attack.” In Impacts of and human response to the September 11, 2001 disasters: What research tells us, edited by M. F. Myers, 165–198. Boulder, CO: Natural Hazards Research and Applications Information Center.
Watson, H. A. 1961. Launch control safety study. Murray Hill, NJ: Bell Telephone Laboratories.
Wei, W., D. Wu, Q. Wu, M. Shafie-Khah, and J. P. S. Catalão. 2019. “Interdependence between transportation system and power distribution system: A comprehensive review on models and applications.” J. Mod. Power Syst. Clean Energy 7 (3): 433–448. https://doi.org/10.1007/s40565-019-0516-7.
Wheeler, T., M. Denman, R. A. Williams, N. Martin, and Z. Jankovsky. 2017. Nuclear power plant cyber security discrete dynamic event tree analysis. Albuquerque, NM: Sandia National Laboratories.
Wu, Y., L. Xie, and Y. Yue. 2010. “Study on fault analysis technology by means of Petri nets.” Int. J. Performability Eng. 6 (3): 269–277.
Yan, X.-Y., W.-X. Wang, Z.-Y. Gao, and Y.-C. Lai. 2017. “Universal model of individual and population mobility on diverse spatial scales.” Nat. Commun. 8 (1): 1639. https://doi.org/10.1038/s41467-017-01892-8.
Yang, Y., S. T. Ng, S. Zhou, F. J. Xu, and H. Li. 2019. “A physics-based framework for analyzing the resilience of interdependent civil infrastructure systems: A climatic extreme event case in Hong Kong.” Sustainable Cities Soc. 47 (May): 101485. https://doi.org/10.1016/j.scs.2019.101485.
Zaidi, S. M. A., V. Chandola, M. R. Allen, J. Sanyal, R. N. Stewart, B. L. Bhaduri, and R. A. McManamay. 2018. “Machine learning for energy-water nexus: Challenges and opportunities.” Big Earth Data 2 (3): 228–267. https://doi.org/10.1080/20964471.2018.1526057.
Zhang, C., J. Kong, and S. P. Simonovic. 2018. “Modeling joint restoration strategies for interdependent infrastructure systems.” PLoS One 13 (4): e0195727. https://doi.org/10.1371/journal.pone.0195727.
Zhang, P., and S. Peeta. 2011. “A generalized modeling framework to analyze interdependencies among infrastructure systems.” Transp. Res. Part B Methodol. 45 (3): 553–579. https://doi.org/10.1016/j.trb.2010.10.001.
Zhou, S., S. T. Ng, Y. Yang, and J. F. Xu. 2020. “Delineating infrastructure failure interdependencies and associated stakeholders through news mining: The case of Hong Kong’s water pipe bursts.” J. Manage. Eng. 36 (5): 04020060. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000821.
Zimmerman, R. 2001. “Social implications of infrastructure network interactions.” J. Urban Technol. 8 (3): 97–119. https://doi.org/10.1080/106307301753430764.
Zlotnik, A., L. Roald, S. Backhaus, M. Chertkov, and G. Andersson. 2017. “Coordinated scheduling for interdependent electric power and natural gas infrastructures.” IEEE Trans. Power Syst. 32 (1): 600–610. https://doi.org/10.1109/TPWRS.2016.2545522.

Information & Authors

Information

Published In

Go to Natural Hazards Review
Natural Hazards Review
Volume 23Issue 1February 2022

History

Received: Sep 29, 2020
Accepted: Sep 27, 2021
Published online: Nov 8, 2021
Published in print: Feb 1, 2022
Discussion open until: Apr 8, 2022

Permissions

Request permissions for this article.

Authors

Affiliations

Postdoc Research Associate, Dept. of Civil and Environmental Engineering, Advanced Technology for Large Structural Systems Engineering Research Center, Lehigh Univ., 117 ATLSS Dr., Bethlehem, PA 18015. ORCID: https://orcid.org/0000-0003-0546-2389
Associate Professor, Dept. of Civil and Environmental Engineering, Advanced Technology for Large Structural Systems Engineering Research Center, Lehigh Univ., 117 ATLSS, Bethlehem, PA 18015 (corresponding author). ORCID: https://orcid.org/0000-0002-5685-2283. Email: [email protected]
Professor, Dept. of Computer Science and Engineering, Lehigh Univ., 113 Research Dr., Bethlehem, PA 18015. ORCID: https://orcid.org/0000-0002-9326-3648

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

  • A Scenario-Driven Fault-Control Decision Support Model for Disaster Preparedness Using Case-Based Reasoning, Natural Hazards Review, 10.1061/NHREFO.NHENG-1722, 24, 4, (2023).
  • A belief rule-base approach to the assessment and improvement of seismic resilience of high-speed railway station buildings, Soil Dynamics and Earthquake Engineering, 10.1016/j.soildyn.2022.107680, 165, (107680), (2023).
  • Community structure recovery optimization for partial disruption, functionality, and restoration in interdependent networks, Reliability Engineering & System Safety, 10.1016/j.ress.2022.108853, 229, (108853), (2023).
  • An Artificial Intelligence (AI) Approach to Controlling Disaster Scenarios, Future Role of Sustainable Innovative Technologies in Crisis Management, 10.4018/978-1-7998-9815-3.ch003, (28-46), (2022).
  • Impacts of varying network parameters on the vulnerability and resilience of interdependent critical infrastructure systems, Sustainable and Resilient Infrastructure, 10.1080/23789689.2022.2126628, 7, 6, (984-1007), (2022).
  • Quantitative Models for Interdependent Functionality and Recovery of Critical Infrastructure Systems, Objective Resilience, 10.1061/9780784415894.ch4, (127-229), (2022).
  • Quantifying component importance for disaster resilience of communities with interdependent civil infrastructure systems, Reliability Engineering & System Safety, 10.1016/j.ress.2022.108747, 228, (108747), (2022).

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share