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Human-centered modeling framework of multiple interdependency in urban systems for simulation of post-disaster recovery processes

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Abstract

This paper presents a human-centered modeling framework of urban systems to capture various types of interdependency underlying urban sociotechnical and socioeconomic systems. The proposed framework consists of three major subsystems: civil life, manufacturing/service industry, and lifeline infrastructure. This framework classifies nine different types of interdependencies existing within and between these three subsystems. This paper also presents a computer simulation of the post-disaster recovery process of urban systems considering various interdependencies captured by the modeling framework. We adopt an agent-based model incorporating a network model for implementing the three subsystems as well as the various types of interdependencies. A sensitivity analysis was conducted based on the R4 framework of disaster resilience to verify and validate the simulation model. The simulation results were generally consistent with the predictions made by the R4 framework, suggesting that the model was implemented properly and can capture the multiple interdependencies behind the urban systems.

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References

  1. Albara-Bertrand JM (2013) Disasters and Networked Economy, 2013. Routledge, Oxon

  2. Amantini A, Choras M, D’Antonio A, Egozcue E, Germanus D, Hutter R (2012) The human role in tools for improving robustness and resilience of critical infrastructures. Cognit Technol Work 14:143–155

  3. Bruneau M, Chang SE, Eguchi RT, Lee GC, O’Rourke TD, Reinhorm AM, Shinozuka M, Tierney K, Wallace WA, von Winterfeld D (2003) A framework to quantitatively assess and enhance the seismic resilience of communities. Earthq Spectra 19(4):737–738

  4. Central Disaster Prevention Council (2013) Disaster preparedness for Nankai trough earthquake. http://www.bousai.go.jp/jishin/nankai/taisaku_wg/pdf/20130528_honbun.pdf. Accessed 26 July 2018 (in Japanese)

  5. Dundenhoeffer DD, Permann MR, Boring RL, 2006, Decision consequence in complex environments: visualizing decision impact. In: Proc. Decision Consequence in Complex Environments, pp 211–218

  6. Enjalbert S, Vanderhaegen F (2017) A hybrid reinforced learning system to estimate resilience indicators. Eng Appl Artif Intell 64:295–301

  7. Folke C (2006) Resilience: the emergence of a perspective for social-ecological systems analyses. Glob Environ Change 16:253–267

  8. Furuta K, Kanno T, 2013, Issues in service system resilience. In: Proc. 43rd Annual IEEE/IFIP Conf. Dependable Systems and Networks Workshop

  9. Furuta H, Nakatsu K, Nomura Y (2005) Optimal restoration scheduling of damaged networks in uncertain environment. Doboku Gakkai Ronbunshuu A 64(2):434–445

  10. Guidotti R, Chmielewski H, Unnikrishnan V, Gardoni P, McAllister T, de Lindt J (2016) Modeling the resilience of critical infrastructure: the role of network dependencies. Sustain Resil Infrastruct 1(3–4):153–168

  11. Hasan S, Foliente G (2015) Modeling infrastructure system interdependencies and socioeconomic impacts of failure in extreme events: emerging R&D challenges. Nat Hazards 78(3):2143–2168

  12. Hayashi H, Kameda H, Nojima N (1994) Troubles people have to suffer when lifelines fail to function after earthquake. In: Proceedings from the Fifth US-Japan Workshop on earthquake resistant design of lifeline facilities and countermeasures against soil liquefaction, pp 593–599

  13. Holling C (1973) Resilience and stability of ecological systems. Annu Rev Ecol Syst 4:1–23

  14. Hollnagel E (2011) RAG—the resilience analysis grid. In: Hollnagel E, Pariès J, Woods DD, Wreathall J (eds) Resilience engineering in practice. A Guidebook. Ashgate, Surrey, England

  15. Hollnagel D, Woods DD, Leveson N (2006) Resilience engineering, concepts and precepts. Ashgate, Hampshire, England

  16. Hollnagel E, Nemeth CP, Dekker S (2008) Resilience engineering perspectives. Ashgate, Hampshire, England

  17. Johansen C, Tien I (2018) Probabilistic multi-scale modeling of interdependencies between critical infrastructure systems for resilience. Sustain Resil Infrastruct 3(1):1–15

  18. Johnson J, Wood AM (2017) Integrating positive and clinical psychology: viewing human functioning as continua from positive to negative can benefit clinical assessment. Interv Underst Resil 41:335–349

  19. Jovanovic AS, Schmid N, Klimek P (2016) Use of indicators for assessing resilience of smart critical infrastructures. In: Linkov I, Florin MV (eds) IRGC resource guide on resilience. IRGC, Lausanne

  20. Kanno T, Suzuki T, Yoshida Y, Furuta K, 2016, Simulation of post-disaster recovery for building a resilient Tokyo. In: Proc. 6th. Int’l Conf. Building Resilience, Paper No.14

  21. Kasthurirangan G, Srinivas P (eds) (2010) Sustainable and resilient critical infrastructure systems. Springer, Berlin, Heidelberg

  22. Kito T, Ueda K (2014) The Implications of automobile parts supply network structures: a complex network approach. CIRP Ann Manuf Technol 63(1):393–396

  23. Krackhardt D, Carley KM (1998) A PCANS model of structure in organizations. In: Proc. Int’l Symp. Command and control research and technology, pp 113–119

  24. Maslow A (1954) Motivation and personality. Harper & Brothers, New York

  25. Multidisciplinary Center for Earthquake Engineering Research (2018) http://www.buffalo.edu/mceer.html. Accessed 14 June 2018

  26. National Academies (2012) Disaster resilience. National Academies Press, Washington DC

  27. Okuyama Y, Santos JR (2014) Disaster impact and input-output analysis. Econ Syst Res 26(1):1–12

  28. Ouderaogo KA, Enjalbert S, Vanderhaegen F (2013) How to learn from the resilience of human-machine systems? Eng Appl Artif Intell 26:24–34

  29. Ouyang M (2014) Review on modeling and simulation of interdependent critical infrastructure system. Reliab Eng Syst Saf 121:43–60

  30. Patriarca R, Bergstrom J, Gravio GD, Costantino F (2018) Resilience engineering: current status of the research and future challenges. Saf Sci 102:79–100

  31. Putnik GD, Skulj G, Vrabic R, Varela L, Butala P (2015) Simulation study of large production network robustness in uncertain environment. CIRP Ann Manuf Technol 64(1):439–442

  32. Regt A, Siegel AW, Schraagen JM (2016) Toward quantifying metrics for rail-system resilience: identification and analysis of performance weak resilience signals. Cognit Technol Work 18:319–331

  33. Reiner M, McElvaney K (2017) Foundational infrastructure framework for city resilience. Sustain Resil Infrastruct 2(1–7):1–7

  34. Resilience (2018) The Oxford English Dictionary (OED Online). http://www.oed.com/view/Entry/163619?redirectedFrom=resilience#eid. Accessed 20 June 2018

  35. Rigi AW, Saurin TA, Wachs P (2015) A systematic literature review of resilience engineering: research areas and a research agenda proposal. Reliab Eng Syst Saf 141:142–152

  36. Rinaldi SM, Peerenboom JP, Kelly TK (2001) Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE Control Syst Mag 21(6):11–25

  37. Rouse WB (2003) Engineering complex systems: implications for research in systems engineering. IEEE Trans Syst Man Cybernet Part C Appl Rev 33(2):183–196

  38. Rouse WB (2015) Modeling and visualization of complex systems and enterprises: explorations of physical, human, economic, and social phenomena. Wiley, Hoboken, New Jersey

  39. Shirali GA, Motamedzade M, Mohammadfam I, Ebrahimipour V (2016) Assessment of resilience engineering factors based on system properties in a process industry. Cognit Technol Work 18:19–31

  40. Sugimoto H, Tamura T, Arimura K, Saito K (1999) The restoration model of the damaged road network based on the cooperation of the improvement teams. Doboku Gakkai Ronbunshuu 625(IV–44):135–148

  41. Tang L, Jing K, He J, Stanley HE (2016) Complex interdependent supply chain networks: cascading failure and robustness. Phys A 443:58–69

  42. Tierney K, Bruneau M (2007) Conceptualizing and measuring resilience: a key to disaster loss reduction. TR News 250:14–15

  43. Togawa T, Mimuro A, Kato H, Hayashi Y, Nishino S, Takano T, 2011, Evaluation post-disaster reconstruction and improvement management from QOL standards in disasters In: Proc. Joint Intl Symp. On social management systems, pp 362–369

  44. Wei D, Ji K (2010) Resilient industrial control system (RICS): concepts, formulation, metrics and insights. In: Proc. Int’l Symp. on Resilient Control Systems, pp 15–22

  45. Zhang W, Wang N, Nicholson C (2017) Resilience-based post-disaster recovery strategies for road-bridge networks. Struct Infrastruct Eng 13(11):1404–1413

  46. Zio E (2016) Challenges in the vulnerability and risk analyses of critical infrastructures. Reliab Eng Syst Saf 152:137–150

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Correspondence to T. Kanno.

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Kanno, T., Koike, S., Suzuki, T. et al. Human-centered modeling framework of multiple interdependency in urban systems for simulation of post-disaster recovery processes. Cogn Tech Work 21, 301–316 (2019). https://doi.org/10.1007/s10111-018-0510-2

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Keywords

  • Disaster resilience
  • Critical infrastructure
  • Interdependency
  • Agent-based model
  • Network model