Case Study for Quantifying Flood Resilience of Interdependent Building-Roadway Infrastructure Systems

Kanti Sen, M; Dutta, S; Gandomi, AH; Putcha, C

Case Study for Quantifying Flood Resilience of Interdependent Building-Roadway Infrastructure Systems

Kanti Sen, M Dutta, S Gandomi, AH Putcha, C

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Publisher:: American Society of Civil Engineers
Publication Type:: Journal Article
Citation:: ASCE - ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 2021, 7, (2), pp. 1-19
Issue Date:: 2021-06-01

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Field	Value	Language
dc.contributor.author	Kanti Sen, M
dc.contributor.author	Dutta, S
dc.contributor.author	Gandomi, AH
dc.contributor.author	Putcha, C
dc.date.accessioned	2022-03-22T03:32:19Z
dc.date.available	2022-03-22T03:32:19Z
dc.date.issued	2021-06-01
dc.identifier.citation	ASCE - ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 2021, 7, (2), pp. 1-19
dc.identifier.issn	2376-7642
dc.identifier.issn	2376-7642
dc.identifier.uri	http://hdl.handle.net/10453/155448
dc.description.abstract	Resilience is defined as the ability of a system to withstand and recover to a desired level of performance after the occurrence of a hazard. Community resilience has a significant socioeconomic implication for any disaster. Therefore, attempting to quantify resilience after a disaster is of utmost importance, particularly for planners, designers, and decision makers. Modern society depends on various infrastructure system networks to ensure functionality, and these infrastructure systems perform on their own and also perform interdependently with other infrastructure networks during natural hazards. For quantifying resilience, the interdependency between infrastructure systems plays a significant role; for instance, in the event of building damage, the state of damage to the roadways network is also crucial for the recovery process and ultimately in resilience. As a result, large-scale disruption of any infrastructure network increases significantly because of interdependency. In this work, an integrated geographic information system (GIS) and Bayesian belief network (BBN) framework is developed to study the resilience and effects in functionality due to interdependency among building and roadways infrastructure systems in a community. GIS is used for data collection, and BBN is adopted for computing the posterior probabilities of resilience. The framework is then implemented in a study area of Barak Valley in North-East India, and resilience is evaluated for the considered building-roadways network. Sensitivity analysis of system resilience to the critical components is performed to facilitate decision making under uncertainty. Finally, some general recommendations are given for improving flood resilience for future disasters.
dc.language	English
dc.publisher	American Society of Civil Engineers
dc.relation.ispartof	ASCE - ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
dc.relation.isbasedon	10.1061/AJRUA6.0001117
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0905 Civil Engineering
dc.title	Case Study for Quantifying Flood Resilience of Interdependent Building-Roadway Infrastructure Systems
dc.type	Journal Article
utslib.citation.volume	7
utslib.for	0905 Civil Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-03-22T03:32:16Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	7
utslib.citation.issue	2

Abstract:

Resilience is defined as the ability of a system to withstand and recover to a desired level of performance after the occurrence of a hazard. Community resilience has a significant socioeconomic implication for any disaster. Therefore, attempting to quantify resilience after a disaster is of utmost importance, particularly for planners, designers, and decision makers. Modern society depends on various infrastructure system networks to ensure functionality, and these infrastructure systems perform on their own and also perform interdependently with other infrastructure networks during natural hazards. For quantifying resilience, the interdependency between infrastructure systems plays a significant role; for instance, in the event of building damage, the state of damage to the roadways network is also crucial for the recovery process and ultimately in resilience. As a result, large-scale disruption of any infrastructure network increases significantly because of interdependency. In this work, an integrated geographic information system (GIS) and Bayesian belief network (BBN) framework is developed to study the resilience and effects in functionality due to interdependency among building and roadways infrastructure systems in a community. GIS is used for data collection, and BBN is adopted for computing the posterior probabilities of resilience. The framework is then implemented in a study area of Barak Valley in North-East India, and resilience is evaluated for the considered building-roadways network. Sensitivity analysis of system resilience to the critical components is performed to facilitate decision making under uncertainty. Finally, some general recommendations are given for improving flood resilience for future disasters.

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http://hdl.handle.net/10453/155448