Towards HLA-based Modeling of Interdependent Infrastructure Systems

2021 ◽  
Author(s):  
Joseph Jonathan Magoua ◽  
Fei Wang ◽  
Nan Li
Keyword(s):  
Infrastructure Systems ◽  
Interdependent Infrastructure

Infrastructure Decay Modeling With the Input-Output Inoperability Model

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Vhance V. Valencia ◽  
Alfred E. Thal ◽  
John M. Colombi ◽  
William E. Sitzabee
Keyword(s):  
Asset Management ◽  
Input Output ◽  
Infrastructure Systems ◽  
Cascading Effects ◽  
Multiple Networks ◽  
Infrastructure Network ◽  
Asset Managers ◽  
Infrastructure Interdependency ◽  
Interdependent Infrastructure

Asset management and infrastructure interdependency concepts are found to be useful in the study of infrastructure decay. As such, infrastructure decay is modeled with the input-output inoperability model (IIM), which is a method of analysis that captures cascading effects of a disturbance in interdependent infrastructure systems. This paper presents an extension to the IIM that simplifies the construction of the interdependency matrix central to the model and integrates the use of component decay curves for each component in the system. The revised model results in the ability of infrastructure asset managers to recognize the effect of decay across an entire infrastructure network or multiple networks.

Integrating restoration and scheduling decisions for disrupted interdependent infrastructure systems

2011 ◽  
Vol 203 (1) ◽  
pp. 279-294 ◽  
Author(s):  
Burak Cavdaroglu ◽  
Erik Hammel ◽  
John E. Mitchell ◽  
Thomas C. Sharkey ◽  
William A. Wallace
Keyword(s):  
Infrastructure Systems ◽  
Interdependent Infrastructure

Institutional congruence for resilience management in interdependent infrastructure systems

2020 ◽  
Vol 46 ◽  
pp. 101515 ◽  
Author(s):  
Hamed Farahmand ◽  
Shangjia Dong ◽  
Ali Mostafavi ◽  
Philip R. Berke ◽  
Sierra C. Woodruff ◽  
...  
Keyword(s):  
Infrastructure Systems ◽  
Resilience Management ◽  
Interdependent Infrastructure

scholarly journals A Two-Stage Restoration Resource Allocation Model for Enhancing the Resilience of Interdependent Infrastructure Systems

2019 ◽  
Vol 11 (19) ◽  
pp. 5143 ◽  
Author(s):  
Jingjing Kong ◽  
Chao Zhang ◽  
Slobodan P. Simonovic
Keyword(s):  
Resource Allocation ◽  
Recovery Time ◽  
Critical Role ◽  
Recovery Process ◽  
Decision Makers ◽  
Two Stage ◽  
Allocation Model ◽  
Infrastructure Systems ◽  
Resource Allocation Model ◽  
Interdependent Infrastructure

Infrastructure systems play a critical role in delivering essential services that are important to the economy and welfare of society. To enhance the resilience of infrastructure systems after a large-scale disruptive event, determining where and when to invest restoration resources is a challenge for decision makers. Comprehensively considering the recovery time of infrastructure systems and the overall losses resulting from a disaster, this study proposes a two-stage restoration resource allocation model for enhancing the resilience of interdependent infrastructure systems. First, to evaluate the effect of resource allocation during the recovery process, dynamic resilience is selected as the criterion for the recovery of infrastructure systems. Second, taking into consideration the decision makers’ point of view, a two-stage resource allocation model is proposed. The objective of the first stage is to quickly recover the infrastructure systems’ dynamic resilience to meet the basic needs of the users. The second stage is aimed at minimizing the overall losses in the following recovery process. The effects of infrastructure interdependencies on resource allocation are incorporated in the model using the dynamic inoperability input–output model. Through a case study, the proposed approach is compared with other resource allocation strategies. The results show that: (1) the restoration resource allocation strategy obtained from the proposed approach balances the recovery time and the overall losses to infrastructure systems; and (2) the value of the usage cost of the unit restoration resource has a significant impact on the recovery time and the overall losses under different strategies. The proposed model is both effective and efficient in solving the post-disaster resource allocation problem and can provide decision makers with scientific decision support.

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