A Framework and Case Study for the Resilience of Infrastructures

A Framework and Case Study for the Resilience of Infrastructures

Ali Golara (NIGC, Iran)
DOI: 10.4018/978-1-5225-2089-4.ch010
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Abstract

This chapter defines resilience in different contexts comprehensively, and organizes the mathematical theory of network resilience by providing a generalization in order to create a quantitative framework for resilience characterization of an infrastructure network. At this point, a new performance index measuring delivery importance was employed for an applied purpose and an industrial example using realistic data was solved to evaluate the resilience of the entire network. It can be utilized for any type of hazard which might lead to the disruption of the system. The principles and theory in this study can also be applied to other infrastructures that are interconnected and operate as a network, such as transporting systems, electrical power, water supply and distribution systems.
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Introduction

Natural disasters always result to great damages and losses in natural and man-made environments. These damages are crystallized in different forms of Fatality, Economic, Social, Security, Cultural, and Military damages, and can as well lead to decay and disintegration of the society. The extent and severity of these damages are a function of environmental circumstances, the human understanding of risk and the risk-taking behaviour of the society. Thus, estimating the impact of the risks on the environment and human beings is a main prerequisite. Every potential and physical destructive event, phenomenon or human activity that may lead to loss of life or injury, destruction of buildings, disorder, impaired social, economical and infrastructural systems, may well contain the secret, hidden aspects and conditions, which may represent a sign of future threats.

The first difficulty in identifying the risk is acquiring and collecting reliable information, as well as classifying them and their impact on the various categories. Next is to identify possible ways in reducing the damages caused by these risks. The linking of technical findings in the risk with the increasing levels of awareness and risk warnings can be referred to other challenges. Furthermore, risk-taking is an increasingly global concern and its impact and activities in one area can affect the risk-taking in other areas. Providing a system with layers of information for risk factors, the vulnerable components exposed to the disasters, amount of damages derived from the risk factors can be a step in reducing and controlling the risk-taking.

Lack of detailed knowledge of risk factors or lack of adequate information may possibly affect the risk information of the built environment and change vulnerability. For example, in the case of earthquake risk, the first step is the gathering of information of identified active faults. However, there are considerable uncertainties in this step, since unidentified and hidden faults may possibly lead to future major incidents. Hence, the gathering and classification of such information in order to predict damages due to the event, is vital. Also, this information must be collected from the most detailed analysis such as the response of all components of a complicated system against the incidents to most general information such as the culture of society and population density. Therefore, there are lot of uncertainties in dealing with risk assessment methodologies.

Contrary to risk analysis, which begins with the identification of hazards and characterization of probabilities (Golara, 2014), resilience analysis enhances the system response to surprise events. Due to the tight coupling of complex systems, the adverse impacts of a failure in one engineered system may propagate, and possibly amplify, through a number of other connected systems (Vespignani, 2010). Recently, several unprecedented accidents, including the Deepwater Horizon oil spill in 2010 and the Fukushima Daiichi nuclear disaster in 2011, have prompted the need for resilience of infrastructure systems and communities (Alderson et al., 2014). The April 2013 attack on the Pacific Gas and Electric Metcalf electricity substation in California (Parfomak, 2014) as well as the explosion of a high-pressure pipeline that carries natural gas from Iran to Turkey in 2015, serve as a reminder that deliberate threats to infrastructures still exist. Scholars or institutes from various fields have defined the term “Resilience”, in different ways (e.g. Holling, 1973; Haimes, 2009; Aven, 2011; Bruneau et al., 2003; Kahan et al., 2009; and Vugrin et al., 2010).

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