Statistical Approach to Quantifying the Destructive Impact of Natural Disasters on Petroleum Infrastructures

Ilbeigi, Mohammad; Dilkina, Bistra

doi:10.1061/(asce)me.1943-5479.0000566

Cited by 29 publications

(3 citation statements)

References 13 publications

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“…Delays in the reconstruction of transportation infrastructure after a hurricane also slow down the reconstruction of other sectors, as it is the common denominator of all the damaged areas and its disruption affects all of them (Ilbeigi and Dislkina, 2017). For instance, due to the transportation infrastructure collapse caused by the 1994 Northridge earthquake, 27.3% of the businesses were shut down and 22% of the people in the community lost their jobs (Heaney et al.…”

Section: Literature Reviewmentioning

confidence: 99%

Key components of successful post–hurricane reconstruction of transportation infrastructures

Safapour

Kermanshachi

Rouhanizadeh

2022

BEPAM

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PurposeIn the aftermath of hurricanes, the damage levied on transportation infrastructures increases the timeliness of emergency responses and recovery procedures, making it essential that they are reconstructed as quickly as possible – on time and within budget. The aim of this study was to determine significant performance indicators (PIs) that considerably affect cost and schedule performance as well as reworks in post–hurricane reconstruction of transportation infrastructure including highways, bridges, roadways, etc. Additionally, the determined PIs were clustered to investigate key components.Design/methodology/approachThe root causes of reconstruction projects' poor performance were identified through the existing literature, and 30 transportation infrastructure case studies were analyzed to determine the significant PIs that corresponded to cost, schedule performance and reworks. The factor analysis method was used to cluster the significant PIs and determine the key components affecting them.FindingsEight key components were found for cost, eight for schedule performance and six for reworks. The key components of cost performance are shortage of resources, information management, coordination, safety, location, quality of materials, quality of resources and project complexity. The key components of reconstruction schedule performance are human resources, risk management, work suspension, material resources, productivity, on-site inspections, geometrical characteristics and level of reconstruction complexity. The six key components of reconstruction reworks are logistic management, pace of decision-making, accommodation for staff, environmental issues, available temporary paths and volume of debris.Originality/valueThe outcomes of this research will assist authorities and decision makers in identifying and evaluating the critical root causes of poor cost performance, poor schedule performance and reworks and will enable them to facilitate the timely and effective allocation of resources.

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Section: Literature Reviewmentioning

confidence: 99%

Key components of successful post–hurricane reconstruction of transportation infrastructures

Safapour

Kermanshachi

Rouhanizadeh

2022

BEPAM

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“…Qiao et al (2019)), and the oil and gas industry (e.g. Ilbeigi & Dilkina (2017)) -underlining the broad application area of such methods. However, as mentioned in the introductory section, these studies do not consider the effect of unobserved risk factors.…”

Section: Prediction and Modelling Of Resilience And Recoverymentioning

confidence: 99%

Recoverability Modeling of Power Distribution Systems Using Accelerated Life Models: Case of Power Cut due to Extreme Weather Events in Norway

2020

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Today's societies rely on electrical power distribution systems. Recent weather events have illustrated that the loss of such service can lead to severe consequences for societies and stakeholders. Hence, in order to reduce the impact of such extreme events on infrastructure systems and to limit the associated losses, it is crucial to design infrastructure that can bounce back and recover rapidly after disruptions (i.e. to be resilient). In this regard, it is vital to have knowledge of technical, organizational, internal, and external factors that influence the infrastructure's recovery process. These factors can broadly be categorized into two different groups, namely observed and unobserved risk factors. In most studies on resilience, the effect of unobserved covariates is neglected. This may lead to erroneous model selection for analyzing the time to recovery of the disrupted infrastructure, as well as wrong conclusions and thus decisions. The aim of this paper is to identify the risk factors (observed and unobserved) affecting the recovery process of disrupted infrastructure. To this aim, the paper extends the application of accelerated failure time (AFT) models, to model the recovery time of disrupted critical infrastructures in the presence of unobserved and observed risk factors. This model can be used to analyse how important these factors are from the viewpoint of resource allocation and decision-making. The application and implications of the model are presented in a case study, from both technical and management perspectives. The case study investigated in this paper applies the developed model, analysing recovery times from 73 disruption reports on Norwegian electric power distribution grids after four major extreme weather events. The analysis indicates that failures in the regional grid, natural conditions, area affected, and failures in operational control system have a significant impact on the recovery process.

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“…Herein, resilience is understood as a threefold concept: (i) the capacity to absorb a shock or disturbance; (ii) the capacity to adapt to change; and (iii) the rapidity of the recovery process (Francis and Bekera 2014;Mattsson and Jenelius 2015). Over the last two decades many studies focussed primarily on a rapid recovery to a pre-disaster state (Cimellaro et al 2010;Comes and de Walle 2014;Janić 2015;Zobel 2011;Ilbeigi and Dilkina 2018). A comprehensive recent review by (Hosseini et al 2016) provides an overview of applications and adaptations on this initial model.…”

Section: Resilience and Rapid Adaptation Frameworkmentioning

confidence: 99%

Critical Airport Infrastructure Disaster Resilience: A Framework and Simulation Model for Rapid Adaptation

2020

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Resilient critical airport infrastructures affected by a disaster need to sustain minimal functionality and quickly resume full operation, while at the same time coping with the increased operational demands imposed by the unfolding disaster response. In this paper, we develop a resilience framework and model-driven approach that focuses on the ability of the infrastructure to rapidly adapt to a new steady state under these conditions. This requires both the extension of capacity as well as the adaptation of key processes. Through discrete event simulations, we study the implications of different policies to improve airport resilience under different disaster impact scenarios for a stylized case. Our results show that although decision-makers may be tempted to focus on short-term measures that can be implemented immediately, resilience is improved most by a combination of rapid process changes and longer-term measures that structurally increase airport capacity.

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Statistical Approach to Quantifying the Destructive Impact of Natural Disasters on Petroleum Infrastructures

Cited by 29 publications

References 13 publications

Key components of successful post–hurricane reconstruction of transportation infrastructures

Key components of successful post–hurricane reconstruction of transportation infrastructures

Recoverability Modeling of Power Distribution Systems Using Accelerated Life Models: Case of Power Cut due to Extreme Weather Events in Norway

Critical Airport Infrastructure Disaster Resilience: A Framework and Simulation Model for Rapid Adaptation

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