scholarly journals Resilience Assessment: A Performance-Based Importance Measure

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7575
Author(s):  
Ali Nouri Qarahasanlou ◽  
Ali Zamani ◽  
Abbas Barabadi ◽  
Mahdi Mokhberdoran
Keyword(s):  
Risk Factors ◽  
Dynamic Stress ◽  
Importance Measure ◽  
Critical Infrastructures ◽  
System Configuration ◽  
Operational Conditions ◽  
Resilience Management ◽  
Critical Components ◽  
Resilience Assessment

The resilience of a system can be considered as a function of its reliability and recoverability. Hence, for effective resilience management, the reliability and recoverability of all components which build up the system need to be identified. After that, their importance should be identified using an appropriate model for future resource allocation. The critical infrastructures are under dynamic stress due to operational conditions. Such stress can significantly affect the recoverability and reliability of a system‘s components, the system configuration, and consequently, the importance of components. Hence, their effect on the developed importance measure needs to be identified and then quantified appropriately. The dynamic operational condition can be modeled using the risk factors. However, in most of the available importance measures, the effect of risk factors has not been addressed properly. In this paper, a reliability importance measure has been used to determine the critical components considering the effect of risk factors. The application of the model has been shown through a case study.

scholarly journals Resilience Assessment and Importance Measure for Interdependent Critical Infrastructures

2021 ◽  
Author(s):  
Xing Liu ◽  
Yiping Fang ◽  
Elisa Ferrario ◽  
Enrico Zio
Keyword(s):  
Distribution System ◽  
Dynamic Modelling ◽  
Recovery Phase ◽  
Decision Makers ◽  
Importance Measure ◽  
Critical Infrastructures ◽  
System Protection ◽  
Modelling Framework ◽  
Resilience Indicators

Abstract Based upon a novel control-based dynamic modelling framework, this paper proposes two new indicators, i.e., resilience by mitigation and resilience by recovery, for the resilience analysis of interdependent critical infrastructures (ICIs) under disruptions. The former is built from the protection activities before and during the mitigation phase of a disruptive event, and the latter is the result of the restoration efforts which take place at the recovery phase. The total resilience of ICIs combines both of these two aspects by taking into account the preferences of the decision-makers. We demonstrate the applicability of the proposed modelling framework and metrics in a case study involving ICIs made of a power grid and a gas distribution system. Owing to the new resilience indicators, the priorities of subsystems and links within ICIs at different phases can be ranked, therefore different resilience strategies at different phases of disruptive events are compared. The results show that proposed metrics can be used by stakeholders of ICIs on improving the effectiveness of system protection measurements.

scholarly journals Bearing Severity Fault Evaluation Using Contour Maps—Case Study

2021 ◽  
Vol 11 (14) ◽  
pp. 6452
Author(s):  
César Ricardo Soto-Ocampo ◽  
Juan David Cano-Moreno ◽  
José Manuel Mera ◽  
Joaquín Maroto
Keyword(s):  
Health Indicators ◽  
Bearing Faults ◽  
Contour Maps ◽  
Initial Stage ◽  
Critical Components ◽  
Bearing Damage ◽  
First Time ◽  
Current Operating

Increasing industrial competitiveness has led to an increased global interest in condition monitoring. In this sector, rotating machinery plays an important role, where the bearing is one of the most critical components. Many vibration-based signal treatments are already being used to identify features associated with bearing faults. The information embedded in such features are employed in the construction of health indicators, which allow for evaluation of the current operating status of the machine. In this work, the use of contour maps to represent the diagnosis map of a bearing, used as a health map, is presented for the first time. The results show that the proposed method is promising, allowing for the satisfactory detection and evaluation of the severity of bearing damage. In this initial stage of the research, our results suggest that this method can improve the classification of bearing faults and, therefore, optimise maintenance processes.

scholarly journals Quantitative method for resilience assessment framework of airport network during COVID-19

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260940
Author(s):  
Jiuxia Guo ◽  
Yang Li ◽  
Zongxin Yang ◽  
Xinping Zhu
Keyword(s):  
Complex Network ◽  
Small World ◽  
Global Scale ◽  
Assessment Framework ◽  
Small World Networks ◽  
Scale Free ◽  
Global Pandemic ◽  
Network Metrics ◽  
Resilience Assessment

The resilience and vulnerability of airport networks are significant challenges during the COVID-19 global pandemic. Previous studies considered node failure of networks under natural disasters and extreme weather. Herein, we propose a complex network methodology combined with data-driven to assess the resilience of airport networks toward global-scale disturbance using the Chinese airport network (CAN) and the European airport network (EAN) as a case study. The assessment framework includes vulnerability and resilience analyses from the network- and node-level perspectives. Subsequently, we apply the framework to analyze the airport networks in China and Europe. Specifically, real air traffic data for 232 airports in China and 82 airports in Europe are selected to form the CAN and EAN, respectively. The complex network analysis reveals that the CAN and the EAN are scale-free small-world networks, that are resilient to random attacks. However, the connectivity and vulnerability of the CAN are inferior to those of the EAN. In addition, we select the passenger throughput from the top-50 airports in China and Europe to perform a comparative analysis. By comparing the resilience evaluation of individual airports, we discovered that the factors of resilience assessment of an airport network for global disturbance considers the network metrics and the effect of government policy in actual operations. Additionally, this study also proves that a country’s emergency response-ability towards the COVID-19 has a significantly affectes the recovery of its airport network.

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