Modeling the recovery process: A key dimension of resilience. (October 2019)
- Record Type:
- Journal Article
- Title:
- Modeling the recovery process: A key dimension of resilience. (October 2019)
- Main Title:
- Modeling the recovery process: A key dimension of resilience
- Authors:
- Cassottana, Beatrice
Shen, Lijuan
Tang, Loon Ching - Abstract:
- Abstract: The recovery process is a key determinant of system resilience because it describes the capability of a system to restore its performance after a disruption. In this work, we construct recovery functions that satisfy the necessary conditions to model the performance of critical infrastructure systems over time, during periods of loss and restoration following a disruptive event. To characterize the responses by various systems, we estimate the parameters of those functions by using empirical data about major infrastructure disruptions, including their recovery processes. The validity of our procedure is then illustrated by applying data from the three major utility companies that served New Jersey in the aftermath of Hurricane Sandy. Models are selected via standard methods to compare those recovery processes. Our results indicate that the recovery functions proposed here can capture the sensitivity of a system response to key parameters, thereby supporting the design of a more resilient system.
- Is Part Of:
- Reliability engineering & system safety. Volume 190(2019)
- Journal:
- Reliability engineering & system safety
- Issue:
- Volume 190(2019)
- Issue Display:
- Volume 190, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 190
- Issue:
- 2019
- Issue Sort Value:
- 2019-0190-2019-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-10
- Subjects:
- Resilience -- Recovery -- Performance function
Reliability (Engineering) -- Periodicals
System safety -- Periodicals
Industrial safety -- Periodicals
Fiabilité -- Périodiques
Sécurité des systèmes -- Périodiques
Sécurité du travail -- Périodiques
620.00452 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09518320 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ress.2019.106528 ↗
- Languages:
- English
- ISSNs:
- 0951-8320
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7356.422700
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 10934.xml