IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-3-319-52425-2_21.html
   My bibliography  Save this book chapter

Fragility Curves of Restoration Processes for Resilience Analysis

In: Risk and Reliability Analysis: Theory and Applications

Author

Listed:
  • Gian Paolo Cimellaro

    (Politecnico di Torino)

Abstract

In literature the fragility curves are usually adopted to evaluate the probability of exceedance of a given damage state. This chapter presents for the first time a procedure for developing fragility curves of restoration processes which can be adopted for resilience analysis. The restoration process describes the capacity to recover from a system failure and it is one of the most uncertain variables in the resilience analysis therefore, the problem should be treated in probabilistic terms. In the chapter, a method is proposed for evaluating the Restoration Fragility Functions (RFF) of a given system following an extreme event. The restoration curves have been built empirically using the data obtained by a discrete event simulation model of the system considered. Different restoration processes obtained through Monte Carlo simulations have been analyzed statistically to determine the probability of exceedance of a given restoration state. Then, Restoration Fragility Functions (RFF) are obtained using the Maximum Likelihood Estimation (MLE) approach assuming a lognormal cumulative distribution function. The method has been applied to an Emergency Department of a hospital during a crisis, because these buildings are critical facilities which should withstand after an earthquake in order to assist injuries. Two different case studies have been compared: the Emergency Department (ED) with and without emergency plan.

Suggested Citation

  • Gian Paolo Cimellaro, 2017. "Fragility Curves of Restoration Processes for Resilience Analysis," Springer Series in Reliability Engineering, in: Paolo Gardoni (ed.), Risk and Reliability Analysis: Theory and Applications, pages 495-507, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-319-52425-2_21
    DOI: 10.1007/978-3-319-52425-2_21
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ssrchp:978-3-319-52425-2_21. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.