eprintid: 10178164
rev_number: 11
eprint_status: archive
userid: 699
dir: disk0/10/17/81/64
datestamp: 2023-10-04 09:31:06
lastmod: 2024-11-20 07:10:04
status_changed: 2023-10-04 09:31:06
type: article
metadata_visibility: show
sword_depositor: 699
creators_name: Opabola, Eyitayo A
creators_name: Galasso, Carmine
title: A probabilistic framework for post-disaster recovery modeling of buildings and electric power networks in developing countries
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F44
keywords: post-earthquake recovery, developing countries, resilience, electric power networks, decision support
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: Post-disaster recovery is a significant challenge, especially in developing countries. Various technical, environmental, socioeconomic, political, and cultural factors substantially influence post-disaster recovery. As a result, methodologies relevant in developed nations may not be directly applicable in Global South contexts. This study introduces a probabilistic framework for modeling the post-disaster recovery of buildings and electric power networks (EPN) in developing countries. The proposed framework combines a building-level assessment of individual assets with a community-level assessment of EPNs to evaluate a building portfolio's post-event functionality state. As part of the framework, a stochastic network analysis approach is proposed to estimate the recovery time of damaged buildings while accounting for technical, environmental, socioeconomic, political, and cultural factors, quantified using data gathered from past events. Similarly, a probabilistic modeling approach is proposed to quantify the EPN's initial post-event outage levels. Specifically, empirical formulations for estimating the recovery time of an EPN as a function of its initial post- event outage levels are calibrated using post-event data from developing countries. A case study is presented to illustrate the application of the proposed framework to model the post-earthquake recovery of a synthetic low-income residential community. The analysis showed that negative technical, environmental, socioeconomic, political, and cultural factors could amplify the reconstruction time of damaged buildings by a factor of almost three. The proposed framework can support decision-makers in disaster planning and management strategies for vulnerable low-income communities.
date: 2024-02
date_type: published
publisher: Elsevier
official_url: https://doi.org/10.1016/j.ress.2023.109679
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 2092251
doi: 10.1016/j.ress.2023.109679
lyricists_name: Opabola, Eyitayo Ademola
lyricists_id: EOPAB27
actors_name: Flynn, Bernadette
actors_id: BFFLY94
actors_role: owner
full_text_status: public
publication: Reliability Engineering and System Safety
volume: 242
article_number: 109679
issn: 0951-8320
citation:        Opabola, Eyitayo A;    Galasso, Carmine;      (2024)    A probabilistic framework for post-disaster recovery modeling of buildings and electric power networks in developing countries.                   Reliability Engineering and System Safety , 242     , Article 109679.  10.1016/j.ress.2023.109679 <https://doi.org/10.1016/j.ress.2023.109679>.       Green open access   
 
document_url: https://discovery-pp.ucl.ac.uk/id/eprint/10178164/1/1-s2.0-S0951832023005938-main.pdf