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Seismic Risk Mitigation for a Portfolio of Reinforced Concrete Frame Buildings through Optimal Allocation of a Limited Budget

Author(s):


Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2018
Page(s): 1-18
DOI: 10.1155/2018/8184756
Abstract:

The mitigation of seismic risk for a population of vulnerable civil critical structures (e.g., hospitals, schools, and bridges) is a crucial issue for many governments of earthquake-prone regions. Furthermore, owing to the global economic crisis, limited financial resources make full seismic rehabilitation of entire building stocks challenging. Therefore, a critical decision has to be made on the following key question: what is the most advantageous way of spending the available budget while treating each building in a portfolio differently, by giving it a different level of structural improvement to reduce the overall risk of the portfolio of buildings as much as possible? Herein, a decision-making tool is proposed to address this high-social-impact issue. Starting with a limited amount of information, which is gathered through expeditious surveys on existing buildings, and by involving uncertainties, the overall risk is evaluated from the fragility analysis of each structure. This is conducted via simplified pushover analyses by considering the local seismic hazard. Then, an optimization is performed for each building of the portfolio to select a relevant structural intervention from four alternatives (no intervention, partial retrofit, full retrofit, and demolition and reconstruction), based on both the overall risk reduction and the amount of financial resources. Procedures for quick estimation of fragility curves and installation costs are also discussed as part of the proposed approach. Finally, a practical application is presented with reference to a simulated case study consisting of 46 reinforced concrete school buildings located in Campania, Italy.

Copyright: © 2018 Nicola Caterino et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10176419
  • Published on:
    30/11/2018
  • Last updated on:
    02/06/2021
 
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