Quantifying restoration time of pipelines after earthquakes

Quantifying restoration time of pipelines after earthquakes: Comparison of Bayesian belief networks and fuzzy models

De Iuliis, Melissa (Politecnico di Torino)
Kammouh, O. (TU Delft Integral Design & Management)
Cimellaro, Gian Paolo (Politecnico di Torino)
Tesfamariam, Solomon (University of British Columbia)

2021

Critical infrastructures are an integral part of our society and economy. Services like gas supply or water networks are expected to be available at all times since a service failure may incur catastrophic consequences to the public health, safety, and financial capacity of the society. Several resilience strategies have been examined to reduce disaster risk and evaluate the downtime of infrastructures following destructive events. This paper introduces an indicator-based downtime estimation model for buried infrastructures (i.e., water and gas networks). The model distinguishes the important aspects that contribute to determining the downtime of buried infrastructure following a hazardous event. The proposed downtime model relies on two inference methods for its computation, Fuzzy Logic (FL) and Bayesian Network (BN), which are adapted for the current application. Finally, through a case scenario, a comparison of the two inference methods, in terms of results and limitations, is presented. Results show that both methods incorporate intuitive knowledge and/or historical data for defining fuzzy rules (in FL) and estimating conditional probabilities (in BN). The difference stands in the interpretation of the outcome. The output of the FL is a membership that defines how well the downtime fits the fuzzy levels while the BN output is a probability distribution that represents how likely the downtime is in a certain state. Nevertheless, both approaches can be utilized by decision-makers to easily estimate the time to restore the functionality of buried infrastructures and plan preventive safety measures accordingly.

Bayesian network
Downtime
Fuzzy logic
Infrastructure
Lifelines
Resilience
Restoration

http://resolver.tudelft.nl/uuid:7444e3cc-7998-47e3-a55b-cb527f7b7aba

https://doi.org/10.1016/j.ijdrr.2021.102491

2023-08-10

2212-4209

International Journal of Disaster Risk Reduction, 64

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

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© 2021 Melissa De Iuliis, O. Kammouh, Gian Paolo Cimellaro, Solomon Tesfamariam