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An open-source toolbox for investigating functional resilience in sewer networks based on global resilience analysis

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posted on 2025-08-01, 13:40 authored by B Kamali, AN Ziaei, A Beheshti, R Farmani
Resilience analysis of urban infrastructures such as sewerage systems is very important due to different stressors. Failure in these infrastructures may lead to economic, social, health and environmental consequences. The functional resilience of systems can be analyzed in all failure levels caused by unpredictable or even unknown events based on the global resilience analysis (GRA) method. To perform GRA under different scenarios of pipe collapse and blockage, the performance of the system must be evaluated in all possible link failure combinations. The time of this process might be unfeasibly long in real sewerage networks. In this paper, an open-source toolbox is developed which uses a proposed scenario selection method based on roulette wheel to perform GRA without simulating all possible scenarios. This toolbox is based on a proposed O-SWMM API which is a developed version of EPA's Storm Water Management Model (SWMM) to optimize simulation time and memory usage. The results show that the mean resilience for a sample and also a real sewer network was estimated by the proposed method with RMSE less than 0.025 and 0.022 respectively comparing with simulating all possible scenarios. Moreover, the GRA computation using O-SWMM API was at least 2.26 times faster than SWMM.exe.

Funding

IF\192057

Royal Academy of Engineering (RAE)

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© 2021 Elsevier Ltd. This version is made available under the CC-BY-NC-ND 4.0 license: https://creativecommons.org/licenses/by-nc-nd/4.0/

Notes

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record

Journal

Reliability Engineering and System Safety

Publisher

Elsevier / European Safety and Reliability Association / Safety Engineering and Risk Analysis Division

Version

  • Accepted Manuscript

Language

en

FCD date

2022-01-04T11:43:22Z

FOA date

2022-11-14T00:00:00Z

Citation

Vol. 218 (B), article 108201

Department

  • Engineering

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