IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i16p6593-d1219322.html
   My bibliography  Save this article

Stormwater Infrastructure Resilience Assessment against Seismic Hazard Using Bayesian Belief Network

Author

Listed:
  • Maryam Garshasbi

    (Industrial Systems Engineering, University of Regina, Regina, SK S4S 0A2, Canada)

  • Golam Kabir

    (Industrial Systems Engineering, University of Regina, Regina, SK S4S 0A2, Canada)

  • Subhrajit Dutta

    (Department of Civil Engineering, National Institute of Technology Silchar, Silchar 781017, India)

Abstract

Resilient stormwater infrastructure is one of the fundamental components of resilient and sustainable cities. For this, the resilience assessment of stormwater infrastructure against earthquake hazards is crucial for municipal authorities. The objective of this study is to develop a resilience assessment framework for stormwater pipe infrastructure against seismic hazards. A Bayesian belief network (BBN)-based stormwater infrastructure resilience model is constructed based on the published literature and expert knowledge. The developed framework is implemented in the city of Regina, Canada, to assess the city’s stormwater pipe infrastructure resilience. The outcome of the model indicates that proposed BBN-based stormwater infrastructure resilience model can effectively quantify uncertainties and handle the nonlinear relationships between several reliability and recovery factors. The model is also capable of identifying the most sensitive and vulnerable stormwater pipes within the network.

Suggested Citation

  • Maryam Garshasbi & Golam Kabir & Subhrajit Dutta, 2023. "Stormwater Infrastructure Resilience Assessment against Seismic Hazard Using Bayesian Belief Network," IJERPH, MDPI, vol. 20(16), pages 1-19, August.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:16:p:6593-:d:1219322
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/16/6593/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/16/6593/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ouyang, Min & Wang, Zhenghua, 2015. "Resilience assessment of interdependent infrastructure systems: With a focus on joint restoration modeling and analysis," Reliability Engineering and System Safety, Elsevier, vol. 141(C), pages 74-82.
    2. Ramírez, Pedro A. Pérez & Utne, Ingrid Bouwer, 2015. "Use of dynamic Bayesian networks for life extension assessment of ageing systems," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 119-136.
    3. Heather J. Murdock & Karin M. De Bruijn & Berry Gersonius, 2018. "Assessment of Critical Infrastructure Resilience to Flooding Using a Response Curve Approach," Sustainability, MDPI, vol. 10(10), pages 1-22, September.
    4. Tien, Iris & Der Kiureghian, Armen, 2016. "Algorithms for Bayesian network modeling and reliability assessment of infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 134-147.
    5. Maryam Garshasbi & Golam Kabir, 2022. "Earthquake Resilience Framework for a Stormwater Pipe Infrastructure System Integrating the Best Worst Method and Dempster–Shafer Theory," Sustainability, MDPI, vol. 14(5), pages 1-29, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    2. Jingjing Kong & Slobodan P. Simonovic & Chao Zhang, 2019. "Resilience Assessment of Interdependent Infrastructure Systems: A Case Study Based on Different Response Strategies," Sustainability, MDPI, vol. 11(23), pages 1-31, November.
    3. Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "The Resilience of Critical Infrastructure Systems: A Systematic Literature Review," Energies, MDPI, vol. 14(6), pages 1-32, March.
    4. Maryam Garshasbi & Golam Kabir, 2022. "Earthquake Resilience Framework for a Stormwater Pipe Infrastructure System Integrating the Best Worst Method and Dempster–Shafer Theory," Sustainability, MDPI, vol. 14(5), pages 1-29, February.
    5. Chemweno, Peter & Pintelon, Liliane & Muchiri, Peter Nganga & Van Horenbeek, Adriaan, 2018. "Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 64-77.
    6. Zhang, Mimi & Gaudoin, Olivier & Xie, Min, 2015. "Degradation-based maintenance decision using stochastic filtering for systems under imperfect maintenance," European Journal of Operational Research, Elsevier, vol. 245(2), pages 531-541.
    7. Trucco, Paolo & Petrenj, Boris, 2023. "Characterisation of resilience metrics in full-scale applications to interdependent infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    8. Hao, Yucheng & Jia, Limin & Zio, Enrico & Wang, Yanhui & Small, Michael & Li, Man, 2023. "Improving resilience of high-speed train by optimizing repair strategies," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    9. Sajid, Zaman, 2021. "A dynamic risk assessment model to assess the impact of the coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    10. Yang, Bofan & Zhang, Lin & Zhang, Bo & Xiang, Yang & An, Lei & Wang, Wenfeng, 2022. "Complex equipment system resilience: Composition, measurement and element analysis," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    11. Zou, Qiling & Chen, Suren, 2019. "Enhancing resilience of interdependent traffic-electric power system," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    12. Wang, Zeyu & Shafieezadeh, Abdollah, 2020. "Real-time high-fidelity reliability updating with equality information using adaptive Kriging," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    13. Liu, Huan & Tatano, Hirokazu & Pflug, Georg & Hochrainer-Stigler, Stefan, 2021. "Post-disaster recovery in industrial sectors: A Markov process analysis of multiple lifeline disruptions," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    14. Jingjing Kong & Chao Zhang & Slobodan P. Simonovic, 2019. "A Two-Stage Restoration Resource Allocation Model for Enhancing the Resilience of Interdependent Infrastructure Systems," Sustainability, MDPI, vol. 11(19), pages 1-16, September.
    15. Kameshwar, Sabarethinam & Cox, Daniel T. & Barbosa, Andre R. & Farokhnia, Karim & Park, Hyoungsu & Alam, Mohammad S. & van de Lindt, John W., 2019. "Probabilistic decision-support framework for community resilience: Incorporating multi-hazards, infrastructure interdependencies, and resilience goals in a Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    16. Mrinal Kanti Sen & Subhrajit Dutta & Golam Kabir, 2021. "Flood Resilience of Housing Infrastructure Modeling and Quantification Using a Bayesian Belief Network," Sustainability, MDPI, vol. 13(3), pages 1-24, January.
    17. Lu, Qing-Chang & Xu, Peng-Cheng & Zhao, Xiangmo & Zhang, Lei & Li, Xiaoling & Cui, Xin, 2022. "Measuring network interdependency between dependent networks: A supply-demand-based approach," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    18. Han, Lin & Zhao, Xudong & Chen, Zhilong & Gong, Huadong & Hou, Benwei, 2021. "Assessing resilience of urban lifeline networks to intentional attacks," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    19. Bibartiu, Otto & Dürr, Frank & Rothermel, Kurt & Ottenwälder, Beate & Grau, Andreas, 2021. "Scalable k-out-of-n models for dependability analysis with Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    20. Fang, Yi-Ping & Sansavini, Giovanni, 2019. "Optimum post-disruption restoration under uncertainty for enhancing critical infrastructure resilience," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 1-11.

    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:gam:jijerp:v:20:y:2023:i:16:p:6593-:d:1219322. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.