IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v243y2024ics095183202300772x.html
   My bibliography  Save this article

Quantifying fire resilience of buildings considering the impact of water damage accompanied by fire extinguishment

Author

Listed:
  • HIMOTO, Keisuke
  • SAWADA, Yuto
  • OHMIYA, Yoshifumi

Abstract

The primary factor that affects the functionality of buildings due to fire is the deterioration caused by heating from hot flames and smoke. The application of water, whether by occupants, firefighters or sprinkler systems, takes an important role in reducing the intensity of the fire. However, it can lead to the impairment of non-structural components, equipment systems and stored items inside the building rendering them unusable and disrupting the building's functionality for an extended period. Past studies on fire resilience have mainly focused on assessing burn losses in buildings, neglecting the consideration of water losses. This study introduces a new approach that enables a reasonable evaluation of fire resilience of buildings by accounting for the water loss accompanied by fire extinguishment. The new approach is based on the physical prediction of water spread inside the building, which involves calculation of the changes in water levels in each room over time due to transfers between rooms through openings, staircases and gaps, and absorption by room boundary members. The estimated area of water damage is then correlated statistically with the time required for functional recovery, which allows for the assessment of fire resilience. To illustrate the proposed method, we conducted a case study on a four-story office building. When the fire originated on the fourth floor, water applied to the building spread through the corridors and staircases, with the extent of water damage decreasing on the lower floors. Additionally, we employed a Monte Carlo simulation with randomly assigned fire origins to quantitatively evaluate the impact of sprinkler systems on fire resilience. Comparing burn and water losses, we found that burn losses generally exceeded water losses in many cases. However, under specific fire and water application conditions, opposite results were observed, underscoring the importance of assessing both burn and water losses simultaneously for a comprehensive evaluation of fire resilience.

Suggested Citation

  • HIMOTO, Keisuke & SAWADA, Yuto & OHMIYA, Yoshifumi, 2024. "Quantifying fire resilience of buildings considering the impact of water damage accompanied by fire extinguishment," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
  • Handle: RePEc:eee:reensy:v:243:y:2024:i:c:s095183202300772x
    DOI: 10.1016/j.ress.2023.109858
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S095183202300772X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2023.109858?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kammouh, Omar & Gardoni, Paolo & Cimellaro, Gian Paolo, 2020. "Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    2. Ferrario, E. & Poulos, A. & Castro, S. & de la Llera, J.C. & Lorca, A., 2022. "Predictive capacity of topological measures in evaluating seismic risk and resilience of electric power networks," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    3. Liu, Jin & Zhai, Changhai & Yu, Peng, 2022. "A Probabilistic Framework to Evaluate Seismic Resilience of Hospital Buildings Using Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    4. Himoto, Keisuke & Suzuki, Keichi, 2021. "Computational framework for assessing the fire resilience of buildings using the multi-layer zone model," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    5. Sun, Hao & Wang, Haiqing & Yang, Ming & Reniers, Genserik, 2022. "A STAMP-based approach to quantitative resilience assessment of chemical process systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    6. Amanda Melendez & David Caballero-Russi & Mariantonieta Gutierrez Soto & Luis Felipe Giraldo, 2022. "Computational models of community resilience," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1121-1152, March.
    7. Mottahedi, Adel & Sereshki, Farhang & Ataei, Mohammad & Qarahasanlou, Ali Nouri & Barabadi, Abbas, 2021. "Resilience estimation of critical infrastructure systems: Application of expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    8. De Iuliis, Melissa & Kammouh, Omar & Cimellaro, Gian Paolo & Tesfamariam, Solomon, 2021. "Quantifying restoration time of power and telecommunication lifelines after earthquakes using Bayesian belief network model," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    9. Xu, Min & Li, Guoyuan & Chen, Anthony, 2024. "Resilience-driven post-disaster restoration of interdependent infrastructure systems under different decision-making environments," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    10. Du, Ao & Wang, Xiaowei & Xie, Yazhou & Dong, You, 2023. "Regional seismic risk and resilience assessment: Methodological development, applicability, and future research needs – An earthquake engineering perspective," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    11. Cai, Baoping & Zhang, Yanping & Wang, Haifeng & Liu, Yonghong & Ji, Renjie & Gao, Chuntan & Kong, Xiangdi & Liu, Jing, 2021. "Resilience evaluation methodology of engineering systems with dynamic-Bayesian-network-based degradation and maintenance," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    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. Liu, Juncai & Tian, Li & Yang, Meng & Meng, Xiangrui, 2024. "Probabilistic framework for seismic resilience assessment of transmission tower-line systems subjected to mainshock-aftershock sequences," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    2. Jiang, Qiangqiang & Cai, Baoping & Zhang, Yanping & Xie, Min & Liu, Cuiwei, 2023. "Resilience assessment methodology of natural gas network system under random leakage," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    3. Liu, Jin & Zhai, Changhai & Yu, Peng, 2022. "A Probabilistic Framework to Evaluate Seismic Resilience of Hospital Buildings Using Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    4. Yin, Jiateng & Ren, Xianliang & Liu, Ronghui & Tang, Tao & Su, Shuai, 2022. "Quantitative analysis for resilience-based urban rail systems: A hybrid knowledge-based and data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    5. Sun, Hao & Wang, Haiqing & Yang, Ming & Reniers, Genserik, 2022. "A STAMP-based approach to quantitative resilience assessment of chemical process systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    6. 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).
    7. 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).
    8. Sun, Qin & Li, Hongxu & Wang, Yuzhi & Zhang, Yingchao, 2022. "Multi-swarm-based cooperative reconfiguration model for resilient unmanned weapon system-of-systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    9. Li, Chao & Diao, Yucheng & Li, Hong-Nan & Pan, Haiyang & Ma, Ruisheng & Han, Qiang & Xing, Yihan, 2023. "Seismic performance assessment of a sea-crossing cable-stayed bridge system considering soil spatial variability," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    10. Jia, Rui & Du, Kun & Song, Zhigang & Xu, Wei & Zheng, Feifei, 2024. "Scenario reduction-based simulation method for efficient serviceability assessment of earthquake-damaged water distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    11. Bhuyan, Kasturi & Sharma, Hrishikesh, 2022. "Reliability analysis & performance-based code calibration for slabs/walls of protective structures subject to air blast loading," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    12. Mottahedi, Adel & Sereshki, Farhang & Ataei, Mohammad & Qarahasanlou, Ali Nouri & Barabadi, Abbas, 2021. "Resilience estimation of critical infrastructure systems: Application of expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    13. Amanda Melendez & David Caballero-Russi & Mariantonieta Gutierrez Soto & Luis Felipe Giraldo, 2022. "Computational models of community resilience," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1121-1152, March.
    14. Kamali, Behnaz & Ziaei, Ali Naghi & Beheshti, Aliasghar & Farmani, Raziyeh, 2022. "An open-source toolbox for investigating functional resilience in sewer networks based on global resilience analysis," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    15. Yang, Sen & Zhang, Yi & Lu, Xinzheng & Guo, Wei & Miao, Huiquan, 2024. "Multi-agent deep reinforcement learning based decision support model for resilient community post-hazard recovery," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    16. Gangolu, Jaswanth & Kumar, Ajay & Bhuyan, Kasturi & Sharma, Hrishikesh, 2022. "Probabilistic demand models and performance-based fragility estimates for concrete protective structures subjected to missile impact," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    17. Ramadhani, Adhitya & Khan, Faisal & Colbourne, Bruce & Ahmed, Salim & Taleb-Berrouane, Mohammed, 2022. "Resilience assessment of offshore structures subjected to ice load considering complex dependencies," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    18. Huang, Xiubing & Wang, Naiyu, 2024. "An adaptive nested dynamic downscaling strategy of wind-field for real-time risk forecast of power transmission systems during tropical cyclones," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    19. Yu, Yaocheng & Shuai, Bin & Huang, Wencheng, 2024. "Resilience evaluation of train control on-board system based on multi-dimensional continuous-time Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    20. Wang, Ke & Liu, Jinfeng & Tian, Lai & Tan, Xianfeng & Peng, Guansheng & Qin, Tianwen & Wu, Jun, 2022. "Analyzing vulnerability of optical fiber network considering recoverability," Reliability Engineering and System Safety, Elsevier, vol. 221(C).

    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:eee:reensy:v:243:y:2024:i:c:s095183202300772x. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.