IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v589y2022ics0378437121008876.html
   My bibliography  Save this article

Performance of occupant evacuation in a super high-rise building up to 583 m

Author

Listed:
  • Huang, Zhongyi
  • Fan, Rui
  • Fang, Zhiming
  • Ye, Rui
  • Li, Xiaolian
  • Xu, Qingfeng
  • Gao, Huisheng
  • Gao, Yan

Abstract

The stairwell is the main evacuation channel of super high-rise buildings, so revealing the evacuation characteristics on stairs in such buildings based on a full-scale experiment is critical for safer evacuation. However, currently there are few studies focusing on the evacuation performance of crowd in such buildings, especially for the collective movement scenarios. Here, an evacuation experiment is carried out in Shanghai Tower with a vertical height of 583 m, which is the second tallest building in the world. The evacuation speeds for 69 participants in 58 stair sections are extracted and the effects of travel distance, gender, age and density on descent speeds are analyzed and discussed. According to the result that the group of participants with a 9.63% higher travel height spends a 16.39% longer evacuation time, yet within each group the speed does not decrease with the increase of the moving distance, we propose an interesting hypothesis that the travel distance may affect descent speed, but it needs to be further verified. The speeds of the female are significantly lower than those of the male and the female are more sensitive to the increase of travel distance. At the same time, younger participants show better evacuation ability than the older ones, including that they evacuate faster and are less affected by the confluence. Furthermore, a new method is proposed to calculate density and the fundamental diagram These results are useful for the validation and calibration of related evacuation models, and can provide basic data for the design of emergency evacuation facilities in super high-rise buildings.

Suggested Citation

  • Huang, Zhongyi & Fan, Rui & Fang, Zhiming & Ye, Rui & Li, Xiaolian & Xu, Qingfeng & Gao, Huisheng & Gao, Yan, 2022. "Performance of occupant evacuation in a super high-rise building up to 583 m," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
  • Handle: RePEc:eee:phsmap:v:589:y:2022:i:c:s0378437121008876
    DOI: 10.1016/j.physa.2021.126643
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437121008876
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2021.126643?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. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    2. Ma, Yaping & Li, Lihua & Zhang, Hui & Chen, Tao, 2017. "Experimental study on small group behavior and crowd dynamics in a tall office building evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 488-500.
    3. Zeng, Yiping & Song, Weiguo & Jin, Sha & Ye, Rui & Liu, Xiaodong, 2017. "Experimental study on walking preference during high-rise stair evacuation under different ground illuminations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 26-37.
    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. Guo, Ning & Ling, Xiang & Ding, Zhongjun & Long, Jiancheng & Zhu, Kongjin, 2019. "An improved heuristic-based model to reproduce pedestrian dynamic on the single-file staircase," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    2. Subramanian, Gayathri Harihara & Choubey, Nipun & Verma, Ashish, 2022. "Modelling and simulating serpentine group behaviour in crowds using modified social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    3. Liu, Yixue & Mao, Zhanli, 2022. "An experimental study on the critical state of herd behavior in decision-making of the crowd evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    4. Fu, Libi & Shi, Qingxin & Qin, Huigui & Zhang, Ying & Shi, Yongqian, 2022. "Analysis of movement behavior of pedestrian social groups through a bottleneck," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    5. Murilo S Baptista & Hai-Peng Ren & Johen C M Swarts & Rodrigo Carareto & Henk Nijmeijer & Celso Grebogi, 2012. "Collective Almost Synchronisation in Complex Networks," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-11, November.
    6. Chen, Changkun & Sun, Huakai & Lei, Peng & Zhao, Dongyue & Shi, Congling, 2021. "An extended model for crowd evacuation considering pedestrian panic in artificial attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    7. Ma, Jian & Song, Wei-guo & Zhang, Jun & Lo, Siu-ming & Liao, Guang-xuan, 2010. "k-Nearest-Neighbor interaction induced self-organized pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2101-2117.
    8. Zheng, Yaochen & Chen, Jianqiao & Wei, Junhong & Guo, Xiwei, 2012. "Modeling of pedestrian evacuation based on the particle swarm optimization algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4225-4233.
    9. Yue, Hao & Zhang, Junyao & Chen, Wenxin & Wu, Xinsen & Zhang, Xu & Shao, Chunfu, 2021. "Simulation of the influence of spatial obstacles on evacuation pedestrian flow in walking facilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    10. Shiwakoti, Nirajan & Sarvi, Majid, 2013. "Understanding pedestrian crowd panic: a review on model organisms approach," Journal of Transport Geography, Elsevier, vol. 26(C), pages 12-17.
    11. Krbálek, Milan & Hrabák, Pavel & Bukáček, Marek, 2018. "Pedestrian headways — Reflection of territorial social forces," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 38-49.
    12. Liu, Qian, 2018. "A social force model for the crowd evacuation in a terrorist attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 315-330.
    13. Lian, Liping & Song, Weiguo & Yuen, Kwok Kit Richard & Telesca, Luciano, 2018. "Investigating the time evolution of some parameters describing inflow processes of pedestrians in a room," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 77-88.
    14. Zheng, Xiaoping & Cheng, Yuan, 2011. "Conflict game in evacuation process: A study combining Cellular Automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1042-1050.
    15. Bao, Yu & Huo, Feizhou, 2021. "An agent-based model for staircase evacuation considering agent’s rotational behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    16. Mohammed Mahmod Shuaib, 2016. "Modeling the Pedestrian Ability of Detecting Lanes and Lane Changing Behavior," Modern Applied Science, Canadian Center of Science and Education, vol. 10(7), pages 1-1, July.
    17. Shao, Zhi-Gang & Yang, Yan-Yan, 2015. "Effective strategies of collective evacuation from an enclosed space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 34-39.
    18. Andrea Cavagna & Antonio Culla & Xiao Feng & Irene Giardina & Tomas S. Grigera & Willow Kion-Crosby & Stefania Melillo & Giulia Pisegna & Lorena Postiglione & Pablo Villegas, 2022. "Marginal speed confinement resolves the conflict between correlation and control in collective behaviour," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    19. Zhang, Yihao & Chai, Zhaojie & Lykotrafitis, George, 2021. "Deep reinforcement learning with a particle dynamics environment applied to emergency evacuation of a room with obstacles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    20. Daganzo, Carlos F., 2007. "Urban gridlock: Macroscopic modeling and mitigation approaches," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 49-62, January.

    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:phsmap:v:589:y:2022:i:c:s0378437121008876. 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: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.