IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i16p4177-d398347.html
   My bibliography  Save this article

Modification of Interaction Forces between Smoke and Evacuees

Author

Listed:
  • Sungryong Bae

    (Department of Advanced Industry Convergence, Chosun University, Gwangju 61452, Korea)

  • Jun-Ho Choi

    (Division of Architectural and Fire Protection Engineering, Pukyong National University, Busan 48513, Korea)

  • Hong Sun Ryou

    (School of Mechanical Engineering, Chung-Ang University, Seoul 06974, Korea)

Abstract

The most used fire effect models on evacuees are only focused on the physical capacity of the evacuees. However, some of the evacuees in a fire situation continuously move through the familiar route, although the familiar route is smoke-filled and they know that they are moving towards the fire source. Thus, the additional evacuation models are required for considering the behavioral changes due to the psychological pressure when the evacuees are moving through the smoke or towards the fire source. In this study, the inner smoke region force is modified to improve the accuracy and practicality of the BR-smoke model by varying the walking speed according to the smoke density. Additionally, the BR-smoke model is applied to FDS+Evac to compare the simulation results of the modified BR-smoke model with those of existing models. Based on the results, the evacuation characteristics inside the smoke region can be improved by using the modified BR-smoke model because the evacuees are continuously influenced by the modified inner smoke force inside the smoke region. However, additional studies for determining more reliable evacuee psychological factors are required to improve the reality of the modified BR-smoke model.

Suggested Citation

  • Sungryong Bae & Jun-Ho Choi & Hong Sun Ryou, 2020. "Modification of Interaction Forces between Smoke and Evacuees," Energies, MDPI, vol. 13(16), pages 1-10, August.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4177-:d:398347
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/16/4177/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/16/4177/
    Download Restriction: no
    ---><---

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pengcheng Qin & Mingnian Wang & Zhanwen Chen & Guanfeng Yan & Tao Yan & Changling Han & Anmin Wang, 2021. "Effects of Ambient Pressure on Burning Characteristics of Gasoline: A Pilot Study," Energies, MDPI, vol. 14(15), pages 1-12, July.
    2. Haotian Zheng & Shuchuan Zhang & Junqi Zhu & Ziyan Zhu & Xin Fang, 2022. "Evacuation in Buildings Based on BIM: Taking a Fire in a University Library as an Example," IJERPH, MDPI, vol. 19(23), pages 1-21, December.

    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. 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.
    2. 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).
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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).
    15. Daganzo, Carlos F., 2007. "Urban gridlock: Macroscopic modeling and mitigation approaches," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 49-62, January.
    16. Ma, Liang & Chen, Bin & Wang, Xiaodong & Zhu, Zhengqiu & Wang, Rongxiao & Qiu, Xiaogang, 2019. "The analysis on the desired speed in social force model using a data driven approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 894-911.
    17. Wan, Jiahui & Sui, Jie & Yu, Hua, 2014. "Research on evacuation in the subway station in China based on the Combined Social Force Model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 33-46.
    18. Hu, Xiangmin & Chen, Tao & Deng, Kaifeng & Wang, Guanning, 2023. "Effects of aggressiveness on pedestrian room evacuation using extended cellular automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    19. Li, Jun & Fu, Siyao & He, Haibo & Jia, Hongfei & Li, Yanzhong & Guo, Yi, 2015. "Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 304-321.
    20. Minsung Kim & Minki Kim, 2014. "Group-Wise Herding Behavior in Financial Markets: An Agent-Based Modeling Approach," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-7, April.

    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:jeners:v:13:y:2020:i:16:p:4177-:d:398347. 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.