IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i17p6338-d1230403.html
   My bibliography  Save this article

Dynamic Dose-Based Emergency Evacuation Model for Enhancing Nuclear Power Plant Emergency Response Strategies

Author

Listed:
  • Huifang Miao

    (College of Energy, Xiamen University, Xiamen 361102, China
    Fujian Provincial Nuclear Energy Engineering Technology Research Center, Xiamen 361005, China)

  • Guoming Zhang

    (College of Energy, Xiamen University, Xiamen 361102, China)

  • Peizhao Yu

    (College of Energy, Xiamen University, Xiamen 361102, China)

  • Chunsen Shi

    (College of Energy, Xiamen University, Xiamen 361102, China)

  • Jianxiang Zheng

    (College of Energy, Xiamen University, Xiamen 361102, China
    Fujian Provincial Nuclear Energy Engineering Technology Research Center, Xiamen 361005, China)

Abstract

The safe evacuation of residents near a nuclear power plant during a nuclear accident is vital for emergency response planning. To tackle this challenge, considering the dynamic dispersion of radioactive materials in the atmosphere and its impact on evacuation routes under different meteorological conditions is crucial. This paper develops a dynamic dose-based emergency evacuation model (DDEEM), which is an efficient and optimized nuclear accident evacuation model based on dynamic radiological dose calculation, utilizing an improved A * algorithm to determine optimal evacuation routes. The DDEEM takes into account the influence of radiological plume dispersion and path selection on evacuation effectiveness. This study employs the DDEEM to assess radiological consequences and evacuation strategies for students residing 5 k m from a Chinese nuclear power plant. Under various meteorological conditions, including the three typical meteorological conditions, random ordered and random unordered meteorological sequences, optimal routes obtained through the DDEEM effectively reduce radiological dose exposure and mitigate radiation hazards. The results indicate that all evacuation paths generated by the DDEEM have a maximum dose of less than 1 m S v . Through simulations, the model’s effectiveness and reliability in dynamic radiological environments in terms of radiological consequences and evacuation analysis is verified. The research provides valuable insights and a practical tool for nuclear power plant emergency decision-making, enhancing emergency management capabilities during nuclear accidents. The DDEEM offers crucial technical support and a solid foundation for developing effective emergency response strategies.

Suggested Citation

  • Huifang Miao & Guoming Zhang & Peizhao Yu & Chunsen Shi & Jianxiang Zheng, 2023. "Dynamic Dose-Based Emergency Evacuation Model for Enhancing Nuclear Power Plant Emergency Response Strategies," Energies, MDPI, vol. 16(17), pages 1-21, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6338-:d:1230403
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/17/6338/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/17/6338/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hammond, Gregory D. & Bier, Vicki M., 2015. "Alternative evacuation strategies for nuclear power accidents," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 9-14.
    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. Yushuo Ren & Guoming Zhang & Jianxiang Zheng & Huifang Miao, 2024. "An Integrated Solution for Nuclear Power Plant On-Site Optimal Evacuation Path Planning Based on Atmospheric Dispersion and Dose Model," Sustainability, MDPI, vol. 16(6), pages 1-21, March.

    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. Wang, Xinjian & Liu, Zhengjiang & Loughney, Sean & Yang, Zaili & Wang, Yanfu & Wang, Jin, 2022. "Numerical analysis and staircase layout optimisation for a Ro-Ro passenger ship during emergency evacuation," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    2. Lovreglio, Ruggiero & Spearpoint, Michael & Girault, Mathilde, 2019. "The impact of sampling methods on evacuation model convergence and egress time," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 24-34.
    3. Teichmann, Dusan & Dorda, Michal & Sousek, Radovan, 2021. "Creation of preventive mass evacuation plan with the use of public transport," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    4. Justin Pence & Ian Miller & Tatsuya Sakurahara & James Whitacre & Seyed Reihani & Ernie Kee & Zahra Mohaghegh, 2019. "GIS‐Based Integration of Social Vulnerability and Level 3 Probabilistic Risk Assessment to Advance Emergency Preparedness, Planning, and Response for Severe Nuclear Power Plant Accidents," Risk Analysis, John Wiley & Sons, vol. 39(6), pages 1262-1280, June.

    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:16:y:2023:i:17:p:6338-:d:1230403. 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.