IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i14p3471-d1435168.html
   My bibliography  Save this article

Study on Rapid Simulation of the Pre-Cooling Process of a Large LNG Storage Tank with the Consideration of Digital Twin Requirements

Author

Listed:
  • Yunfei Zhao

    (College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China)

  • Caifu Qian

    (College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China)

  • Guangzhi Shi

    (CNOOC Energy Development Co., Ltd., Tianjin 300450, China)

  • Mu Li

    (CNOOC Energy Development Co., Ltd., Tianjin 300450, China)

  • Zaoyang Qiu

    (CNOOC Gas and Power Group, Beijing 100028, China)

  • Baohe Zhang

    (Offshore Oil Engineering Co,. Ltd., Tianjin 300461, China)

  • Zhiwei Wu

    (College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China)

Abstract

The pre-cooling of a large LNG storage tank involves complex phenomena such as heat transfer, low-temperature flow, gas displacement, and vaporization. The whole pre-cooling process could take up to 50 h. For large-scale, full-capacity storage tanks, it is particularly important to accurately control the pre-cooling temperature. Digital twin technology can characterize and predict the full life cycle parameters from the beginning of pre-cooling development to the end and even the appearance of damage in real time. The construction of a digital twin platform requires a large number of data samples in order to predict the operating state of the device. Therefore, a simulation method with high computational efficiency for the pre-cooling process of LNG tanks is of great importance. In this paper, the mixture model and discrete phase model (DPM) are applied to simulate the pre-cooling process of a large LNG full-capacity tank. Following Euler–Lagrange, the DPM greatly simplifies the solution process. Compared with the experimental results, the maximum error of the DPM simulation results is less than 11%. Such a highly efficient simulation method for the large LNG full-capacity storage tank can make it possible to build the digital twin platform that needs hundreds of data model samples.

Suggested Citation

  • Yunfei Zhao & Caifu Qian & Guangzhi Shi & Mu Li & Zaoyang Qiu & Baohe Zhang & Zhiwei Wu, 2024. "Study on Rapid Simulation of the Pre-Cooling Process of a Large LNG Storage Tank with the Consideration of Digital Twin Requirements," Energies, MDPI, vol. 17(14), pages 1-12, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:14:p:3471-:d:1435168
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/14/3471/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/14/3471/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rodrigo Pereira Botão & Hirdan Katarina de Medeiros Costa & Edmilson Moutinho dos Santos, 2023. "Global Gas and LNG Markets: Demand, Supply Dynamics, and Implications for the Future," Energies, MDPI, vol. 16(13), pages 1-14, July.
    2. Fengyuan Yan & Jinliang Geng & Guangxin Rong & Heng Sun & Lei Zhang & Jinxu Li, 2023. "Optimization and Analysis of an Integrated Liquefaction Process for Hydrogen and Natural Gas Utilizing Mixed Refrigerant Pre-Cooling," Energies, MDPI, vol. 16(10), pages 1-18, May.
    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. Gabriela Pantoja Passos & Hirdan Katarina de Medeiros Costa & Edmilson dos Santos, 2024. "Analysis of the Impacts of Small-Scale LNG Projects for Energy Supply of the North Region of Brazil: The Case of Roraima," Sustainability, MDPI, vol. 16(5), pages 1-25, March.
    2. Ewelina Orysiak & Hubert Zielski & Mateusz Gawle, 2024. "LNG Logistics Model to Meet Demand for Bunker Fuel," Energies, MDPI, vol. 17(7), pages 1-22, April.
    3. Lisong Wang & Lijuan He & Yijian He, 2024. "Review on Absorption Refrigeration Technology and Its Potential in Energy-Saving and Carbon Emission Reduction in Natural Gas and Hydrogen Liquefaction," Energies, MDPI, vol. 17(14), pages 1-51, July.

    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:17:y:2024:i:14:p:3471-:d:1435168. 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.