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

Yunfei Zhao, Caifu Qian, Guangzhi Shi, Mu Li, Zaoyang Qiu, Baohe Zhang and Zhiwei Wu ()
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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

Energies, 2024, vol. 17, issue 14, 1-12

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.

Keywords: LNG storage tank; pre-cooling; phase change; numerical simulation; digital twin (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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