Real-time data assimilation for the thermodynamic modeling of cryogenic storage tanks

Pedro A. Marques, Samuel Ahizi and Miguel A. Mendez

Energy, 2024, vol. 302, issue C

Abstract: The thermal management of cryogenic storage tanks requires advanced control strategies to minimize the boil-off losses produced by heat leakages and sloshing-enhanced heat and mass transfer. This work presents a data-assimilation approach to calibrate a 0D thermodynamic model for cryogenic fuel tanks from data collected in real time from multiple tanks. The model combines energy and mass balance between three control volumes (the ullage vapor, the liquid, and the solid tank) with an Artificial Neural Network (ANN) for predicting the heat transfer coefficients from the current tank state.

Keywords: Thermodynamics; Cryogenics; Sloshing; Modeling; Machine learning; Data assimilation (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:302:y:2024:i:c:s0360544224015123

DOI: 10.1016/j.energy.2024.131739

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