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Volume-of-fluid-based method for three-dimensional shape prediction during the construction of horizontal salt caverns energy storage.
- Source :
-
Energy . Sep2024, Vol. 302, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- Construction prediction is the key for the shape control of energy storage salt caverns, which benefits with the storage capacity and long-term operational safety. However, the conventional grid discretization methods using elastic grid could not accurately tracking the three-dimensional boundary movements of salt cavern. This paper introduced a novel construction prediction model of salt cavern using a Volume-of-fluid based method. The tracking of the salt caverns' dissolving boundary is successfully reconstructed and tracked by the fluid volume fractions (0-1) in structural grids. The model was validated by indoor experiment and field data. In the simulation of indoor experiment, the lateral expansion, which was difficult to reproduce in previous models, is successfully simulated. The volume of the simulation chamber is 392.8 ml with an error of 1.9 %. During the simulation of Volgograd horizontal cavern construction, the simulated cavern shape is close to the sonar detection, with an average error in radius about 3.6 %. And the brine-discharge concentration is consistent with the site monitoring, with an average error about 4.5 %. These results validate the capability of the proposed method in three-dimensional dynamic boundary tracking and shape prediction of salt cavern. • A salt cavern construction prediction model is introduced using a Volume-of-Fluid method. • Three dimentional simulation of the movement of dissolving salt cavern interfaces is achieved for the first time. • A demo C++ program has been developed for numerical implementation of the proposed model. • model's reliability is verified through simulations of an indoor experiment and a field project. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03605442
- Volume :
- 302
- Database :
- Academic Search Index
- Journal :
- Energy
- Publication Type :
- Academic Journal
- Accession number :
- 177859168
- Full Text :
- https://doi.org/10.1016/j.energy.2024.131740