Development of a Reduced Order Model of Geostrophic Flow based on a Combination of Proper Orthogonal Decomposition and Long-Short Term Memory Network

Document Type : Research Article

Authors

1 Department of Computer Engineering, University of Qom, Qom, Iran

2 CFD, Turbulence and Combustion Research Lab, Department of Mechanical Engineering, University of Qom, Qom, Iran

Abstract

Mathematical modeling is used to study the phenomena and behavior of the system. Complex mathematical equations require powerful and time-consuming computational tools where that must be examined in order to obtain the correct behavior of a system. However, they require robust computational tools and take a lot of time. High-accuracy numerical simulations utilize numerical schemes and modeling tools to solve this set of equations and generate useful information about the behavior of a system. It makes many restrictions on the solution of scientific problems in different research fields such as geophysical and atmospheric flows, which have high temporal and spatial variations. Therefore, the development of effective and robust algorithms to achieve the maximum quality of numerical simulations with the optimal computational cost is a research topic. There are several methods for dimension reduction but this study used a combination of Proper Orthogonal Decomposition and long-short term memory network. Finally, comparing the results related to the modal coefficients which are obtained by the reduced order model and computational fluid dynamics snapshots projection shows the high accuracy of the proposed method. Also, one of the items considered in the study of algorithms is the time complexity of the algorithm. The computational time of the proposed method which is reconstructed using 15 modes is ten times faster than when all features have been used to reconstruct the model.

Keywords

Main Subjects

References

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Amirkabir Journal of Mechanical Engineering
Volume 54, Issue 11
February 2023
Pages 2583-2600

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