Publications

A dynamic mode decomposition technique for the analysis of non–uniformly sampled flow data

Published in Journal of Computational Physics, 2022

This paper is about the novel method of $\theta$-DMD, which can handle non-uniformly sampled data.

Recommended citation: Binghua Li, Jesús Garicano-Mena, Eusebio Valero. (2022) "A dynamic mode decomposition technique for the analysis of non–uniformly sampled flow data" Journal of Computational Physics. 468(3):111495. http://dx.doi.org/10.1016/j.jcp.2022.111495

Dynamic Mode Decomposition Analysis of Spatially Agglomerated Flow Databases

Published in Energies, 2020

This paper is about using machine learning and compress sensing theory to apply DMD on large flow datasets.

Recommended citation: Binghua Li, Jesús Garicano-Mena, Yao Zheng, Eusebio Valero. (2020) "Dynamic Mode Decomposition Analysis of Spatially Agglomerated Flow Databases" Energies. 13(9):2134. http://dx.doi.org/10.3390/en13092134

A composite dynamic mode decomposition analysis of turbulent channel flows

Published in Physics of Fluids, 2019

This paper is about the new method of composite DMD which could find the most relative modes to the physics.

Recommended citation: Jesús Garicano-Mena, Binghua Li, Esteban Ferrer, Eusebio Valero. (2019) "A composite dynamic mode decomposition analysis of turbulent channel flows" Physics of Fluids. 31(11):115102. http://dx.doi.org/10.1063/1.5119342