Data-driven modal decomposition methods as feature detection techniques for flow problems: A critical assessment
Modal decomposition techniques are showing a fast growth in popularity for their wide range
of applications and their various properties, especially as data-driven tools. There are many …
of applications and their various properties, especially as data-driven tools. There are many …
Effective control of two-dimensional Rayleigh–Bénard convection: Invariant multi-agent reinforcement learning is all you need
Rayleigh–Bénard convection (RBC) is a recurrent phenomenon in a number of industrial
and geoscience flows and a well-studied system from a fundamental fluid-mechanics …
and geoscience flows and a well-studied system from a fundamental fluid-mechanics …
[HTML][HTML] Higher order dynamic mode decomposition to model reacting flows
This work presents a new application of higher order dynamic mode decomposition
(HODMD) for the analysis of reactive flows. Due to the high complexity of the data analysed …
(HODMD) for the analysis of reactive flows. Due to the high complexity of the data analysed …
A data–driven sensibility tool for flow control based on resolvent analysis
This study presents a novel application of data-driven resolvent analysis algorithm for flow
control. The objective is to identify key coherent structures connected to regions of the flow …
control. The objective is to identify key coherent structures connected to regions of the flow …
Identification of Structural Sensitivity Zones Via Clustering for Flow Control Applications
E Muñoz, H Dave, G D'Alessio, G Bontempi… - Available at SSRN … - papers.ssrn.com
Structural sensitivity is a valuable tool for assessing flow control strategies. However, its
conventional implementation involves significant computational costs due to the need to …
conventional implementation involves significant computational costs due to the need to …