Identifying Locally Turbulent Vortices within Instabilities
August 21, 2024 ยท Declared Dead ยท ๐ IEEE Symposium on Large Data Analysis and Visualization
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Fabien Vivodtzev, Florent Nauleau, Jean-Philippe Braeunig, Julien Tierny
arXiv ID
2408.12662
Category
physics.flu-dyn
Cross-listed
cs.CV,
cs.GR,
cs.LG
Citations
0
Venue
IEEE Symposium on Large Data Analysis and Visualization
Last Checked
1 month ago
Abstract
This work presents an approach for the automatic detection of locally turbulent vortices within turbulent 2D flows such as instabilites. First, given a time step of the flow, methods from Topological Data Analysis (TDA) are leveraged to extract the geometry of the vortices. Specifically, the enstrophy of the flow is simplified by topological persistence, and the vortices are extracted by collecting the basins of the simplified enstrophy's Morse complex. Next, the local kinetic energy power spectrum is computed for each vortex. We introduce a set of indicators based on the kinetic energy power spectrum to estimate the correlation between the vortex's behavior and that of an idealized turbulent vortex. Our preliminary experiments show the relevance of these indicators for distinguishing vortices which are turbulent from those which have not yet reached a turbulent state and thus known as laminar.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ physics.flu-dyn
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Efficient collective swimming by harnessing vortices through deep reinforcement learning
R.I.P.
๐ป
Ghosted
NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework
R.I.P.
๐ป
Ghosted
Teaching the Incompressible Navier-Stokes Equations to Fast Neural Surrogate Models in 3D
R.I.P.
๐ป
Ghosted
Prediction of Reynolds Stresses in High-Mach-Number Turbulent Boundary Layers using Physics-Informed Machine Learning
R.I.P.
๐ป
Ghosted
From Deep to Physics-Informed Learning of Turbulence: Diagnostics
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted