Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Martin Lellep"'
Autor:
Andrés Cremades, Sergio Hoyas, Rahul Deshpande, Pedro Quintero, Martin Lellep, Will Junghoon Lee, Jason P. Monty, Nicholas Hutchins, Moritz Linkmann, Ivan Marusic, Ricardo Vinuesa
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Despite its great scientific and technological importance, wall-bounded turbulence is an unresolved problem in classical physics that requires new perspectives to be tackled. One of the key strategies has been to study interactions among the
Externí odkaz:
https://doaj.org/article/bad246b40a5c4e169d43de69a1f29ec7
Autor:
Andres Cremades, Sergio Hoyas, Pedro Quintero, Martin Lellep, Moritz Linkmann, Ricardo Vinuesa
Despite its great scientific and technological importance, wall-bounded turbulence is an unresolved problem that requires new perspectives to be tackled. One of the key strategies has been to study interactions among the coherent structures in the fl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe38fdcc9c6a5808211107115ebc7014
https://doi.org/10.21203/rs.3.rs-2923712/v1
https://doi.org/10.21203/rs.3.rs-2923712/v1
Autor:
Yasmin Hengster, Martin Lellep, Julian Weigel, Matthew Bross, Johannes Bosbach, Daniel Schanz, Andreas Schröder, Florian Huhn, Matteo Novara, Daniel Garaboa-Paz, Christian Kähler, Moritz Linkmann
Using curvature and torsion to describe Lagrangian trajectories gives a full description of these as well as an insight into small and large time scales as temporal derivatives up to order 3 are involved. One might expect that the statistics of these
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1bdc8e15d6314fee99516e1b961c8feb
Recent studies of pressure-driven flows of dilute polymer solutions in straight channels demonstrated the existence of two-dimensional coherent structures that are disconnected from the laminar state and appear through a sub-critical bifurcation from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0237cb355453cf49093b8dd125198a6
http://arxiv.org/abs/2211.09063
http://arxiv.org/abs/2211.09063
Publikováno v:
Journal of Fluid Mechanics. 942
Machine Learning (ML) is becoming increasingly popular in fluid dynamics. Powerful ML algorithms such as neural networks or ensemble methods are notoriously difficult to interpret. Here, we introduce the novel Shapley Additive Explanations (SHAP) alg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::59a27e27129225685780da3c4e4e4c5f
https://doi.org/10.1017/jfm.2022.307
https://doi.org/10.1017/jfm.2022.307
We perform a linear stability analysis of viscoelastic plane Couette and plane Poiseuille flows with free-slip boundary conditions. The fluid is described by the Oldroyd-B constitutive model, and the flows are driven by a suitable body force. We find
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49a7d5174ecdedfe1351a399b16e246a
Publikováno v:
Lellep, M, Prexl, J, Linkmann, M & Eckhardt, B 2020, ' Using Machine Learning to predict extreme events in the Hénon map ', Chaos, vol. 30, no. 1, 013113 . https://doi.org/10.1063/1.5121844
Machine Learning (ML) inspired algorithms provide a flexible set of tools for analyzing and forecasting chaotic dynamical systems. We here analyze the performance of one algorithm for the prediction of extreme events in the two-dimensional H\'enon ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e6aa14401ea1ee1fdd57c769fb2221b
https://pubmed.ncbi.nlm.nih.gov/32013508
https://pubmed.ncbi.nlm.nih.gov/32013508