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Critical temperature of the classical XY model via autoencoder latent space sampling.
Phys Rev E
January 2025
University of KwaZulu-Natal, School of Chemistry and Physics, Westville Campus, Private Bag X54001, Durban, 4000, South Africa.
The classical XY model has been consistently studied since it was introduced more than six decades ago. Of particular interest has been the two-dimensional spin model's exhibition of the Berezinskii-Kosterlitz-Thouless (BKT) transition. This topological phenomenon describes the transition from bound vortex-antivortex pairs at low temperatures to unpaired or isolated vortices and antivortices above some critical temperature.
View Article and Find Full Text PDFJosephson-Anderson relation as diagnostic of turbulent drag reduction by polymers.
Phys Rev E
January 2025
Johns Hopkins University, Department of Applied Mathematics & Statistics, Baltimore, Maryland 21218, USA.
The detailed Josephson-Anderson relation, which equates instantaneously the volume-integrated vorticity flux and the work by pressure drop, has been the key to drag reduction in superconductors and superfluids. We employ a classical version of this relation to investigate the dynamics of polymer drag-reduced channel flows, particularly in the high-extent drag reduction (HDR) regime which is known to exhibit strong space-time intermittency. We show that high drag is not created instantaneously by near-wall coherent vortex structures as assumed in prior works.
View Article and Find Full Text PDFFluid-network relations: Decay laws meet with spatial self-similarity, scale invariance, and control scaling.
Phys Rev E
December 2024
École Polytechnique Fédérale de Lausanne, Infplane AI Technologies Ltd, Beijing 100080, China and , Lausanne 1015, Switzerland.
Diverse implicit structures of fluids have been discovered recently, providing opportunities to study the physics of fluids applying network analysis. Although considerable work has been devoted to identifying the informative network structures of fluids, we are limited to a primary stage of understanding what kinds of information these identified networks can convey about fluids. An essential question is how the mechanical properties of fluids are embodied in the topological properties of networks or vice versa.
View Article and Find Full Text PDFRare, noise-induced, bypass transition in plane Couette flow can bypass instantons.
Phys Rev E
December 2024
Laboratoire de Mécanique des Fluides de Lille (LMFL), Kampé de Fériet, Univ. Lille, CNRS, ONERA, Arts et Métiers Institute of Technology (ENSAM), école centrale de Lille, UMR 9014, F-59000 Lille, France.
This paper presents a study of rare noise-induced transitions from stable laminar flow to transitional turbulence in plane Couette flow, which we will term buildup. We wish to study forced paths that go all the way from laminar to turbulent flow and to focus the investigation on whether these paths share the properties of noise-induced transitions in simpler systems. The forcing noise has a red spectrum without any component in the natural, large-scale, linear receptivity range of the flow.
View Article and Find Full Text PDFDeep reinforcement learning for active flow control in a turbulent separation bubble.
Nat Commun
February 2025
Barcelona Supercomputing Center, Barcelona, Spain.
The control efficacy of deep reinforcement learning (DRL) compared with classical periodic forcing is numerically assessed for a turbulent separation bubble (TSB). We show that a control strategy learned on a coarse grid works on a fine grid as long as the coarse grid captures main flow features. This allows to significantly reduce the computational cost of DRL training in a turbulent-flow environment.
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