Bulletin of the American Physical Society
APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020; Denver, Colorado
Session D37: Transitional Flows & Chaotic Dynamics: In Honor of Bruno EckhardtInvited
|
Hide Abstracts |
Sponsoring Units: DFD Chair: Alexander Morozov, Univ of Edinburgh Room: 605 |
Monday, March 2, 2020 2:30PM - 3:06PM |
D37.00001: What do we learn from the finite lifetime of turbulence? Invited Speaker: Nigel Goldenfeld In a seminal paper published in 2006, Bruno Eckhardt and co-workers presented evidence to support the remarkable speculation that turbulence in shear flows --- specifically pipe flow --- has a finite lifetime at all Reynolds numbers, without the divergence that would be expected if the laminar and turbulent state were not analytically connected. I discuss these findings and their later extensions in terms of extreme value statistics and finite-size scaling, and show that the finite lifetime in pipe flow does not necessarily contradict the notion that there is a sharp laminar-turbulence transition in the universality class of directed percolation. |
Monday, March 2, 2020 3:06PM - 3:42PM |
D37.00002: Is space time? A spatiotemporal tiling of turbulence Invited Speaker: Predrag Cvitanovic We address the long standing problem of how to describe, by means |
Monday, March 2, 2020 3:42PM - 4:18PM |
D37.00003: Deep learning to discover the dimension of an inertial manifold and predict dynamics on it Invited Speaker: Michael Graham One of the senior author’s last conversations with Bruno Eckhardt concerned the connection of machine learning tools and ideas to dynamical systems and turbulence. This talk concerns one such connection. Many flow geometries, including pipe, channel and boundary layer, have a continuous translation symmetry. As a model for such systems we consider the Kuramoto-Sivashinsky equation (KSE) in a periodic domain. We describe a method to map the dynamics onto a translationally invariant low-dimensional manifold and time-evolve them using neural networks (NN). Dimensionality reduction is achieved by phase-aligning the spatial structures at each time, then putting them into an undercomplete autoencoder that maps the original dynamics onto a lower-dimensional inertial manifold where the long-time dynamics live. We infer the dimension of the manifold by tracking the autoencoder error vs. dimension—this drops by orders of magnitude once the proper dimension is reached. The spatial structure and phase are then integrated forward in time using a NN. This approach significantly outperforms Principal Components Analysis. |
Monday, March 2, 2020 4:18PM - 4:54PM |
D37.00004: The onset of turbulence: from invariant solutions to a directed percolation phase transition Invited Speaker: Bjoern Hof Flows through pipes and channels exhibit an abrupt transition from ordered laminar to high dimensional turbulent flow. At the lowest Reynolds numbers where this transition can be observed the resulting flows are spatio temporally intermittent and are composed of patches of turbulence surrounded by laminar fluid. As will be shown, in direct numerical simulations individual turbulent patches (i.e. stripes and puffs) can be continued to much lower Reynolds numbers where they originate from spatially localized periodic orbit solutions. I will further discuss experimental studies of interacting turbulent patches and how the competition between the decay and the proliferation of turbulence gives rise to a phase transition to sustained turbulence. |
Monday, March 2, 2020 4:54PM - 5:30PM |
D37.00005: Nonlinear invariant solutions underlying spatio-temporal patterns in thermally driven shear flows Invited Speaker: Tobias Schneider Driven wall-bounded fluid flows transitioning to turbulence are spatially extended chaotic dissipative non-equilibrium systems that support a large variety of self-organized patterns with regular spatial and temporal structure. In linearly stable parallel shear flows, patterns such as long-studied spontaneously emerging turbulent-laminar oblique stripes remain only partly understood. On the contrary, thermal convection in a fluid layer between two horizontal plates kept at different temperature, exhibits patterns that can often be described via a sequence of bifurcations off a base state undergoing a linear instability. If a Rayleigh-Bénard convection cell is inclined against gravity, buoyancy forces drive hot and cold fluid up and down the incline leading to a shear flow. In this so-called inclined layer convection (ILC) system, the competition of buoyancy and shear gives rise to a large variety of complex spatio-temporal flow patterns. |
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700