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Related papers: Simulation of Droplet Trains in Microfluidic Netwo…

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Nonlinear systems, such as with degrading hysteretic behavior, are often encountered in engineering applications. In addition, due to the ubiquitous presence of uncertainty and the modeling of such systems becomes increasingly difficult. On…

Machine Learning · Statistics 2023-04-26 Subhayan De , Patrick T. Brewick

We investigated a model for the neural integrator based on hysteretic units connected by positive feedback. Hysteresis is assumed to emerge from the intrinsic properties of the cells. We consider the recurrent networks containing either…

Neurons and Cognition · Quantitative Biology 2007-05-23 Maxim Nikitchenko , Alexei Koulakov

Experiments on streams of water flowing down a rigid substrate have been performed for various plate inclinations and flow rates, and we focused on the regime of stationary meanders. The outcome is that (i) the flow is highly hysteretic :…

Fluid Dynamics · Physics 2007-05-23 Nolwenn Le Grand-Piteira , Adrian Daerr , Laurent Limat

Motion in a one-dimensional (1D) microfluidic array is simulated. Water droplets, dragged by flowing oil, are arranged in a single row, and due to their hydrodynamic interactions spacing between these droplets oscillates with a wave-like…

Fluid Dynamics · Physics 2015-06-05 Bin Liu , J. Goree , Yan Feng

The existence and limits of metastable droplets have been calculated using finite-system renormalization-group theory, for q-state Potts models in spatial dimension d=3. The dependence of the droplet critical sizes on magnetic field,…

Statistical Mechanics · Physics 2021-05-20 E. Can Artun , A. Nihat Berker

We examine the nonequilibrium nature of two-phase fluid displacements in a quasi-two-dimensional medium (a model open fracture), in the presence of localized constrictions ("defects"), from a theoretical and numerical standpoint. Our…

Fluid Dynamics · Physics 2024-01-25 Ran Holtzman , Marco Dentz , Marcel Moura , Mykyta Chubynsky , Ramon Planet , Jordi Ortin

Constructing simpler models, either stochastic or deterministic, for exploring the phenomenon of flow reversals in fluid systems is in vogue across disciplines. Using direct numerical simulations and nonlinear time series analysis, we…

Fluid Dynamics · Physics 2017-12-19 Manu Mannattil , Ambrish Pandey , Mahendra K. Verma , Sagar Chakraborty

The fluidic pinball has been recently proposed as an attractive and effective flow configuration for exploring machine learning fluid flow control. In this contribution, we focus on the route to chaos in this system without actuation, as…

Fluid Dynamics · Physics 2021-04-14 Nan Deng , Luc R. Pastur , Marek Morzyński , Bernd R. Noack

We study the transient response of a colloidal bead which is released from different heights and allowed to relax in the potential well of an optical trap. Depending on the initial potential energy, the system's time evolution shows…

Soft Condensed Matter · Physics 2011-06-10 Manas Khan , A. K. Sood

The theory of pattern formation in reaction-diffusion systems is extended to the case of a directed network. Due to the structure of the network Laplacian of the scrutinised system, the dispersion relation has both real and imaginary parts,…

Pattern Formation and Solitons · Physics 2014-08-01 Malbor Asllani , Joseph D. Challenger , Francesco Saverio Pavone , Leonardo Sacconi , Duccio Fanelli

We have investigated kinematic reversibility in a cold atom system under strongly overdamped conditions. In such systems, inertia is negligible, and for noninteracting rigid particles, inverting the external force causes a perfect reversal…

Atomic Physics · Physics 2026-05-06 Sara Sloman , J. Van Butcher , Chandra Raman

The irreversibility of trajectories in stochastic dynamical systems is linked to the structure of their causal representation in terms of Bayesian networks. We consider stochastic maps resulting from a time discretization with interval \tau…

Data Analysis, Statistics and Probability · Physics 2018-03-15 Andrea Auconi , Andrea Giansanti , Edda Klipp

Fluid flow networks are ubiquitous and can be found in a broad range of contexts, from human-made systems such as water supply networks to living systems like animal and plant vasculature. In many cases, the elements forming these networks…

Fully developed turbulence is a universal and scale-invariant chaotic state characterized by an energy cascade from large to small scales where the cascade is eventually arrested by dissipation. In this article, we show how to harness these…

Soft Condensed Matter · Physics 2024-04-09 Xander M. de Wit , Michel Fruchart , Tali Khain , Federico Toschi , Vincenzo Vitelli

Liquid drops that are pinned to solid surfaces by contact-angle hysteresis can be dislodged by wind forcing. When this occurs at high Reynolds numbers, substantial drop-interface oscillations precede depinning. It has been hypothesized that…

Fluid Dynamics · Physics 2021-05-11 Roger L. Simon, , Edward B. White

Flow-based generative models parameterize probability distributions through an invertible transformation and can be trained by maximum likelihood. Invertible residual networks provide a flexible family of transformations where only…

Machine Learning · Statistics 2020-07-27 Ricky T. Q. Chen , Jens Behrmann , David Duvenaud , Jörn-Henrik Jacobsen

Recent microfluidic experiments revealed that large particles advected in a fluidic loop display long-range hydrodynamic interactions. However, the consequences of such couplings on the traffic dynamics in more complex networks remain…

Soft Condensed Matter · Physics 2015-05-30 Raphaël Jeanneret , Julien Piera-Vest , Denis Bartolo

This study investigates the role of inertia in moving contact lines using experiments, theoretical analysis, and numerical simulations. Experiments are conducted using a plate immersion configuration over a wide range of Reynolds numbers…

Minimal input/output selection is investigated in this paper for each subsystem of a networked system. Some novel sufficient conditions are derived respectively for the controllability and observability of a networked system, as well as…

Optimization and Control · Mathematics 2019-10-15 Tong Zhou

Pairs of numerically computed trajectories of a chaotic system may coalesce because of finite arithmetic precision. We analyse an example of this phenomenon, showing that it occurs surprisingly frequently. We argue that our model belongs to…

Chaotic Dynamics · Physics 2020-08-26 Bruce N. Roth , Michael Wilkinson