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Direct numerical simulation is performed to study compressible, viscous flow around a circular cylinder. The present study considers two-dimensional, shock-free continuum flow by varying the Reynolds number between 20 and 100 and the…

Fluid Dynamics · Physics 2017-05-26 Daniel Canuto , Kunihiko Taira

Inspiratory and expiratory flow in a multi-generation pig lung airway was numerically studied at a peak tracheal flow rate corresponding to a Reynolds number of 1150. The model was validated by comparing velocity distributions with previous…

Fluid Dynamics · Physics 2018-04-18 Peshala P. T Gamage , Fardin Khalili , Azad Md. K , Hansen A Mansy

Reinforcement learning has by now become well established in finding excellent flow control strategies for a variety of scenarios. Existing literature has focused on using a simple two-jet solution (and variants there-of) or a…

Fluid Dynamics · Physics 2026-04-30 Rohan Kaushik , Anna Schwarz , Andrea Beck

The ability to reroute and control flow is vital to the function of venation networks across a wide range of organisms. By modifying individual edges in these networks, either by adjusting edge conductances or creating and destroying edges,…

Soft Condensed Matter · Physics 2021-01-14 Jason W. Rocks , Andrea J. Liu , Eleni Katifori

The stability of complex networks, from power grids to biological systems, is crucial for their proper functioning. It is thus important to control such systems to maintain or restore their stability. Traditional approaches rely on…

Optimization and Control · Mathematics 2025-09-23 Yuzhen Qin , Fabio Pasqualetti , Danielle S. Bassett , Marcel van Gerven

The unsteady flow physics of wind-turbine wakes under dynamic forcing conditions are critical to the modeling and control of wind farms for optimal power density. Unsteady forcing in the streamwise direction may be generated by unsteady…

This study presents novel drag reduction active-flow-control (AFC) strategies} for a three-dimensional cylinder immersed in a flow at a Reynolds number based on freestream velocity and cylinder diameter of $Re_D=3900$. The cylinder in this…

Fluid Dynamics · Physics 2025-02-20 P. Suárez , F. Álcantara-Ávila , A. Miró , J. Rabault , B. Font , O. Lehmkuhl , R. Vinuesa

Deep artificial neural networks (ANNs) used together with deep reinforcement learning (DRL) are receiving growing attention due to their capabilities to control complex problems. This technique has been recently used to solve problems…

Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply.…

Adaptation and Self-Organizing Systems · Physics 2017-11-28 Erik Andreas Martens , Konstantin Klemm

Non-linear effects of the Navier-Stokes equations disappear under the Stokes regime of Newtonian fluid flows disallowing the fluid flow rectification. Here we show mathematically and experimentally that passive flow rectification of…

Fluid Dynamics · Physics 2018-11-21 Aryan Mehboudi , Junghoon Yeom

Insects use flight muscles attached at the base of the wings to produce impressive wing flapping frequencies. The maximum power output of these flight muscles is insufficient to maintain such wing oscillations unless there is good elastic…

Fluid Dynamics · Physics 2016-07-20 Yangyang Huang , Eva Kanso

We study, possibly distributed, robust weight control policies for DC power networks that change link susceptances, or weights in response to balanced disturbances to the supply-demand vector. The margin of robustness for a given control…

Optimization and Control · Mathematics 2016-10-19 Qin Ba , Ketan Savla

Graph neural networks, recently introduced into the field of fluid flow surrogate modeling, have been successfully applied to model the temporal evolution of various fluid flow systems. Existing applications, however, are mostly restricted…

Fluid Dynamics · Physics 2026-01-14 Rui Gao , Zhi Cheng , Rajeev K. Jaiman

The influence of the bending rigidity of a flexible heaving wing on its propulsive performance in a two-dimensional imposed parallel flow is investigated in the inviscid limit. Potential flow theory is used to describe the flow over the…

Fluid Dynamics · Physics 2009-08-01 S. Michelin , S. G. Llewellyn Smith

Locally broken symmetries are used across fields to transport matter, particles and information in preferential directions. Beyond local mechanisms, spatially distributed nonlinearities in crystalline media have enabled non-reciprocal…

Soft Condensed Matter · Physics 2026-03-31 Aaron Winn , Justine Parmentier , Eleni Katifori , Martin Brandenbourger

This paper presents a recurrent neural network approach to simulating mechanical ventilator pressure. The traditional mechanical ventilator has a control pressure that is monitored by a medical practitioner and can behave incorrectly if the…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-10 Su Diao , Changsong Wei , Junyu Wang , Yizhou Li

Direct numerical simulations of turbulent suspension flows are carried out with the Force-Coupling Method in plane Couette and pressure-driven channel configurations. Dilute to moderately concentrated suspensions of neutrally buoyant…

Fluid Dynamics · Physics 2018-08-15 Guiquan Wang , Micheline Abbas , Eric Climent

The present study reports on flow past airfoils (stationary and moving) using sharp interface immersed-boundary approach. Non-boundary conforming approach like immersed-boundary method offers a viable alternative over traditional boundary…

Fluid Dynamics · Physics 2021-02-11 Pradeep Kumar Seshadri , Ashoke De

The acoustofluidic method holds great promise for manipulating microorganisms. When exposed to the steady vortex structures of acoustic streaming flow, these microorganisms exhibit intriguing dynamic behaviors, such as hydrodynamic trapping…

Fluid Dynamics · Physics 2025-04-25 Xuyang Sun , Wenchang Tan , Yi Man

Unsteady flow fields over a circular cylinder are trained and predicted using four different deep learning networks: convolutional neural networks with and without consideration of conservation laws, generative adversarial networks with and…

Fluid Dynamics · Physics 2019-10-04 Sangseung Lee , Donghyun You
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