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In this work, we study the flow in curved channels, an archetypal configuration that allows insights into problems featuring turbulence bounded by curved walls. Besides its relevance to many engineering applications, it exhibits a rich…

Fluid Dynamics · Physics 2025-03-19 Giulio Soldati , Paolo Orlandi , Sergio Pirozzoli

This paper addresses the air traffic flow management research problem of determining reroute, ground delay and air delay for flights using stochastic weather forecast information. The overall goal is to minimize system-wide reroute and…

Optimization and Control · Mathematics 2019-03-12 Guodong Zhu , Peng Wei

Reservoir computing is applied to model the large-scale evolution and the resulting low-order turbulence statistics of a two-dimensional turbulent Rayleigh-B\'{e}nard convection flow at a Rayleigh number ${\rm Ra}=10^7$ and a Prandtl number…

Fluid Dynamics · Physics 2020-11-25 Sandeep Pandey , Jörg Schumacher

Direct numerical simulation (DNS), mostly used in fundamental turbulence research, is limited to low turbulent intensities due the current and future computer resources. Standard turbulence models, like RaNS (Reynolds averaged…

Fluid Dynamics · Physics 2015-06-17 Christoph Glawe , Heiko Schmidt , Alan R. Kerstein , Rupert Klein

The internal flow in corrugated tubes of different helical pitch, covering from the laminar to turbulent regime, was studied in order to characterize the three-dimensional flow and the influence of corrugation geometry on pressure drop and…

We present direct numerical simulation results of turbulent open channel flow at bulk Reynolds numbers up to 12000, coupled with (passive) scalar transport at Schmidt numbers up to 200. Care is taken to capture the very large scale motions…

Fluid Dynamics · Physics 2022-01-19 Michele Pinelli , Herlina Herlina , Jan G. Wissink , Markus Uhlmann

A dynamical systems approach to turbulence envisions the flow as a trajectory through a high-dimensional state space transiently visiting the neighbourhoods of unstable simple invariant solutions (E. Hopf, Commun. Appl. Maths 1, 303, 1948).…

Fluid Dynamics · Physics 2023-11-15 Jacob Page , Peter Norgaard , Michael P. Brenner , Rich R. Kerswell

Microscale turbulent flow in porous media is conducive to the development of flow instabilities due to strong vortical and shearing flow occurring within the pore space. When the flow instabilities around individual solid obstacles interact…

Fluid Dynamics · Physics 2025-04-03 Vishal Srikanth , Andrey V. Kuznetsov

An extended version of the resolvent formulation is used to evaluate the use of anisotropic porous materials as passive flow control devices for turbulent channel flow. The effect of these porous substrates is introduced into the governing…

Fluid Dynamics · Physics 2021-01-15 Andrew Chavarin , Christoph Efstathiou , Shilpa Vijay , Mitul Luhar

Microscale turbulence in porous media is a new physical phenomenon that exhibits unique properties unlike those in classical turbulence flows. At low values of porosity, the surface forces on the solid obstacles compete with the inertial…

Fluid Dynamics · Physics 2021-08-24 V. Srikanth , C. W. Huang , T. S. Su , A. V. Kuznetsov

Two-way coupled direct numerical simulations are used to investigate the effects of inertial particles on self-sustained, turbulent coherent structures (i.e. the so-called the regeneration cycle) in plane Couette flow at low Reynolds number…

Fluid Dynamics · Physics 2019-01-30 Guiquan Wang , David Richter

The selective frequency damping method was applied to a bent flow. The method was used in an adaptive formulation. The most dangerous frequency was determined by solving an eigenvalue problem. It was found that one of the patterns,…

Fluid Dynamics · Physics 2020-11-06 Alexander V. Proskurin

The venerable 2D point-vortex model plays an important role as a simplified version of many disparate physical systems, including superfluids, Bose-Einstein condensates, certain plasma configurations, and inviscid turbulence. This system is…

Chaotic Dynamics · Physics 2013-05-29 Spencer A. Smith , Bruce M. Boghosian

Transformation optics (TO) is a new method to design metamaterials that can manipulate electromagnetic fields. Inspired by the traditional TO techniques which is mostly based on the solid metamaterials with a limited range of tunability, a…

Optics · Physics 2026-02-24 R. Yan , Y. Yang , X. Tu , T. Huang , Y. Liu , C. Song

Turbulent flows consist of a wide range of interacting scales. Since the scale range increases as some power of the flow Reynolds number, a faithful simulation of the entire scale range is prohibitively expensive at high Reynolds numbers.…

Fluid Dynamics · Physics 2023-07-24 Dhawal Buaria , Katepalli R. Sreenivasan

We present a coupling framework for Stokes-Darcy systems valid for arbitrary flow direction at low Reynolds numbers and for isotropic porous media. The proposed method is based on an overlapping domain decomposition concept to represent the…

Numerical Analysis · Mathematics 2024-01-24 Marco Discacciati , Paola Gervasio

This study proposes a newly-developed deep-learning-based method to generate turbulent inflow conditions for spatially-developing turbulent boundary layer (TBL) simulations. A combination of a transformer and a multiscale-enhanced…

Fluid Dynamics · Physics 2023-03-22 Mustafa Z. Yousif , Meng Zhang , Linqi Yu , Ricardo Vinuesa , HeeChang Lim

The manipulation of a collection of fluid particles in a low Reynolds number environment has several important applications. As we demonstrate in this paper, this manipulation problem is related to the scientific question of how fluid flow…

Fluid Dynamics · Physics 2024-02-27 Jake Buzhardt , Phanindra Tallapragada

This paper presents a computational framework for the robust stiffness design of hyperelastic structures at finite deformations subject to various uncertain sources. In particular, the loading, material properties, and geometry…

Computational Engineering, Finance, and Science · Computer Science 2025-01-28 Nan Feng , Guodong Zhang , Kapil Khandelwal

This study employs Deep Reinforcement Learning (DRL) for active flow control in a turbulent flow field of high Reynolds numbers at $Re=274000$. That is, an agent is trained to obtain a control strategy that can reduce the drag of a cylinder…

Fluid Dynamics · Physics 2024-12-23 Jingbo Chen , Enrico Ballini , Stefano Micheletti
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