Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Steady, Laminar Flow Between Parallel Plates01:17

Steady, Laminar Flow Between Parallel Plates

Understanding steady, laminar flow between parallel plates is essential for analyzing and designing flow in narrow rectangular channels, commonly found in various water conveyance and drainage systems. The Navier-Stokes equations govern fluid motion and are generally challenging to solve due to their nonlinearity. However, simplifications are possible in certain cases, like the steady laminar flow between parallel plates. For this scenario, we assume steady, incompressible, laminar flow.
Laminar and Turbulent Flow01:07

Laminar and Turbulent Flow

Fluid dynamics is the study of fluids in motion. Velocity vectors are often used to illustrate fluid motion in applications like meteorology. For example, wind—the fluid motion of air in the atmosphere—can be represented by vectors indicating the speed and direction of the wind at any given point on a map. Another method for representing fluid motion is a streamline. A streamline represents the path of a small volume of fluid as it flows. When the flow pattern changes with time, the streamlines...
Typical Model Studies01:30

Typical Model Studies

Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
Plane Potential Flows01:23

Plane Potential Flows

Plane potential flows simplify fluid motion by assuming the fluid to be irrotational and incompressible. These characteristics allow these flows to be described by a velocity potential function, ϕ, representing the flow speed in a given direction, and a stream function, ψ, that visualizes the flow path, both governed by Laplace's equation. These parameters help in estimating flow patterns, velocity distributions, and pressure fields around various hydraulic structures.
Uniform Flow
Uniform flow...
Turbulent Flow01:24

Turbulent Flow

Turbulent flow is characterized by unpredictable fluctuations in velocity and pressure, which result in a chaotic fluid movement distinct from the orderly patterns of laminar flow. While laminar flow is governed by smooth, parallel layers with minimal mixing, turbulent flow exhibits highly irregular, three-dimensional patterns. This behavior arises due to instabilities in the fluid's velocity profile, and amplifies as the flow velocity increases. Minor disturbances, known as turbulent spots,...
Couette Flow01:22

Couette Flow

Couette flow represents the flow of fluid between two parallel plates, with one plate fixed and the other moving with a constant velocity. This configuration allows for a simplified analysis using the Navier-Stokes equations, which govern fluid motion under conditions of viscosity and incompressibility. For Couette flow, the assumptions include a steady, laminar, incompressible flow with a zero-pressure gradient in the flow direction. This flow type is beneficial for understanding shear-driven...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Interaction Renormalization and Validity of Kinetic Equations for Turbulent States.

Physical review letters·2025
Same author

Multimode correlations and the entropy of turbulence in shell models.

Physical review. E·2023
Same author

Sum-of-squares bounds on correlation functions in a minimal model of turbulence.

Physical review. E·2023
Same author

Information theory characteristics improve the prediction of lithium response in bipolar disorder patients using a support vector machine classifier.

Bipolar disorders·2022
Same author

Singular Measures and Information Capacity of Turbulent Cascades.

Physical review letters·2020
Same author

Light transport and vortex-supported wave-guiding in micro-structured optical fibres.

Scientific reports·2020

Related Experiment Video

Updated: Jul 11, 2026

Investigating the Three-dimensional Flow Separation Induced by a Model Vocal Fold Polyp
09:58

Investigating the Three-dimensional Flow Separation Induced by a Model Vocal Fold Polyp

Published on: February 3, 2014

Fluid-particle separation in a random flow described by the telegraph model.

Gregory Falkovich1, Marco Martins Afonso

  • 1Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|October 13, 2007
PubMed
Summary

This study analyzes fluid particle separation using telegraph noise. We found negative Lyapunov exponents in 1D and positive in 2D, revealing insights into fluid dynamics and entropy production.

More Related Videos

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques
10:53

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Published on: March 12, 2019

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
13:02

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

Published on: February 27, 2016

Related Experiment Videos

Last Updated: Jul 11, 2026

Investigating the Three-dimensional Flow Separation Induced by a Model Vocal Fold Polyp
09:58

Investigating the Three-dimensional Flow Separation Induced by a Model Vocal Fold Polyp

Published on: February 3, 2014

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques
10:53

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Published on: March 12, 2019

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
13:02

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

Published on: February 27, 2016

Area of Science:

  • Fluid Dynamics
  • Statistical Mechanics
  • Nonlinear Dynamics

Background:

  • Understanding particle dispersion in turbulent flows is crucial for various scientific and engineering applications.
  • Previous models often relied on simplified noise assumptions, limiting their applicability to real-world scenarios.

Purpose of the Study:

  • To investigate the statistical properties of relative separation between two fluid particles in a random flow.
  • To model Lagrangian strain using a telegraph noise process for a more realistic representation.
  • To derive analytical solutions for interparticle distance statistics under finite-correlated noise.

Main Methods:

  • Utilized a telegraph noise model for Lagrangian strain, a stationary random Markov process.
  • Derived closed equations for interparticle distance in the presence of finite-correlated noise.
  • Performed analytical calculations for one-dimensional (1D) and two-dimensional (2D) incompressible isotropic cases.

Main Results:

  • In 1D, analytically determined long-time growth rates of distance moments and a negative senior Lyapunov exponent.
  • Derived the exact Cramér function and confirmed its satisfaction of the fluctuation relation despite time irreversibility.
  • In 2D, obtained a positive Lyapunov exponent and asymptotic growth rates for fast and slow strain limits, identifying a singular quasideterministic limit.

Conclusions:

  • The telegraph noise model provides valuable insights into fluid particle dispersion, offering a balance between simplicity and realism.
  • The findings highlight the distinct behaviors of particle separation in 1D and 2D flows and under different strain rates.
  • The study demonstrates the applicability of fluctuation relations even with time-irreversible strain statistics.