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

Typical Model Studies01:30

Typical Model Studies

667
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.
667
Modeling and Similitude01:12

Modeling and Similitude

699
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
699
Dimensionless Groups in Fluid Mechanics01:15

Dimensionless Groups in Fluid Mechanics

867
Dimensionless groups in fluid mechanics provide simplified ratios that help analyze fluid behavior without relying on specific units. The Reynolds number (Re), which represents the ratio of inertial to viscous forces, distinguishes between laminar and turbulent flows, making it essential in the design of pipelines and aerodynamic surfaces. The Froude number (Fr), the ratio of inertial to gravitational forces, is particularly useful in predicting wave formation and hydraulic jumps in...
867
Design Example: Creating a Hydraulic Model of a Dam Spillway01:21

Design Example: Creating a Hydraulic Model of a Dam Spillway

837
Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
837
Newtonian Fluid: Problem Solving01:18

Newtonian Fluid: Problem Solving

1.1K
Newtonian fluids exhibit a constant viscosity, meaning their shear stress and shear strain rate are directly proportional. This property ensures a predictable and stable response to applied forces, maintaining a linear relationship between force and flow. Examples include water, air, and light oils, consistently demonstrating this proportional behavior regardless of external conditions.
A velocity gradient forms within the fluid when a Newtonian fluid is placed between two parallel plates, with...
1.1K
Viscosity of Fluid01:19

Viscosity of Fluid

1.6K
Viscosity measures the resistance a fluid offers to flow and deformation. It results from internal friction between layers of fluid moving relative to one another. Dynamic viscosity, denoted by the Greek letter mu (μ), quantifies the force needed to move one fluid layer over another. For Newtonian fluids like water and air, the relationship between the shearing stress and the rate of shearing strain is linear, meaning their viscosity remains constant regardless of the applied stress.
1.6K

You might also read

Related Articles

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

Sort by
Same author

Astrocytic connexin43 phosphorylation contributes to seizure susceptibility after mild traumatic brain injury.

The FEBS journal·2026
Same author

xCT (Slc7a11) Regulation: Lessons from Cancer Research.

Neurochemical research·2026
Same author

Combined heart-liver transplant in an acute-on-chronic liver failure (ACLF) setting.

Indian journal of thoracic and cardiovascular surgery·2026
Same author

Abnormal calcium release and delayed afterdepolarizations: A comparison of two mathematical models for human ventricular myocytes.

PloS one·2026
Same author

Mechano-electric feedback reduces the occurrence of delayed-afterdepolarization-driven focal activity.

Computers in biology and medicine·2026
Same author

Interfaces as transport barriers in two-dimensional Cahn-Hilliard-Navier-Stokes turbulence.

Journal of physics. Condensed matter : an Institute of Physics journal·2025
Same journal

Erratum: Low-dimensional model for adaptive networks of spiking neurons [Phys. Rev. E 111, 014422 (2025)].

Physical review. E·2026
Same journal

Disentangling the effects of many-body forces on depletion interactions.

Physical review. E·2026
Same journal

Charge transport and mode transition in dual-energy electron beam diodes.

Physical review. E·2026
Same journal

Optimization of multisite reactions in complex compartmentalized media.

Physical review. E·2026
Same journal

Origin of geometric cohesion in nonconvex granular materials: Interplay between interdigitation and rotational constraints enhancing frictional stability.

Physical review. E·2026
Same journal

Interaction of walkers with a standing Faraday wave.

Physical review. E·2026
See all related articles

Related Experiment Video

Updated: Mar 12, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

13.4K

Multiscaling in superfluid turbulence: A shell-model study.

Vishwanath Shukla1, Rahul Pandit2

  • 1Laboratoire de Physique Statistique de l'Ecole Normale Supérieure, 24 Rue Lhomond, 75231 Paris, France.

Physical Review. E
|November 15, 2016
PubMed
Summary
This summary is machine-generated.

This study reveals that multiscaling behavior in three-dimensional superfluid turbulence is more complex than in fluid turbulence. The findings explore velocity structure functions and their dependence on fluid properties.

More Related Videos

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions
11:51

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions

Published on: February 22, 2018

9.2K
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

9.1K

Related Experiment Videos

Last Updated: Mar 12, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

13.4K
Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions
11:51

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions

Published on: February 22, 2018

9.2K
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

9.1K

Area of Science:

  • Physics
  • Fluid Dynamics
  • Quantum Turbulence

Background:

  • Superfluid turbulence exhibits complex dynamics governed by the Hall-Vinen-Bekharevich-Khalatnikov (HVBK) equations.
  • Understanding multiscaling behavior is crucial for characterizing energy dissipation and cascade processes.

Purpose of the Study:

  • To investigate the multiscaling behavior of velocity structure functions in three-dimensional superfluid turbulence.
  • To analyze the influence of normal-fluid fraction and mutual-friction coefficients on these scaling properties.

Main Methods:

  • Utilized a shell model based on the Gledzer-Okhitani-Yamada model for the 3D HVBK equations.
  • Examined the dependence of multiscaling exponents on key physical parameters.

Main Results:

  • The multiscaling exponents were found to depend on the normal-fluid fraction and mutual-friction coefficients.
  • The complexity of multiscaling behavior in superfluid turbulence was quantitatively demonstrated.

Conclusions:

  • Superfluid turbulence displays more intricate multiscaling properties compared to classical fluid turbulence.
  • The developed 3D-HVBK shell model provides a valuable tool for studying quantum turbulence.