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

Correlation of Experimental Data01:23

Correlation of Experimental Data

232
Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
232
Dimensionless Groups in Fluid Mechanics01:15

Dimensionless Groups in Fluid Mechanics

340
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...
340
Viscosity of Fluid01:19

Viscosity of Fluid

428
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.
428
Newtonian Fluid: Problem Solving01:18

Newtonian Fluid: Problem Solving

230
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...
230
Pressure Variation in a Fluid at Rest01:11

Pressure Variation in a Fluid at Rest

256
In a fluid at rest, the pressure at any point beneath the fluid surface depends solely on the depth, not on the container's shape or size. This principle, known as hydrostatic pressure, arises because, in stationary fluids, there is no acceleration, meaning the forces within the fluid balance out. Only vertical forces, caused by the weight of the fluid above, contribute to pressure changes with depth.
When measuring pressure at two different levels within the fluid, the difference in...
256
Capillarity in Fluid01:19

Capillarity in Fluid

222
Capillarity describes the movement of liquid in small spaces without external forces acting on it. The capillarity is driven by surface tension and adhesive interactions between the liquid and surrounding solid surfaces. This effect is often seen in narrow tubes, porous materials, and fine particles.
Surface tension is crucial to capillarity. It results from cohesive forces between liquid molecules at the liquid-air boundary, forming a skin that resists external forces. When the capillary tube...
222

You might also read

Related Articles

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

Sort by
Same author

Conservative Potentials for a Lattice-Mapped, Coarse-Grain Scheme with Fuzzy Switching Functions.

The journal of physical chemistry. A·2022
Same author

Conservative Potentials for a Lattice-Mapped Coarse-Grained Scheme.

The journal of physical chemistry. A·2021
See all related articles

Related Experiment Video

Updated: Jul 8, 2025

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

8.6K

Analytic expressions for correlations in coarse-grained simple fluids.

Siwei Luo1, Mark Thachuk1

  • 1Department of Chemistry, University of British Columbia, Vancouver, British Columbia V6T 1Z1, Canada.

The Journal of Chemical Physics
|December 14, 2023
PubMed
Summary
This summary is machine-generated.

This study develops an analytical method for coarse-graining fluid simulations, simplifying potential calculations for homogeneous fluids. The new approach offers a foundation for large-scale simulations and studying atomic versus continuum fluid models.

More Related Videos

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

4.5K
Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures
10:56

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures

Published on: May 20, 2014

12.2K

Related Experiment Videos

Last Updated: Jul 8, 2025

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

8.6K
Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

4.5K
Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures
10:56

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures

Published on: May 20, 2014

12.2K

Area of Science:

  • Computational physics
  • Statistical mechanics
  • Fluid dynamics

Background:

  • Coarse-graining of fluids is complex due to particle diffusion.
  • Existing methods group particles into regions, with potentials depending on statistical properties.
  • Previous work identified a generalized quadratic form for these potentials.

Purpose of the Study:

  • To derive analytic expressions for coarse-graining potential parameters using statistical mechanics.
  • To enable a priori calculation of potentials for homogeneous, simple fluids.
  • To provide a quantitative framework for exploring the discrete-continuum boundary in fluid modeling.

Main Methods:

  • Utilizing statistical mechanics to derive analytic expressions for potential parameters.
  • Employing fluid properties, including pair distribution functions.
  • Comparing derived expressions with simulation-obtained values.

Main Results:

  • Analytic expressions for coarse-graining potential parameters were successfully derived.
  • Derived expressions showed good agreement with simulation-based values.
  • The method allows for a priori potential calculation without fitting.

Conclusions:

  • The derived analytic expressions simplify the coarse-graining scheme for homogeneous fluids.
  • This work lays the foundation for large-scale, bottom-up fluid simulations.
  • The approach offers quantitative insights into the transition from atomic to continuum fluid descriptions.