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

Density00:56

Density

18.9K
Density is an important characteristic of substances, crucial in determining whether an object sinks or floats in a fluid. Its SI unit is kg/m3, and its cgs unit is g/cm3. The density of an object helps in identifying its composition, and also reveals information about the phase of the matter and its substructure. The densities of liquids and solids are roughly comparable, consistent with the fact that their atoms are in close contact. However, gases have much lower densities than liquids and...
18.9K
Accelerating Fluids01:17

Accelerating Fluids

2.0K
When a fluid is in constant acceleration, the pressure and buoyant force equations are modified. Suppose a beaker is placed in an elevator accelerating upward with a constant acceleration, a. In the beaker, assume there is a thin cylinder of height h with an infinitesimal cross-sectional area, ΔS.
The motion of the liquid within this infinitesimal cylinder is considered to obtain the pressure difference. Three vertical forces act on this liquid:
2.0K
Density and Archimedes' Principle01:05

Density and Archimedes' Principle

8.4K
When a lump of clay is dropped into water, it sinks. But if the same lump of clay is molded into the shape of a boat, it starts to float. Because of its shape, the clay boat displaces more water than the lump and experiences a greater buoyant force, even though its mass is the same. The same holds true for steel ships. The average density of an object majorly determines if the object will float. If an object's average density is less than that of the surrounding fluid, it will float. The...
8.4K
pV-Diagrams01:18

pV-Diagrams

6.0K
The pV diagram, which is a graph of pressure versus volume of the gas under study, is helpful in describing certain aspects of the substance. When the substance behaves like an ideal gas, the ideal gas equation describes the relationship between its pressure and volume. On a pV diagram, it is common to plot an isotherm, which is a curve showing p as a function of V with the number of molecules and the temperature fixed. Then, for an ideal gas, the product of the pressure of the gas and its...
6.0K
Viscosity of Fluid01:19

Viscosity of Fluid

1.1K
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.
1.1K
Velocity Potential01:20

Velocity Potential

645
In steady, incompressible flow through a long, straight pipe with a uniform cross-section, the flow in the central region (far from the pipe walls) is irrotational. This irrotational nature means that fluid particles do not rotate around their axes, and a scalar function called the velocity potential, represented by ϕ, can be used to describe their movement. In irrotational flows, the velocity field V is defined as the gradient of the velocity potential:
645

You might also read

Related Articles

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

Sort by
Same author

Benchmarking autoregressive conditional diffusion models for turbulent flow simulation.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

HYVE: Hybrid Vertex Encoder for Neural Distance Fields.

IEEE transactions on visualization and computer graphics·2026
Same author

Implicit Frictional Dynamics With Soft Constraints.

IEEE transactions on visualization and computer graphics·2024
Same author

Unsteady cylinder wakes from arbitrary bodies with differentiable physics-assisted neural network.

Physical review. E·2024
Same author

Implicit Frictional Boundary Handling for SPH.

IEEE transactions on visualization and computer graphics·2020
Same author

Volumetric Isosurface Rendering with Deep Learning-Based Super-Resolution.

IEEE transactions on visualization and computer graphics·2019
Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026
Same journal

RTF2Mesh: Restricted Tangent Face Based Mesh Compression With Neural Displacement Fields.

IEEE transactions on visualization and computer graphics·2026
Same journal

Practical Occluder Generation for Mobile Games.

IEEE transactions on visualization and computer graphics·2026
See all related articles

Related Experiment Video

Updated: Jan 5, 2026

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

12.5K

Implicit Density Projection for Volume Conserving Liquids.

Tassilo Kugelstadt, Andreas Longva, Nils Thuerey

    IEEE Transactions on Visualization and Computer Graphics
    |October 22, 2019
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new method for fluid simulations that ensures consistent volume by tracking particle density. This improves realism and performance in simulations like FLIP and APIC.

    More Related Videos

    Determining 3D Flow Fields via Multi-camera Light Field Imaging
    14:25

    Determining 3D Flow Fields via Multi-camera Light Field Imaging

    Published on: March 6, 2013

    17.1K
    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

    8.9K

    Related Experiment Videos

    Last Updated: Jan 5, 2026

    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

    12.5K
    Determining 3D Flow Fields via Multi-camera Light Field Imaging
    14:25

    Determining 3D Flow Fields via Multi-camera Light Field Imaging

    Published on: March 6, 2013

    17.1K
    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

    8.9K

    Area of Science:

    • Computer Graphics
    • Computational Physics
    • Fluid Dynamics

    Background:

    • Standard fluid simulation methods like FLIP and APIC struggle with volume conservation due to numerical errors.
    • These errors accumulate over time, leading to unrealistic volume changes in simulations.

    Purpose of the Study:

    • To develop a novel method for enforcing volume conservation in hybrid Eulerian/Lagrangian fluid simulations.
    • To address limitations of existing pressure solvers that cannot correct for accumulated volume errors.

    Main Methods:

    • Proposed an implicit density projection approach to enforce constant fluid density.
    • Derived a pressure Poisson equation incorporating density deviations based on the mass conservation law.
    • Integrated density tracking via simulation particles into existing solvers.

    Main Results:

    • Achieved robust volume conservation even in degenerate configurations and with boundary handling.
    • Demonstrated significant improvements in incompressibility, visual realism, and computational performance compared to standard methods.
    • Enabled relaxed time step and solver accuracy requirements, leading to higher performance.

    Conclusions:

    • The novel density projection method effectively maintains fluid volume and enhances simulation quality.
    • The approach offers practical advantages, including better particle distribution and reduced need for resampling.
    • This method represents a significant advancement for realistic and efficient fluid simulations.