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

Bernoulli's Equation for Flow Along a Streamline01:30

Bernoulli's Equation for Flow Along a Streamline

830
Bernoulli's equation relates the energy conservation in a fluid moving along a streamline. The equation applies to incompressible and inviscid fluids under steady flow. For such a flow, Newton's second law is applied to a small fluid element, which experiences forces due to pressure differences, gravity, and velocity variations. The force balance leads to the following form of Bernoulli's equation:
830
Bernoulli's Equation for Flow Normal to a Streamline01:16

Bernoulli's Equation for Flow Normal to a Streamline

729
Bernoulli's equation for flow normal to a streamline explains how pressure varies across curved streamlines due to the outward centrifugal forces induced by the fluid's curvature. The pressure is higher on the inner side of the curve, near the center of curvature, and decreases outward to balance these centrifugal forces.
The pressure difference depends on the fluid's velocity and radius of curvature. The pressure variation is minimal in flows with nearly straight streamlines.
729
Rapidly Varying Flow01:24

Rapidly Varying Flow

56
Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
56
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

59
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
59
Three-Dimensional Analysis of Strain01:29

Three-Dimensional Analysis of Strain

207
Three-dimensional strain analysis is crucial for understanding how materials deform under stress, particularly in elastic, homogeneous materials. This method employs principal stress axes to simplify complex stress states into more understandable forms. Subjected to stress, a small cubic element within a material either expands or contracts along these axes, transforming into a rectangular parallelepiped. This transformation effectively illustrates the material's deformation. The principal...
207
Dimensionless Groups in Fluid Mechanics01:15

Dimensionless Groups in Fluid Mechanics

307
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...
307

You might also read

Related Articles

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

Sort by
Same author

Defibrillation Testing in Patients Undergoing Replacement of the S-ICD Generator: Is There Still a Need?

Pacing and clinical electrophysiology : PACE·2024
Same author

Micro-jet formation induced by the interaction of a spherical and toroidal cavitation bubble.

Ultrasonics sonochemistry·2024
Same author

Amplification of Supersonic Microjets by Resonant Inertial Cavitation-Bubble Pair.

Physical review letters·2024
Same author

General mechanisms for stabilizing weakly compressible models.

Physical review. E·2023
Same author

Analysis and reconstruction of the multiphase lattice Boltzmann flux solver for multiphase flows with large density ratios.

Physical review. E·2022
Same author

Resolution of left atrial appendage thrombi: No difference between phenprocoumon and non-vitamin K-dependent oral antagonists.

Clinical cardiology·2022
Same journal

A harmonized fast-fashion garment-variant dataset for textile circularity and sustainability assessment.

Data in brief·2026
Same journal

Terahertz reflectivity dataset: Reading text on both sides of the page.

Data in brief·2026
Same journal

High-quality draft genome sequence data of <i>Levilactobacillus brevis</i> 3LB isolated from fermented milk koumiss.

Data in brief·2026
Same journal

Interview dataset: Encouraging the development of industrial symbiosis networks in Slovenia - transition to the circular economy.

Data in brief·2026
Same journal

Timeseries of multispectral and radar data and vegetation indices from Sentinel-1, Sentinel-2 and Landsat-8 at field scale.

Data in brief·2026
Same journal

BACI-VI-Bench: A dataset of variational inequality benchmark instances for multi-agent trade-network equilibrium.

Data in brief·2026
See all related articles

Related Experiment Video

Updated: Jun 12, 2025

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

16.6K

Flow field data of three-dimensional Riemann problems.

Nils Hoppe1, Nico Fleischmann1, Benedikt Biller1

  • 1Chair of Aerodynamics and Fluid Mechanics, Technical University of Munich, Boltzmannstr. 15, 85748 Garching, Germany.

Data in Brief
|September 23, 2024
PubMed
Summary
This summary is machine-generated.

This study presents novel 3D Riemann problems for validating compressible flow solvers, revealing common solver issues. The data enables quantitative comparisons for improved computational fluid dynamics (CFD) accuracy.

Keywords:
Compressible flowGas dynamicsHigh-order methodsHigh-resolution

More Related Videos

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

12.2K
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

8.5K

Related Experiment Videos

Last Updated: Jun 12, 2025

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

16.6K
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

12.2K
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

8.5K

Area of Science:

  • Computational Fluid Dynamics (CFD)
  • Fluid Mechanics
  • Numerical Analysis

Background:

  • Existing validation cases for compressible flow solvers are limited to 1D or 2D, failing to capture the complexity of inherently 3D flows.
  • Accurate simulation of 3D compressible flows is crucial for various engineering and scientific applications.

Purpose of the Study:

  • To introduce genuine three-dimensional (3D) Riemann problems for validating and verifying compressible flow solvers.
  • To provide simulation data that highlights common shortcomings of existing solvers, such as spurious oscillations and symmetry breaking.
  • To facilitate quantitative comparisons between different solvers and numerical methods.

Main Methods:

  • Simulation of 3D Riemann problems using the open-source ALPACA compressible flow solver.
  • Implementation of a finite-volume scheme with HLLC and Roe Riemann solvers and fifth-order WENO reconstruction.
  • Conducting simulations on a high-performance compute cluster (>300 cores).

Main Results:

  • Generation of simulation data for 3D Riemann problems designed to induce 3D effects and trigger solver deficiencies.
  • Identification of issues like spurious pressure oscillations, unphysical symmetry breaking, and shock disturbances in solver performance.
  • Provision of raw flow field data, input files, post-processing scripts, and visualizations.

Conclusions:

  • The provided dataset offers a valuable resource for rigorous validation of 3D compressible flow solvers.
  • The 3D Riemann problems effectively expose limitations in current numerical methods.
  • The accompanying data facilitates reproducible research and the development of more robust CFD tools.