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

Unsoundness of Aggregate due to Volume Change01:26

Unsoundness of Aggregate due to Volume Change

478
Unsoundness in aggregates due to volume changes is primarily caused by the physical alterations aggregates undergo, such as freezing and thawing, thermal changes, and wetting and drying. Unsound aggregates, when subjected to these changes, result in volume change upon disintegration. This, in turn, contributes to the deterioration of concrete, including scaling, pop-outs, and cracking. Particular types of aggregates, such as porous flints, cherts, and those containing clay minerals, are...
478
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

665
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...
665
Control Volume and System Representations01:16

Control Volume and System Representations

1.7K
Two key frameworks are employed to analyze mass, energy, and momentum transfer: the control volume approach and the system approach. These frameworks offer different perspectives, depending on whether the focus is on a specific region in space (control volume approach) or a defined mass of fluid (system approach).
The control volume approach considers a stationary region in space through which fluid flows. This region is bounded by a control surface.  For instance, in the case of water...
1.7K
Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

780
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
780
Finding Volume Using Cross-Sectional Area01:24

Finding Volume Using Cross-Sectional Area

211
For solids whose cross-sectional areas vary in a predictable way, volume can be determined by integrating these areas along an axis perpendicular to the slices. This approach is particularly useful for polyhedral solids, where classical geometric formulas may not be immediately applicable. A tetrahedron provides a clear example of how cross-sectional integration can be applied to a three-dimensional object with continuously changing geometry.Consider a tetrahedron with height h and a base that...
211
Work Done During Volume Change01:17

Work Done During Volume Change

6.3K
In mechanics, work is done on an object when the force acting on it displaces the object. In thermodynamics, work done on a system can be estimated when the system's volume changes during any thermodynamic process.
Consider a gas confined to a cylinder fitted with a movable piston at one end. If the gas expands from volume V1 to volume V2, it exerts a force on the piston, such that the piston moves by a distance dr.
The work done by the gas on the piston can be expressed as
6.3K

You might also read

Related Articles

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

Sort by
Same author

Mapping of PTP1B, TCPTP, SHP2, and Putative Substrates Reveals Novel Networks in Glomerular Podocytes.

Journal of cellular physiology·2026
Same author

SigTime: Learning and Visually Explaining Time Series Signatures.

IEEE transactions on visualization and computer graphics·2025
Same author

ClimateSOM: A Visual Analysis Workflow for Climate Ensemble Datasets.

IEEE transactions on visualization and computer graphics·2025
Same author

GSCache: Real-Time Radiance Caching for Volume Path Tracing Using 3D Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2025
Same author

Bridging Theory and Practice: A Multiphase Study of GenAI-Assisted Visualization Learning.

IEEE computer graphics and applications·2025
Same author

VISTA: A Visual Analytics Framework to Enhance Foundation Model-Generated Data Labels.

IEEE transactions on visualization and computer graphics·2025

Related Experiment Video

Updated: Apr 4, 2026

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing
11:36

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing

Published on: February 9, 2022

3.3K

Fuzzy Volume Rendering.

N Fout1, Kwan-Liu Ma

  • 1UC Davis, USA. natefout@gmail.com

IEEE Transactions on Visualization and Computer Graphics
|September 11, 2015
PubMed
Summary

This study introduces fuzzy volume rendering, an uncertainty-aware algorithm. It enhances data reliability by managing uncertainty in volume rendering for better decision-making.

Area of Science:

  • Computer Science
  • Visualization
  • Scientific Computing

Background:

  • Assessing volume rendering reliability requires understanding data uncertainty and its propagation.
  • Existing methods often fail to account for rendering algorithm contributions to uncertainty.

Purpose of the Study:

  • To develop a framework for managing uncertainty in volume rendering.
  • To create a self-validating computational model for computing a posteriori uncertainty bounds.

Main Methods:

  • Adopted a possibility-based representation for various uncertainty types (variability, imprecision, fuzziness).
  • Extended the fuzzy transform for uncertainty accumulation and propagation rules.
  • Applied this framework to develop fuzzy volume rendering.

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

17.3K
Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature
11:49

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

Published on: April 5, 2013

21.9K

Related Experiment Videos

Last Updated: Apr 4, 2026

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing
11:36

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing

Published on: February 9, 2022

3.3K
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

17.3K
Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature
11:49

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

Published on: April 5, 2013

21.9K

Main Results:

  • Developed an automated framework for uncertainty management in visualization.
  • Introduced fuzzy volume rendering, an uncertainty-aware algorithm.
  • Demonstrated efficient handling of complex uncertainty in volume rendering.

Conclusions:

  • Fuzzy volume rendering provides more complete data depictions, enabling reliable conclusions.
  • The proposed method offers a self-validating approach to uncertainty bounds in volume rendering.
  • This framework enhances decision-making by improving the reliability of visualized data.