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

Types of Non-structural Cracks in Concrete01:28

Types of Non-structural Cracks in Concrete

507
Non-structural cracks are primarily of three types: plastic, early-age thermal, and drying shrinkage cracks. Plastic cracks are further classified into plastic shrinkage cracks and plastic settlement cracks.
Plastic shrinkage cracks typically form within hours after the concrete is poured. The concrete's surface dries faster than the bottom, creating tensile stress that the still-plastic concrete cannot withstand, leading to diagonal or randomly patterned cracks on the concrete surface.
507
Propagation of Waves01:07

Propagation of Waves

3.0K
When a wave propagates from one medium to another, part of it may get reflected in the first medium, and part of it may get transmitted to the second medium. In such a case, the interface of the two mediums can be considered as a boundary that is neither fixed nor free.
Consider a scenario where a wave propagates from a string of low linear mass density to a string of high linear mass density. In such a case, the reflected wave is out of phase with respect to the incident wave, however the...
3.0K
Propagation of Action Potentials01:23

Propagation of Action Potentials

9.5K
The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
9.5K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.5K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.5K
Dynamic Equilibrium02:20

Dynamic Equilibrium

63.0K
A reversible chemical reaction represents a chemical process that proceeds in both forward (left to right) and reverse (right to left) directions. When the rates of the forward and reverse reactions are equal, the concentrations of the reactant and product species remain constant over time and the system is at equilibrium. A special double arrow is used to emphasize the reversible nature of the reaction. The relative concentrations of reactants and products in equilibrium systems vary greatly;...
63.0K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

2.0K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
2.0K

You might also read

Related Articles

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

Sort by
Same author

Signatures of the sub-Rayleigh to supershear fracture transition in snow avalanche experiments.

Nature communications·2025
Same author

Time-dependent density functional theory investigation of the formation of H3+ from alkanes.

The Journal of chemical physics·2025
Same author

FDG PET/CT reveals solitary hepatic metastasis from urachal adenocarcinoma mimicking a hepatic pseudolesion on contrast-enhanced CT.

Revista espanola de medicina nuclear e imagen molecular·2025
Same author

Clinicopathological features and prognosis of patients with colorectal Mucinous adenocarcinoma mixed with other pathological components: a nationwide retrospective study in China.

Techniques in coloproctology·2025
Same author

Search for the Rare Decay D^{0}→μ^{+}μ^{-} in Proton-Proton Collisions at sqrt[s]=13.6  TeV.

Physical review letters·2025
Same author

Observation of Λ Hyperon Local Polarization in p-Pb Collisions at sqrt[s_{NN}]=8.16  TeV.

Physical review letters·2025

Related Experiment Video

Updated: Feb 7, 2026

Mechanoluminescent Visualization of Crack Propagation for Joint Evaluation
04:58

Mechanoluminescent Visualization of Crack Propagation for Joint Evaluation

Published on: January 6, 2023

5.8K

Dynamic anticrack propagation in snow.

J Gaume1,2, T Gast3,4, J Teran3,4

  • 1School of Architecture, Civil and Environmental Engineering, Swiss Federal Institute of Technology, 1015, Lausanne, Switzerland. johan.gaume@gmail.com.

Nature Communications
|August 5, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a new model for anticrack propagation in porous materials, accurately simulating snow fracture dynamics. The findings aid in understanding and forecasting geological hazards like landslides and avalanches.

More Related Videos

Full-field Strain Measurements for Microstructurally Small Fatigue Crack Propagation Using Digital Image Correlation Method
07:37

Full-field Strain Measurements for Microstructurally Small Fatigue Crack Propagation Using Digital Image Correlation Method

Published on: January 16, 2019

10.1K
Antibody Staining in C. Elegans Using "Freeze-Cracking"
13:10

Antibody Staining in C. Elegans Using "Freeze-Cracking"

Published on: October 14, 2013

23.8K

Related Experiment Videos

Last Updated: Feb 7, 2026

Mechanoluminescent Visualization of Crack Propagation for Joint Evaluation
04:58

Mechanoluminescent Visualization of Crack Propagation for Joint Evaluation

Published on: January 6, 2023

5.8K
Full-field Strain Measurements for Microstructurally Small Fatigue Crack Propagation Using Digital Image Correlation Method
07:37

Full-field Strain Measurements for Microstructurally Small Fatigue Crack Propagation Using Digital Image Correlation Method

Published on: January 16, 2019

10.1K
Antibody Staining in C. Elegans Using "Freeze-Cracking"
13:10

Antibody Staining in C. Elegans Using "Freeze-Cracking"

Published on: October 14, 2013

23.8K

Area of Science:

  • Geophysics
  • Material Science
  • Computational Mechanics

Background:

  • Dynamic crack propagation in porous materials presents significant challenges.
  • Anticracks in geomaterials like sedimentary rocks and snow are complex due to material inter-penetration.

Purpose of the Study:

  • To develop and validate a numerical model for anticrack propagation in porous cohesive materials.
  • To accurately reproduce the dynamics of anticrack onset and propagation observed in snow fracture experiments.

Main Methods:

  • A novel elastoplasticity model for porous cohesive materials was employed.
  • A large-strain hybrid Eulerian-Lagrangian numerical method was utilized.
  • A modified strain-softening plastic flow rule was developed to capture material complexities.

Main Results:

  • The model accurately reproduced anticrack onset and propagation dynamics in snow fracture experiments.
  • The modified flow rule effectively captured mixed-mode loading effects, including cohesion loss and volumetric collapse.
  • The simulation successfully modeled solid-fluid phase transitions in geomaterials.

Conclusions:

  • The developed unified model advances continuum numerical modeling of dynamic crack propagation in porous media.
  • This research provides crucial insights for mitigating and forecasting gravitational hazards.
  • The model's ability to simulate solid-fluid phase transitions is vital for geohazard assessment.