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

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model01:09

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model

511
Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the...
511
Entropy and Solvation02:05

Entropy and Solvation

7.4K
The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...
7.4K
Typical Model Studies01:30

Typical Model Studies

485
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
485
Elastic Strain Energy for Shearing Stresses01:20

Elastic Strain Energy for Shearing Stresses

318
As discussed in previous lessons, strain energy in a material is the energy stored when it is elastically deformed, a concept crucial in materials science and mechanical engineering. This energy results from the internal work done against the cohesive forces within the material. When a material undergoes shearing stress and corresponding shearing strain, the strain energy density, which is the energy stored per unit volume, is calculated. Within the elastic limit, where the stress is...
318
Colloidal precipitates01:09

Colloidal precipitates

939
The high insolubility of some precipitates can result in an unfavorable relative supersaturation. This can lead to colloidal particles with a large surface-to-mass ratio, where adsorption is promoted. For instance, in the precipitation of silver chloride, silver ions are adsorbed on the surface of the colloidal particles, forming a primary layer. This layer attracts ions of opposite charge (such as nitrate ions), forming a diffuse secondary layer of adsorbed ions. This electric double layer...
939
First Law: Particles in Two-dimensional Equilibrium01:18

First Law: Particles in Two-dimensional Equilibrium

7.2K
Recall that a particle in equilibrium is one for which the external forces are balanced. Static equilibrium involves objects at rest, and dynamic equilibrium involves objects in motion without acceleration; but it is important to remember that these conditions are relative. For instance, an object may be at rest when viewed from one frame of reference, but that same object would appear to be in motion when viewed by someone moving at a constant velocity.
Newton's first law tells us about...
7.2K

You might also read

Related Articles

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

Sort by
Same author

Machine Learning Modeling for Spatial-Temporal Prediction of Geohazard.

Sensors (Basel, Switzerland)·2023
Same author

An Entropic Approach to Estimating the Instability Criterion of People in Floodwaters.

Entropy (Basel, Switzerland)·2021
Same author

Evaluating Different Methods for Determining the Velocity-Dip Position over the Entire Cross Section and at the Centerline of a Rectangular Open Channel.

Entropy (Basel, Switzerland)·2020
Same author

A Simple Explicit Expression for the Flocculation Dynamics Modeling of Cohesive Sediment Based on Entropy Considerations.

Entropy (Basel, Switzerland)·2020
Same author

Modelling the Hindered Settling Velocity of a Falling Particle in a Particle-Fluid Mixture by the Tsallis Entropy Theory.

Entropy (Basel, Switzerland)·2020
Same author

Estimating the Bed-Load Layer Thickness in Open Channels by Tsallis Entropy.

Entropy (Basel, Switzerland)·2020

Related Experiment Video

Updated: Oct 16, 2025

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions
11:51

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions

Published on: February 22, 2018

8.8K

An Extended Entropic Model for Cohesive Sediment Flocculation in a Piecewise Varied Shear Environment.

Zhongfan Zhu1, Jie Dou2

  • 1Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, College of Water Sciences, Beijing Normal University, Beijing 100875, China.

Entropy (Basel, Switzerland)
|October 23, 2021
PubMed
Summary

A new entropic model accurately predicts cohesive sediment floc size changes under varying turbulence. This model, based on Shannon entropy, simplifies flocculation dynamics and shows potential for estuarine and coastal sediment transport modeling.

Keywords:
cohesive sedimententropyflocculationmodelpiecewise varied shear

More Related Videos

Experimental Measurement of Settling Velocity of Spherical Particles in Unconfined and Confined Surfactant-based Shear Thinning Viscoelastic Fluids
10:28

Experimental Measurement of Settling Velocity of Spherical Particles in Unconfined and Confined Surfactant-based Shear Thinning Viscoelastic Fluids

Published on: January 3, 2014

13.9K
Challenges in Rheological Characterization of Highly Concentrated Suspensions — A Case Study for Screen-printing Silver Pastes
08:42

Challenges in Rheological Characterization of Highly Concentrated Suspensions — A Case Study for Screen-printing Silver Pastes

Published on: April 10, 2017

20.2K

Related Experiment Videos

Last Updated: Oct 16, 2025

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions
11:51

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions

Published on: February 22, 2018

8.8K
Experimental Measurement of Settling Velocity of Spherical Particles in Unconfined and Confined Surfactant-based Shear Thinning Viscoelastic Fluids
10:28

Experimental Measurement of Settling Velocity of Spherical Particles in Unconfined and Confined Surfactant-based Shear Thinning Viscoelastic Fluids

Published on: January 3, 2014

13.9K
Challenges in Rheological Characterization of Highly Concentrated Suspensions — A Case Study for Screen-printing Silver Pastes
08:42

Challenges in Rheological Characterization of Highly Concentrated Suspensions — A Case Study for Screen-printing Silver Pastes

Published on: April 10, 2017

20.2K

Area of Science:

  • Environmental science
  • Fluid dynamics
  • Sedimentology

Background:

  • Cohesive sediment flocculation is crucial for estuarine and coastal processes.
  • Existing models struggle to accurately capture floc size evolution under dynamic turbulent shear rates.
  • Understanding floc size dynamics is key to predicting sediment transport and water quality.

Purpose of the Study:

  • To develop an extended entropic model for cohesive sediment floc size.
  • To describe temporal floc size evolution under piecewise varied turbulent shear rates.
  • To validate the model against experimental data and explore its application in hydrodynamic models.

Main Methods:

  • Utilized probability methods based on Shannon entropy theory.
  • Derived a simplified model with three key parameters: initial/steady-state floc size and maximum capacity.
  • Compared model predictions with 13 literature experimental data sets.

Main Results:

  • The entropic model accurately captured monotonic floc size changes over time.
  • High correlation coefficients and low errors validated the model against experimental data.
  • Identified a power decay relationship between the capacity parameter and shear rate in tapered shear flocculation.

Conclusions:

  • The proposed entropic model effectively describes cohesive sediment flocculation dynamics.
  • The model's parameterization using empirical relations enhances its predictive capabilities.
  • This model offers potential integration with hydrodynamic models for cohesive sediment transport in estuarine and coastal regions.