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

Viscosity of Fluid01:19

Viscosity of Fluid

873
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.
873
Dynamic Modulus of Elasticity of Concrete01:16

Dynamic Modulus of Elasticity of Concrete

657
The dynamic modulus of elasticity assesses how a concrete structure deforms under impact or dynamic loads. It is typically higher than the static modulus of elasticity, measured under slow, steady loading conditions.
The sonic test is a common method to determine the dynamic modulus. In this test, a concrete beam, sized either 6 x 6 x 30 inches or 4 x 4 x 20 inches, is clamped at its center. Vibrations are initiated at one end of the beam by an electromagnetic exciter unit powered by a...
657
Newtonian Fluid: Problem Solving01:18

Newtonian Fluid: Problem Solving

618
Newtonian fluids exhibit a constant viscosity, meaning their shear stress and shear strain rate are directly proportional. This property ensures a predictable and stable response to applied forces, maintaining a linear relationship between force and flow. Examples include water, air, and light oils, consistently demonstrating this proportional behavior regardless of external conditions.
A velocity gradient forms within the fluid when a Newtonian fluid is placed between two parallel plates, with...
618
Porosity in Cement Paste01:18

Porosity in Cement Paste

299
The porosity of concrete is a measure of the void spaces within its structure. These spaces impact its strength and durability significantly. When water and cement interact, a chemical reaction called hydration creates a semi-solid paste. This paste includes combined water, making up approximately 23% of the cement's dry mass, and gel water, which fills minuscule voids known as gel pores, accounting for about 28% of the cement gel volume.
The balance of water to cement in the mix is...
299
Viscosity01:17

Viscosity

6.6K
When water is poured into a glass, it falls freely and quickly, whereas if honey or maple syrup is poured over a pancake, it flows slowly and sticks to the surface of the container. This difference in the flow of different kinds of liquids arises due to the fluid friction between the liquid layers and the liquid and the surrounding material. This property of fluids is called fluid viscosity. In this example, water has a lower viscosity than honey and maple syrup.
The SI unit of viscosity is...
6.6K
Fineness of Cement01:15

Fineness of Cement

308
The fineness of cement directly influences the rate of hydration, as the hydration begins at the surface of the cement particles. In addition to hydration, the fineness of cement is vital for various properties of concrete including workability, gypsum requirement, and long-term behavior. The fineness of cement is represented in terms of the specific surface of cement which is typically measured in square meters per kilogram, with several methods available for this determination.
Direct...
308

You might also read

Related Articles

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

Sort by
Same author

Processing, Characterization and Applications of Ceramic Matrix Composites.

Materials (Basel, Switzerland)·2026
Same author

Bioengineering approaches to dynamic impact analysis for cranial fracture interpretation in arcaheology.

Scientific reports·2026
Same author

Processing and Characterisation of Alumina/Eucryptite Nanostructured Composites.

Materials (Basel, Switzerland)·2025
Same author

Analysis of the Rheological Properties of Natural Hydraulic Lime-Based Suspensions for Sustainable Construction and Heritage Conservation.

Materials (Basel, Switzerland)·2024
Same author

Automatic machine learning versus human knowledge-based models, property-based models and the fatigue problem.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2023
Same author

Planar Crack Approach to Evaluate the Flexural Strength of Fiber-Reinforced Concrete Sections.

Materials (Basel, Switzerland)·2022

Related Experiment Video

Updated: Nov 7, 2025

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

14.2K

Calculation of Dynamic Viscosity in Concentrated Cementitious Suspensions: Probabilistic Approximation and Bayesian

Ángel De La Rosa1, Gonzalo Ruiz1, Enrique Castillo2

  • 1ETS de Ingenieros de Caminos, C. y P., Universidad de Castilla-La Mancha, Av. Camilo José Cela s/n, 13071 Ciudad Real, Spain.

Materials (Basel, Switzerland)
|April 30, 2021
PubMed
Summary

This study applies Bayesian analysis to the Krieger-Dougherty equation for calculating dynamic viscosity in cementitious materials. This probabilistic approach significantly improves viscosity predictions compared to traditional methods.

Keywords:
Bayesian analysisKrieger–Dougherty equationcementitious suspensionsdeterministic and probabilistic modelsviscosity

More Related Videos

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

20.3K
Additive Manufacturing of Functionally Graded Ceramic Materials by Stereolithography
06:53

Additive Manufacturing of Functionally Graded Ceramic Materials by Stereolithography

Published on: January 25, 2019

14.7K

Related Experiment Videos

Last Updated: Nov 7, 2025

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

14.2K
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

20.3K
Additive Manufacturing of Functionally Graded Ceramic Materials by Stereolithography
06:53

Additive Manufacturing of Functionally Graded Ceramic Materials by Stereolithography

Published on: January 25, 2019

14.7K

Area of Science:

  • Rheology
  • Materials Science
  • Statistical Mechanics

Background:

  • The Krieger-Dougherty equation models dynamic viscosity in suspensions.
  • Cement pastes, mortars, and concretes exhibit complex rheological behavior.
  • Traditional deterministic models have limitations in capturing the inherent randomness of these systems.

Purpose of the Study:

  • To introduce a probabilistic perspective to the Krieger-Dougherty equation.
  • To enhance the calculation of dynamic viscosity in cementitious suspensions using Bayesian analysis.
  • To transform parametric-deterministic models into parametric-probabilistic models for improved results.

Main Methods:

  • Application of Bayesian analysis to the Krieger-Dougherty equation.
  • Utilizing numerical methods like Markov Chain Monte Carlo (MCMC) and Gibbs Sampling.
  • Employing specific software (OpenBUGS) to overcome computational complexity.

Main Results:

  • Computation of probability density functions for Krieger-Dougherty equation parameters.
  • Successful application to cement pastes, self-compacting mortars, and self-compacting concretes.
  • Demonstrated significant improvement in dynamic viscosity calculations compared to theoretical values.

Conclusions:

  • Bayesian analysis offers a robust framework for rheological modeling of complex suspensions.
  • The probabilistic approach enhances the accuracy and reliability of dynamic viscosity predictions.
  • This methodology provides a more enriched understanding of particle-fluid interactions in cementitious materials.