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

Permeability of Concrete01:25

Permeability of Concrete

714
Permeability in the context of concrete refers to how easily liquids or gases can pass through the material. This quality is crucial for assessing the water-tightness and durability of concrete structures and their resistance to chemical attacks. Concrete permeability can be determined through comparative laboratory tests. These tests typically involve sealing a concrete specimen from the sides, applying water pressure to the top surface with pressure, and measuring the amount of water passing...
714
Typical Model Studies01:30

Typical Model Studies

842
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.
842
Porosity and Absorption of Aggregate01:20

Porosity and Absorption of Aggregate

1.0K
Aggregates contain pores of varying sizes; while some are completely enclosed within the particles, others open onto the surface, allowing water to penetrate. The porosity of aggregates is a major factor contributing to the overall porosity of concrete, given that aggregates constitute about three-quarters of concrete's volume.
When all pores in an aggregate are filled with water, the aggregate is considered saturated and surface-dry. If left in dry air, water will evaporate until the...
1.0K
Dynamic Modulus of Elasticity of Concrete01:16

Dynamic Modulus of Elasticity of Concrete

1.3K
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...
1.3K
Magnetic Susceptibility and Permeability01:31

Magnetic Susceptibility and Permeability

2.9K
In linear magnetic materials, like paramagnets and diamagnets, magnetization is proportional to the magnetic field intensity. The constant of proportionality, a dimensionless number, is called magnetic susceptibility. The value of the susceptibility depends on the type of material.
When diamagnetic materials are placed under an external magnetic field, the moments opposite to the field are induced. Hence, the susceptibility for diamagnets has a minimal negative value of 10-5–10-6. Since...
2.9K
Indeterminate Structure01:18

Indeterminate Structure

1.3K
Indeterminate structures refer to structures where internal forces and reactions cannot be determined using only the equations of static equilibrium.  Indeterminate structures have more unknown forces and reaction forces than equations of static equilibrium that can be used to determine them. Indeterminate structures are often used in engineering to create complex, efficient, and aesthetically pleasing structures. There are various types of indeterminate structures used in engineering and...
1.3K

You might also read

Related Articles

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

Sort by
Same author

Label-free quantification of imaging features in the extracellular matrix of left and right-sided colon cancer tissues.

Scientific reports·2024
Same author

Metal contaminations in sediment and associated ecological risk assessment of river Mahanadi, India.

Environmental monitoring and assessment·2021
Same author

Fabrication and characterization of carbon-backed thin <sup>208</sup>Pb targets.

MethodsX·2016
Same author

International nutrition capacity building--A global SIOP-PODC model from India.

Indian journal of cancer·2016
Same author

A survey of nutritional practices for children with cancer in India.

Indian journal of cancer·2016
Same author

Nutritional status at presentation, comparison of assessment tools, and importance of arm anthropometry in children with cancer in India.

Indian journal of cancer·2016

Related Experiment Video

Updated: May 3, 2026

Wastewater Irrigation Impacts on Soil Hydraulic Conductivity: Coupled Field Sampling and Laboratory Determination of Saturated Hydraulic Conductivity
08:09

Wastewater Irrigation Impacts on Soil Hydraulic Conductivity: Coupled Field Sampling and Laboratory Determination of Saturated Hydraulic Conductivity

Published on: August 19, 2018

8.5K

Uncertainty in dual permeability model parameters for structured soils.

B Arora1, B P Mohanty1, J T McGuire2

  • 1Department of Biological and Agricultural Engineering, Texas A&M University, College Station, Texas, USA.

Water Resources Research
|January 31, 2014
PubMed
Summary
This summary is machine-generated.

Uncertainty in dual permeability model (DPM) parameters is reduced using adaptive Markov chain Monte Carlo (AMCMC) over conventional Metropolis-Hastings (MH). AMCMC effectively resolves parameter correlations, crucial for accurate contaminant transport prediction.

More Related Videos

Author Spotlight: Advancing Agricultural Land Ecosystem Research with a Hydraulic Property Analyzer to Assess Soil Health
07:21

Author Spotlight: Advancing Agricultural Land Ecosystem Research with a Hydraulic Property Analyzer to Assess Soil Health

Published on: August 9, 2024

1.5K
A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates
10:33

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

Published on: February 23, 2018

27.9K

Related Experiment Videos

Last Updated: May 3, 2026

Wastewater Irrigation Impacts on Soil Hydraulic Conductivity: Coupled Field Sampling and Laboratory Determination of Saturated Hydraulic Conductivity
08:09

Wastewater Irrigation Impacts on Soil Hydraulic Conductivity: Coupled Field Sampling and Laboratory Determination of Saturated Hydraulic Conductivity

Published on: August 19, 2018

8.5K
Author Spotlight: Advancing Agricultural Land Ecosystem Research with a Hydraulic Property Analyzer to Assess Soil Health
07:21

Author Spotlight: Advancing Agricultural Land Ecosystem Research with a Hydraulic Property Analyzer to Assess Soil Health

Published on: August 9, 2024

1.5K
A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates
10:33

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

Published on: February 23, 2018

27.9K

Area of Science:

  • Environmental Science
  • Soil Science
  • Hydrology

Background:

  • Accurate contaminant transport prediction relies on dual permeability models (DPM), but parameter identification remains challenging.
  • Unique parameter estimation for macropore, matrix, and interface regions in DPMs is unresolved.
  • Experimental data requirements for DPMs are not fully understood.

Purpose of the Study:

  • Quantify uncertainty in DPM parameters for soil columns with varying macropore distributions.
  • Compare the effectiveness of adaptive Markov chain Monte Carlo (AMCMC) and Metropolis-Hastings (MH) algorithms in parameter estimation.
  • Investigate the significance of the matrix-macropore interface in soil column flow.

Main Methods:

  • Employed adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms.
  • Assumed 10 out of 17 DPM parameters as uncertain or random.
  • Utilized experimental soil columns with single, low-density, and high-density macropore distributions.

Main Results:

  • AMCMC algorithm effectively resolved parameter correlations and showed fast convergence for all DPM parameters.
  • MH algorithm exhibited significant posterior correlations for several parameters, indicating equifinality issues.
  • Tri-modal characteristics in soil hydraulic parameters suggest sequential drainage: macropores, interface, then matrix pores.

Conclusions:

  • The selection of parameter sampling algorithms (AMCMC vs. MH) is critical for obtaining unique DPM parameters.
  • Additional information on parameter correlations is necessary to overcome equifinality when covariance structure is unknown.
  • Matrix-macropore interface hydraulic properties depend on multiple parameters beyond interface conductivity and macropore tortuosity.