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

Mixtures of Acids03:27

Mixtures of Acids

21.6K
The pH of a solution containing an acid can be determined using its acid dissociation constant and its initial concentration. If a solution contains two different acids, then its pH can be determined using one of several methods depending upon the relative strength of the acids and their dissociation constants.
A Mixture of a Strong Acid and a Weak Acid
In a mixture of a strong acid and a weak acid, the strong acid dissociates completely and becomes a source of almost all the hydronium ions...
21.6K
Mixtures of Acids01:19

Mixtures of Acids

1.1K
The pH of a solution containing an acid can be determined using its acid dissociation constant and initial concentration. If a solution contains two different acids, then its pH can be determined using one of several methods depending on the relative strength of the acids and their dissociation constants.
In a strong and weak acid mixture, the strong acid dissociates completely and becomes a source of almost all the hydronium ions present in the solution. In contrast, the weak acid shows...
1.1K
Crystal Field Theory - Tetrahedral and Square Planar Complexes02:46

Crystal Field Theory - Tetrahedral and Square Planar Complexes

48.4K
Tetrahedral Complexes
Crystal field theory (CFT) is applicable to molecules in geometries other than octahedral. In octahedral complexes, the lobes of the dx2−y2 and dz2 orbitals point directly at the ligands. For tetrahedral complexes, the d orbitals remain in place, but with only four ligands located between the axes. None of the orbitals points directly at the tetrahedral ligands. However, the dx2−y2 and dz2 orbitals (along the Cartesian axes) overlap with the ligands less than the dxy,...
48.4K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

247
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
247
Racemic Mixtures and the Resolution of Enantiomers02:30

Racemic Mixtures and the Resolution of Enantiomers

21.6K
A racemic mixture, or racemate, is an equimolar mixture of enantiomers of a molecule that can be separated using their unique interaction with chiral molecules or media. Racemic mixtures are denoted by the (±)- prefix. This ‘optical rotation descriptor’ applies to the whole solution of a racemic mixture rather than a specific stereoisomer. Enantiomers typically have the same physical and chemical properties. Hence, they are not easily separable. However, enantiomers can exhibit...
21.6K
Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

1.0K
Understanding the movement of a rigid body in planar motion involves recognizing that every particle within this body is traversing a path that maintains a consistent distance from a specific plane. This concept is fundamental in the study of physics and mechanical engineering, and it allows us to comprehend better how objects move in space.
Planar motion is typically divided into three distinct categories. The first is rectilinear translation, demonstrated by a subway train that moves along...
1.0K

You might also read

Related Articles

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

Sort by
Same author

Biomechanical evaluation of a laxity-minimizing suture for rotator cuff repair.

JSES reviews, reports, and techniques·2026
Same author

Multiscale modeling of vascular adaptation: methodological advances and open challenges.

Journal of biomechanics·2026
Same author

Chronic Venous Insufficiency - A One-dimensional Blood Flow Modelling Assessment of Venous Valves, Perforators, Muscle Pump Activity and External Compression.

IEEE transactions on bio-medical engineering·2026
Same author

A multiscale computational model of ascending thoracic aortic aneurysm development in Marfan syndrome for in silico trials.

Biomechanics and modeling in mechanobiology·2026
Same author

Intervertebral Disc Elastography to Relate Shear Modulus and Relaxometry in Compression and Bending.

Bioengineering (Basel, Switzerland)·2026
Same author

Editorial: Evolution in cardiovascular MedTech.

Frontiers in medical technology·2026

Related Experiment Video

Updated: Jan 26, 2026

Biaxial Mechanical Characterizations of Atrioventricular Heart Valves
11:00

Biaxial Mechanical Characterizations of Atrioventricular Heart Valves

Published on: April 9, 2019

14.8K

Constrained mixture modeling affects material parameter identification from planar biaxial tests.

Lauranne Maes1, Heleen Fehervary1, Julie Vastmans1

  • 1Biomechanics Section, Mechanical Engineering Department, KU Leuven, Leuven, Belgium.

Journal of the Mechanical Behavior of Biomedical Materials
|April 17, 2019
PubMed
Summary

This study introduces an iterative fitting method for constrained mixture theory in arterial models. The approach accurately determines material parameters for residual stress modeling without needing a stress-free state.

Keywords:
Arterial tissueConstitutive modelingConstrained mixtureDeposition stretchesParameter estimation

More Related Videos

A Novel Biaxial Testing Apparatus for the Determination of Forming Limit under Hot Stamping Conditions
07:40

A Novel Biaxial Testing Apparatus for the Determination of Forming Limit under Hot Stamping Conditions

Published on: April 4, 2017

8.0K
Biaxial Basal Tone and Passive Testing of the Murine Reproductive System Using a Pressure Myograph
09:59

Biaxial Basal Tone and Passive Testing of the Murine Reproductive System Using a Pressure Myograph

Published on: August 13, 2019

9.9K

Related Experiment Videos

Last Updated: Jan 26, 2026

Biaxial Mechanical Characterizations of Atrioventricular Heart Valves
11:00

Biaxial Mechanical Characterizations of Atrioventricular Heart Valves

Published on: April 9, 2019

14.8K
A Novel Biaxial Testing Apparatus for the Determination of Forming Limit under Hot Stamping Conditions
07:40

A Novel Biaxial Testing Apparatus for the Determination of Forming Limit under Hot Stamping Conditions

Published on: April 4, 2017

8.0K
Biaxial Basal Tone and Passive Testing of the Murine Reproductive System Using a Pressure Myograph
09:59

Biaxial Basal Tone and Passive Testing of the Murine Reproductive System Using a Pressure Myograph

Published on: August 13, 2019

9.9K

Area of Science:

  • Biomedical Engineering
  • Computational Mechanics
  • Cardiovascular Research

Background:

  • Residual stresses are crucial in patient-specific arterial models but challenging to determine.
  • Existing methods often require an unknown stress-free configuration.
  • Constrained mixture theory offers a way to model these stresses using in vivo data.

Purpose of the Study:

  • To develop and validate an iterative fitting method for constrained mixture theory parameters in arterial tissue.
  • To enable accurate modeling of residual stresses and prestretches in patient-specific finite element models.
  • To obtain material parameters compatible with the constrained mixture theory.

Main Methods:

  • An iterative fitting approach combining nonlinear least squares optimization and finite element prestressing algorithms.
  • Verification using numerically generated planar biaxial test data with known material parameters.
  • Application to experimental planar biaxial test data from ovine pulmonary artery tissue.

Main Results:

  • The iterative method rapidly converges to correct material parameter sets.
  • Parameters obtained using this method differ significantly from classically derived parameters.
  • In vivo wall stresses calculated with the new parameters are comparable to those from classical methods.

Conclusions:

  • The developed iterative fitting method successfully obtains material parameters compatible with constrained mixture theory.
  • This approach overcomes limitations of classical parameter fitting for arterial tissue.
  • Accurate parameterization is essential for robust patient-specific modeling of arterial biomechanics.