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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

98
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
98
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

114
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
114
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

123
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
123
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

106
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
106
Second-order Op Amp Circuits01:19

Second-order Op Amp Circuits

397
Implementing second-order low-pass filters in audio systems is crucial in refining audio signals by eliminating undesirable high-frequency noise. These filters typically involve second-order op-amp circuits configured as voltage followers, encompassing two nodes with distinct storage elements.
The analysis of such circuits follows a systematic approach, similar to the second-order RLC circuits. In practical scenarios, bulky inductors are rarely employed due to their size and weight. This means...
397
Typical Model Studies01:30

Typical Model Studies

422
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.
422

You might also read

Related Articles

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

Sort by
Same author

<b>New species and new records of cave-dwelling money spiders from Japan with remarks on the genera <i>Anguliphantes</i>, <i>Arcuphantes</i>, <i>Nihonella</i>, <i>Micrargus</i>, and <i>Porrhomma</i> (Araneae, Linyphiidae)</b>.

Zootaxa·2026
Same author

Understanding the mechanisms behind the annuloplasty effect in tricuspid valve TEER: a computational study.

Journal of biomechanics·2026
Same author

Hypoattenuated Leaflet Thickening After TAVR: Incidence, Predictors, and the Role of Platelet Reactivity: A Prospective Multicenter Observational Study.

Journal of clinical medicine·2026
Same author

The In-Situ Mechanics of the Tricuspid Valve: Strain Heterogeneity and Anisotropy via 3D Digital Image Correlation.

Experimental mechanics·2026
Same author

Synthetic Training Enables Deployment on Raw Drone Data: An Attention-Based Framework for Detecting Orphan Wells.

Sensors (Basel, Switzerland)·2026
Same author

Morphological and molecular data reveal a new spider species of the little-known <i>Pholcus nagasakiensis</i> species group (Araneae, Pholcidae) from the Ryukyu Archipelago.

Biodiversity data journal·2026

Related Experiment Video

Updated: Aug 20, 2025

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

6.6K

Enhancing high-fidelity nonlinear solver with reduced order model.

Teeratorn Kadeethum1, Daniel O'Malley2, Francesco Ballarin3

  • 1Sandia National Laboratories, Albuquerque, NM, 87185, USA.

Scientific Reports
|November 23, 2022
PubMed
Summary
This summary is machine-generated.

Reduced order modeling (ROM) accelerates nonlinear solvers for partial differential equations by providing accurate initial guesses. This approach enhances computational efficiency and improves convergence for complex physics-based problems.

More Related Videos

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.7K
High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

3.9K

Related Experiment Videos

Last Updated: Aug 20, 2025

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

6.6K
Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.7K
High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

3.9K

Area of Science:

  • Computational science and engineering
  • Numerical analysis
  • Scientific computing

Background:

  • Full order models (FOM) for solving partial differential equations are computationally expensive.
  • Nonlinear solvers in FOMs often face convergence issues, especially for complex physical phenomena.
  • Reduced order modeling (ROM) offers a potential solution for computational cost reduction.

Purpose of the Study:

  • To develop a novel ROM-assisted approach to enhance the computational efficiency of FOM nonlinear solvers.
  • To improve the convergence rate of FOMs by utilizing ROM predictions as initial guesses.
  • To maintain the accuracy of FOMs while significantly reducing computational time.

Main Methods:

  • A ROM-assisted strategy was developed, using ROM predictions as initial guesses for FOM nonlinear solvers.
  • Four diverse physical problems were used for evaluation: Richards' equation, hyperelastic contact, two-phase flow, and fracture propagation.
  • The approach was tested across various FOM discretizations, including finite volume and finite element methods.

Main Results:

  • The ROM-assisted approach accelerated FOM nonlinear solvers by 18-73% across tested problems.
  • ROM predictions improved convergence, enabling solutions for problems that would otherwise diverge.
  • The accuracy of the ROM directly correlated with the degree of computational cost reduction achieved.

Conclusions:

  • The proposed ROM-assisted method effectively reduces computational cost and enhances convergence for nonlinear solvers of PDEs.
  • This non-intrusive, data-driven approach is adaptable to various nonlinear physics-based problems and FOM discretizations.
  • The strategy offers a significant improvement in computational efficiency without compromising the accuracy of the full order models.