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

Electrostatic Boundary Conditions in Dielectrics01:27

Electrostatic Boundary Conditions in Dielectrics

1.1K
When an electric field passes from one homogeneous medium to another, crossing the boundary between the two mediums imparts a discontinuity in the electric field. This results in electrostatic boundary conditions that depend on the type of mediums the field propagates through.
Consider a case where both the mediums across a boundary are two different dielectric materials. Recall that the electric field and electric displacement are proportional and related through the material's...
1.1K
Electrostatic Boundary Conditions01:16

Electrostatic Boundary Conditions

446
Consider an external electric field propagating through a homogeneous medium. When the electric field crosses the surface boundary of the medium, it undergoes a discontinuity. The electric field can be resolved into normal and tangential components. The amount by which the field changes at any boundary is given by the difference between the field components above and below the surface boundary.
The surface integral of an electric field is given by Gauss's law in integral form and is related to...
446
Magnetostatic Boundary Conditions01:28

Magnetostatic Boundary Conditions

893
An electric field suffers a discontinuity at a surface charge. Similarly, a magnetic field is discontinuous at a surface current. The perpendicular component of a magnetic field is continuous across the interface of two magnetic mediums. In contrast, its parallel component, perpendicular to the current, is discontinuous by the amount equal to the product of the vacuum permeability and the surface current. Like the scalar potential in electrostatics, the vector potential is also continuous...
893
Boundary Conditions: Lossless Lines01:21

Boundary Conditions: Lossless Lines

88
Consider a single-phase, two-wire, lossless transmission line terminated by an impedance at the receiving end and a source with Thevenin voltage and impedance at the sending end. The line, with length, has a surge impedance and wave velocity determined by the line's inductance and capacitance.
At the receiving end, the boundary condition states that the voltage equals the product of the receiving-end impedance and current. This relationship is expressed as a function of the incident and...
88
Multimachine Stability01:25

Multimachine Stability

150
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
150
Boundary Conditions for Current Density01:25

Boundary Conditions for Current Density

834
Current density becomes discontinuous across an interface of materials with different electrical conductivities. The normal component of the current density is continuous across the boundary.
834

You might also read

Related Articles

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

Sort by
Same author

Machine-learning perspectives on Volterra system identification.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2025
Same author

Microphone array analysis of the first non-axisymmetric mode for the detection of pipe conditions.

The Journal of the Acoustical Society of America·2024
Same author

Boundary admittance estimation for wave-based acoustic simulations using Bayesian inference.

JASA express letters·2023
Same author

Microphone array analysis for simultaneous condition detection, localization, and classification in a pipe.

The Journal of the Acoustical Society of America·2023
Same author

A Bayesian Method for Material Identification of Composite Plates via Dispersion Curves.

Sensors (Basel, Switzerland)·2023
Same author

A sampling-based approach for information-theoretic inspection management.

Proceedings. Mathematical, physical, and engineering sciences·2022

Related Experiment Video

Updated: Jun 17, 2025

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
13:07

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

3.8K

Calibrating the Discrete Boundary Conditions of a Dynamic Simulation: A Combinatorial Approximate Bayesian

Jah Shamas1, Tim Rogers1, Anton Krynkin1

  • 1Department of Mechanical Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, UK.

Sensors (Basel, Switzerland)
|August 10, 2024
PubMed
Summary

A new combinatorial approximate Bayesian computation sequential Monte Carlo (ABC-SMC) algorithm estimates high-dimensional binary parameters. This method enhances uncertainty quantification in structural dynamics, proving effective for complex systems.

Keywords:
Bayesian inferenceMonte Carlo simulationstructural vibrationuncertainty quantification

More Related Videos

Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

3.4K
Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

4.4K

Related Experiment Videos

Last Updated: Jun 17, 2025

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
13:07

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

3.8K
Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

3.4K
Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

4.4K

Area of Science:

  • Computational Statistics
  • Bayesian Inference
  • Machine Learning

Background:

  • Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) is used for parameter estimation when likelihood functions are intractable.
  • Conventional ABC-SMC methods are primarily designed for continuous parameters.
  • High-dimensional binary parameter inference remains a challenge in many scientific domains.

Purpose of the Study:

  • To introduce a novel adaptation of ABC-SMC, termed combinatorial ABC-SMC, for inferring high-dimensional binary parameters.
  • To address the limitations of existing methods in handling non-continuous, complex parameter spaces.
  • To demonstrate the efficacy of the proposed method in a practical structural dynamics application.

Main Methods:

  • The study adapts the conventional ABC-SMC algorithm by modifying the proposal distribution to target high-dimensional binary variables.
  • A simulating model replaces the intractable likelihood function, generating artificial data for inference.
  • The combinatorial ABC-SMC scheme iteratively refines parameter estimates through successive 'waves' of sampling.

Main Results:

  • The combinatorial ABC-SMC method successfully infers uncertain boundary conditions in a simulated fiber-optic sensor structural dynamics experiment.
  • The algorithm's performance was validated using multiple vibration datasets, confirming its robustness.
  • Comparative analysis of different metric functions highlighted their impact on the algorithm's convergence.

Conclusions:

  • The proposed combinatorial ABC-SMC algorithm offers a robust solution for parameter estimation in high-dimensional binary spaces.
  • This novel approach enhances uncertainty quantification capabilities, particularly in fields like structural dynamics.
  • The method's adaptability and validated efficacy make it a valuable tool for complex inferential problems where likelihoods are unavailable.