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

Node Analysis for AC Circuits01:14

Node Analysis for AC Circuits

Consider an angioplasty system featuring a catheter equipped with a turbine, a critical tool for removing plaque deposits from coronary arteries. This intricate medical device operates using a circuit model reminiscent of a dual-node RLC circuit powered by a current-controlled voltage source.
To unravel the complexities of this system, nodal analysis is employed, a powerful technique founded on Kirchhoff's current law (KCL), which remains valid for phasors. AC circuits can effectively be...
Multimachine Stability01:25

Multimachine Stability

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:
Transmission-Line Differential Equations01:26

Transmission-Line Differential Equations

Transmission lines are essential components of electrical power systems. They are characterized by the distributed nature of resistance (R), inductance (L), and capacitance (C) per unit length. To analyze these lines, differential equations are employed to model the variations in voltage and current along the line.
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured from the...
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
Bewley Lattice Diagram01:12

Bewley Lattice Diagram

The Bewley lattice diagram, developed by L. V. Bewley, effectively organizes the reflections occurring during transmission-line transients. It visually represents how voltage waves propagate and reflect within a transmission line, making it easier to understand the complex interactions that occur.
Bus Impedance Matrix01:24

Bus Impedance Matrix

Calculating subtransient fault currents for three-phase faults in an N-bus power system involves using the positive-sequence network. When a three-phase short circuit occurs at a specific bus, the analysis uses the superposition method to evaluate two separate circuits.
In the first circuit, all machine voltage sources are short-circuited, leaving only the prefault voltage source at the fault location. The positive-sequence bus impedance matrix can be determined by solving the nodal equations,...

You might also read

Related Articles

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

Sort by
Same author

Wafer-scale CMOS foundry silicon-on-insulator devices for integrated temporal pulse compression.

Nanophotonics (Berlin, Germany)·2025
Same author

Immunoglobulin gene expression profiles and microbiome characteristics in periodontitis in nonhuman primates.

Molecular immunology·2022
Same author

Variations in temporal trends in non-traumatic dental condition related emergencies.

Journal of public health dentistry·2022
Same author

Oral Microbiome and Gingival Gene Expression of Inflammatory Biomolecules With Aging and Periodontitis.

Frontiers in oral health·2022
Same author

Transcriptomic phases of periodontitis lesions using the nonhuman primate model.

Scientific reports·2021
Same author

Variations in Schedule III prescription patterns in a Medicaid population pre- and post-policy.

Scientific reports·2021
Same journal

CALF-SBM: A covariate-assisted latent factor stochastic block model.

Physica A·2026
Same journal

Estimating dynamic transmission rates with a Black-Karasinski process in stochastic SIHR models using particle MCMC.

Physica A·2026
Same journal

Unsupervised pattern and outlier detection for pedestrian trajectories using diffusion maps.

Physica A·2025
Same journal

Calculating Structure Factors of Protein Solutions by Atomistic Modeling of Protein-Protein Interactions.

Physica A·2024
Same journal

Estimating pandemic effects in urban mass transportation systems: An approach based on visibility graphs and network similarity.

Physica A·2023
Same journal

Exact solution for the Anisotropic Ornstein-Uhlenbeck process.

Physica A·2023
See all related articles

Related Experiment Video

Updated: Jun 25, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Delay estimation in a two-node acyclic network.

Radhakrishnan Nagarajan

    Physica A
    |February 14, 2009
    PubMed
    Summary
    This summary is machine-generated.

    Cross-correlation analysis can misidentify multiple time delays in driver-dependent systems. Estimating delays using increment processes offers a potential solution for accurate causal relationship analysis.

    Related Experiment Videos

    Last Updated: Jun 25, 2026

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
    05:30

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

    Published on: September 8, 2023

    Area of Science:

    • * Causal inference and time series analysis.
    • * Network dynamics and signal processing.

    Background:

    • * Cross-correlation is a standard method for estimating time delays between processes.
    • * Identifying causal relationships often relies on accurate time delay estimation.
    • * Previous methods may struggle with complex correlated driver processes.

    Purpose of the Study:

    • * To investigate the impact of monotonically decreasing correlation functions on time delay estimation.
    • * To explore the potential for spurious multiple delay identification using cross-correlation.
    • * To evaluate an alternative delay estimation method using increment processes.

    Main Methods:

    • * Analysis of a two-node acyclic network with one and two delays.
    • * Application of cross-correlation to driver and dependent processes.
    • * Examination of increment processes versus original processes for delay estimation.
    • * Consideration of short-range, long-range, and coarse-grained correlated drivers.

    Main Results:

    • * Cross-correlation analysis can lead to the spurious identification of multiple delays.
    • * The accuracy of delay estimation is influenced by the driver's correlation properties.
    • * Delay estimation using increment processes shows promise under specific constraints.

    Conclusions:

    • * Standard cross-correlation methods may be unreliable for complex correlated systems.
    • * Increment process analysis offers a viable alternative for more robust delay estimation.
    • * Further research is needed to refine delay estimation techniques in network analysis.