Jove
Visualize
Contáctanos
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Videos de Conceptos Relacionados

Conservation of Angular Momentum: Application01:18

Conservation of Angular Momentum: Application

12.2K
A system's total angular momentum remains constant if the net external torque acting on the system is zero. Examples of such systems include a freely spinning bicycle tire that slows over time due to torque arising from friction, or the slowing of Earth's rotation over millions of years due to frictional forces exerted on tidal deformations. However in the absence of a net external torque, the angular momentum remains conserved. The conservation of angular momentum principle requires a...
12.2K
Conservation of Linear Momentum for a System of Particles01:28

Conservation of Linear Momentum for a System of Particles

535
In the dynamic realm of billiards, a fascinating interplay of forces governs the motion of cue balls and stationary balls. When the cue ball collides with a stationary ball, linear momentum is exchanged. The cue ball imparts a fraction of its linear momentum to the stationary ball, causing the cue ball to decelerate while initiating the motion of the stationary ball.
The impulsive force at play during this interaction is of extremely short duration, rendering its impulse negligible. When...
535
Conservation of Angular Momentum01:09

Conservation of Angular Momentum

15.9K
A system's total angular momentum remains constant if the net external torque acting on the system is zero. Considering a system that consists of n tiny particles, the angular momentum of any tiny particle may change, but the system's total angular momentum would remain constant. The principle of conservation of angular momentum only considers the net external torque acting on the system. While there are internal forces exerted by different particles within the system that also produce...
15.9K
Linear Momentum in Control Volume01:13

Linear Momentum in Control Volume

1.3K
Newton's second law is applied to obtain the linear momentum in a control volume in a fluid system. According to this law, the rate of change of linear momentum is equal to the sum of external forces acting on the system. When a control volume matches the fluid system at a specific moment, the forces acting on both are identical. Reynolds transport theorem helps explain this by breaking down the system's linear momentum into two components: the rate of change of linear momentum within...
1.3K
Angular Momentum01:21

Angular Momentum

756
Angular momentum characterizes an object's rotational motion and is defined as the moment of its linear momentum about a specified point O. When a particle moves along a curved path in the x-y plane, the scalar formulation calculates the magnitude of its angular momentum, utilizing the moment arm (d), representing the perpendicular distance from point O to the line of action of the linear momentum. Despite being scalar in formulation, angular momentum is inherently a vector quantity. Its...
756
Principle of Linear Impulse and Momentum for a System of Particles01:21

Principle of Linear Impulse and Momentum for a System of Particles

579
In the context of a system of particles moving relative to an inertial frame of reference, the equation of motion is a crucial tool for understanding the dynamics of the system. This equation, which accounts for external forces acting on each particle, plays a fundamental role in describing the system's behavior.
Notably, internal forces between particles, occurring in equal and opposite collinear pairs, cancel out and are not part of the equation of motion. This exclusion simplifies the...
579

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

Integrating physics and topology in neural networks for learning rigid body dynamics.

Nature communications·2025
Same author

Interactive symbolic regression with co-design mechanism through offline reinforcement learning.

Nature communications·2025
Same author

Calibrated Adaptive Teacher for Domain-Adaptive Intelligent Fault Diagnosis.

Sensors (Basel, Switzerland)·2024
Same author

GEMTELLIGENCE: Accelerating gemstone classification with deep learning.

Communications engineering·2024
Same author

Collective relational inference for learning heterogeneous interactions.

Nature communications·2024
Same author

Learning physics-consistent particle interactions.

PNAS nexus·2023
Same journal

Sub1 contributes to heart failure with preserved ejection fraction driven by aging in mice.

Nature communications·2026
Same journal

The BRCA1-A complex restricts replication fork reversal-dependent DNA repair in ATM deficient cells.

Nature communications·2026
Same journal

Signaling downstream of tumor-stroma interaction regulates mucinous colorectal adenocarcinoma apicobasal polarity.

Nature communications·2026
Same journal

Click-polymerized polyenamine membranes for efficient lithium extraction.

Nature communications·2026
Same journal

Joint trajectories of brain atrophy, white matter hyperintensities and cognition quantify brain maintenance.

Nature communications·2026
Same journal

Proton shuttling at electrochemical interfaces under alkaline hydrogen evolution.

Nature communications·2026
Ver todos los artículos relacionados

Video Experimental Relacionado

Updated: Jan 18, 2026

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
10:32

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

16.0K

Una red neuronal de grafos informada por la física que conserva el momento lineal y angular para sistemas dinámicos

Vinay Sharma1, Olga Fink2

  • 1Intelligent Maintenance and Operations Systems, EPFL, Lausanne, Switzerland.

Nature communications
|January 15, 2026
PubMed
Resumen
Este resumen es generado por máquina.

Presentamos DYNAMI-CAL GRAPHNET, una novedosa red neuronal de grafos informada por la física. Este modelo predice con precisión la dinámica multibody compleja, garantizando la coherencia física y la interpretabilidad para aplicaciones en tiempo real.

Palabras clave:
redes neuronales de grafossistemas dinámicosaprendizaje automáticofísica computacionalrobótica

Más Videos Relacionados

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.9K
Experimental Methods to Study Human Postural Control
08:12

Experimental Methods to Study Human Postural Control

Published on: September 11, 2019

10.0K

Videos de Experimentos Relacionados

Last Updated: Jan 18, 2026

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
10:32

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

16.0K
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.9K
Experimental Methods to Study Human Postural Control
08:12

Experimental Methods to Study Human Postural Control

Published on: September 11, 2019

10.0K

Área de la Ciencia:

  • Física
  • Ciencias de la Computación
  • Ingeniería

Sus antecedentes:

  • La modelización precisa de sistemas dinámicos multibody es crucial para la predicción y la inferencia.
  • Los modelos físicos tradicionales luchan con la escalabilidad y el costo computacional.
  • Las redes neuronales de grafos (GNN) basadas en datos a menudo carecen de coherencia física e interpretabilidad.

Objetivo del estudio:

  • Proponer DYNAMI-CAL GRAPHNET, una red neuronal de grafos informada por la física.
  • Integrar el aprendizaje de GNN con sesgos inductivos basados en la física para mejorar el modelado.
  • Abordar las limitaciones de los enfoques tradicionales y puramente basados en datos en sistemas dinámicos.

Principales métodos:

  • Desarrolló DYNAMI-CAL GRAPHNET, una novedosa red neuronal de grafos informada por la física.
  • Forzó la conservación par a par del momento lineal y angular utilizando marcos de referencia locales de borde equivariantes.
  • Diseñado para equivariancia rotacional, invarianza traslacional y equivariancia de permutación.

Principales resultados:

  • Logró predicciones físicamente consistentes de la dinámica de nodos.
  • Proporcionó impulsos lineales y angulares interpretables a nivel de borde.
  • Demostró acumulación de errores estable, extrapolación efectiva y manejo robusto de interacciones heterogéneas y fuerzas externas en un sistema granular 3D.

Conclusiones:

  • DYNAMI-CAL GRAPHNET ofrece modelado preciso, interpretable y en tiempo real de sistemas dinámicos multibody complejos.
  • Permite la inferencia de fuerzas y momentos al tiempo que maneja de manera eficiente interacciones complejas.
  • Valioso para la robótica, la ingeniería aeroespacial, la ciencia de materiales, los sistemas de control y la optimización de procesos mecánicos.