Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

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

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
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

相关实验视频

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

一个基于物理学的图形神经网络,可保护动态系统的线性和角动量.

Vinay Sharma1, Olga Fink2

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

Nature communications
|January 15, 2026
PubMed
概括
此摘要是机器生成的。

我们介绍了DYNAMI-CAL GRAPHNET,一个新的物理信息图形神经网络. 该模型准确预测复杂的多体动态,确保实时应用的物理一致性和可解释性.

更多相关视频

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

相关实验视频

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

科学领域:

  • 物理 物理学 物理
  • 计算机科学 计算机科学
  • 工程 工程师 工程师 工程师

背景情况:

  • 对多体动态系统的准确建模对于预测和推理至关重要.
  • 传统的基于物理学的模型在可扩展性和计算成本方面扎.
  • 数据驱动的图形神经网络 (GNN) 往往缺乏物理一致性和可解释性.

研究的目的:

  • 提出DYNAMI-CAL GRAPHNET,一个基于物理的图形神经网络.
  • 将GNN学习与基于物理的诱导偏差集成在一起,以改进建模.
  • 解决动态系统中传统和纯数据驱动方法的局限性.

主要方法:

  • 开发了DYNAMI-CAL GRAPHNET,这是一个新的物理信息图形神经网络.
  • 使用等价边缘-局部参考框架强制对保持线性和角动量.
  • 设计用于旋转等差,转换不变和顺序等差.

主要成果:

  • 实现了对节点动态的物理一致预测.
  • 提供了可解释的,边向的线性和角度脉冲.
  • 在3D颗粒系统上证明了稳定的错误积累,有效的推断和对异质相互作用和外部力量的稳健处理.

结论:

  • DYNAMI-CAL GRAPHNET提供了复杂的多体动态系统的准确,可解释和实时建模.
  • 允许推断的力量和时刻,同时有效地处理复杂的相互作用.
  • 对于机器人,航空航天工程,材料科学,控制系统和机械过程优化有价值.