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相关概念视频

Equilibrium Conditions for a Particle01:23

Equilibrium Conditions for a Particle

991
When an object is in equilibrium, it is either at rest or moving with a constant velocity. There are two types of equilibrium: static and dynamic. Static equilibrium occurs when an object is at rest, while dynamic equilibrium occurs when an object is moving with a constant velocity. In both cases, there must be a balance of forces acting on the object.
To understand the concept of equilibrium, let us first consider the forces acting on an object. When different forces act on an object, they can...
991
Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving01:23

Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving

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Consider a wooden box and a cylinder of known masses m1 and m2, respectively,  hanging from a ceiling with the help of a massless pulley system.
182
Principle of Linear Impulse and Momentum for a Single Particle01:20

Principle of Linear Impulse and Momentum for a Single Particle

585
Linear momentum is a fundamental concept in physics that describes the motion of an object. It is a vector quantity, having a magnitude equal to the product of its mass and its velocity, and direction along the object's velocity. On the other hand, linear impulse, also known as momentum impulse, is a concept in physics related to the change in the linear momentum of an object. Impulse is a vector quantity defined as the product of force and the time over which the force is applied.
Delving...
585
First Law: Particles in Two-dimensional Equilibrium01:18

First Law: Particles in Two-dimensional Equilibrium

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Recall that a particle in equilibrium is one for which the external forces are balanced. Static equilibrium involves objects at rest, and dynamic equilibrium involves objects in motion without acceleration; but it is important to remember that these conditions are relative. For instance, an object may be at rest when viewed from one frame of reference, but that same object would appear to be in motion when viewed by someone moving at a constant velocity.
Newton's first law tells us about...
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The Uncertainty Principle04:08

The Uncertainty Principle

23.0K
Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
23.0K
Principle of Linear Impulse and Momentum for a System of Particles01:21

Principle of Linear Impulse and Momentum for a System of Particles

247
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...
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相关实验视频

Updated: May 25, 2025

Image-based Lagrangian Particle Tracking in Bed-load Experiments
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Image-based Lagrangian Particle Tracking in Bed-load Experiments

Published on: July 20, 2017

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基于物理的深度学习用于随机粒子动态估计.

Yongyu Zhang1, Junlun Zhu1, Hao Xie2

  • 1Department of Chemistry, Tsinghua University, Beijing 100084, People's Republic of China.

Proceedings of the National Academy of Sciences of the United States of America
|February 27, 2025
PubMed
概括
此摘要是机器生成的。

我们开发了一种新的AI方法,即随机粒子信息神经网络 (SPINN),以精确分析粒子运动. SPINN提高了对各种材料复杂的扩散动态的理解.

关键词:
异常扩散的异常扩散机器学习是机器学习.单颗粒追踪器是一个单颗粒追踪器.随机微分方程 随机微分方程 随机微分方程

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A Protocol for Real-time 3D Single Particle Tracking
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An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
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An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

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相关实验视频

Last Updated: May 25, 2025

Image-based Lagrangian Particle Tracking in Bed-load Experiments
10:32

Image-based Lagrangian Particle Tracking in Bed-load Experiments

Published on: July 20, 2017

8.9K
A Protocol for Real-time 3D Single Particle Tracking
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A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

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An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
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An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

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科学领域:

  • 物理 物理学 物理
  • 生物物理学的生物物理.
  • 材料科学 材料科学 材料科学

背景情况:

  • 单粒子追踪为研究复杂系统提供了高精度.
  • 微/纳米尺度的粒子动力学本质上是随机的,复杂化了分析.
  • 当前的方法通常假设伪稳定状态,限制准确性.

研究的目的:

  • 引入一种新的深度学习框架,即随机粒子信息神经网络 (SPINN).
  • 通过整合随机微分方程来建模和推断粒子扩散动力学.
  • 提高随机动态的时间分辨率,以改善分析.

主要方法:

  • 开发了SPINN,这是一个基于物理的深度学习框架.
  • 集成的随机微分方程用于模拟扩散.
  • 自主探索的参数空间和区分的决定性/随机元件.

主要成果:

  • 在异常扩散数据集上验证了SPINN,减少了变化并保持了相关性.
  • 准确地描述了不同的随机扩散过程.
  • 在水凝凝过程中揭示了增强的微风学特性.
  • 在液-液相分离过程中发现的界面动力学.

结论:

  • SPINN 提高了复杂的扩散行为的估计和预测.
  • 该框架提供了关于中观尺度下潜在的物理机制的见解.
  • 增强的时间分辨率有助于对随机动态的详细分析.