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

Eulerian and Lagrangian Flow Descriptions01:22

Eulerian and Lagrangian Flow Descriptions

1.4K
Fluid flow analysis is critical in many scientific and engineering disciplines, and two principal approaches are used to describe this flow: the Eulerian and Lagrangian methods. These methods offer different perspectives on monitoring and analyzing the motion of fluids, each with distinct advantages depending on the scenario.
The Eulerian method focuses on fixed points in space where fluid properties, such as velocity, pressure, and temperature, are observed as the fluid moves between these...
1.4K
Laminar and Turbulent Flow01:07

Laminar and Turbulent Flow

8.5K
Fluid dynamics is the study of fluids in motion. Velocity vectors are often used to illustrate fluid motion in applications like meteorology. For example, wind—the fluid motion of air in the atmosphere—can be represented by vectors indicating the speed and direction of the wind at any given point on a map. Another method for representing fluid motion is a streamline. A streamline represents the path of a small volume of fluid as it flows. When the flow pattern changes with time, the...
8.5K
Typical Model Studies01:30

Typical Model Studies

349
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
349
Navier–Stokes Equations01:28

Navier–Stokes Equations

449
For incompressible Newtonian fluids, where density remains constant, stresses show a linear relationship with the deformation rate, defined by normal and shear stresses. Normal stresses depend on the pressure exerted on the fluid and the rate of deformation in specific directions, which determines how fluid flows under varying pressures. Shear stresses, on the other hand, act tangentially across fluid layers. They explain how adjacent fluid layers slide relative to one another, connecting...
449
Turbulent Flow01:24

Turbulent Flow

156
Turbulent flow is characterized by unpredictable fluctuations in velocity and pressure, which result in a chaotic fluid movement distinct from the orderly patterns of laminar flow. While laminar flow is governed by smooth, parallel layers with minimal mixing, turbulent flow exhibits highly irregular, three-dimensional patterns. This behavior arises due to instabilities in the fluid's velocity profile, and amplifies as the flow velocity increases. Minor disturbances, known as turbulent...
156
Boundary Layer Characteristics01:18

Boundary Layer Characteristics

58
When a fluid encounters a solid surface, a boundary layer forms due to the interaction between the fluid's motion and the stationary surface. This phenomenon is characterized by a thin region adjacent to the surface where viscous forces dominate, influencing the fluid's velocity profile. The development of the boundary layer begins at the leading edge of the surface and evolves as the fluid moves downstream.As the fluid flows over the surface, friction between the fluid and the wall slows down...
58

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

Global cascade of kinetic energy in the ocean and the atmospheric imprint.

Science advances·2023
Same author

Inferring turbulent environments via machine learning.

The European physical journal. E, Soft matter·2022
Same author

A few-layer graphene for advanced composite PVDF membranes dedicated to water desalination: a comparative study.

Nanoscale advances·2022
Same author

Global energy spectrum of the general oceanic circulation.

Nature communications·2022
Same author

λ-Navier-Stokes turbulence.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2022
Same author

Dynamics of polydisperse multiple emulsions in microfluidic channels.

Physical review. E·2022

相关实验视频

Updated: Jun 15, 2025

The Diffusion of Passive Tracers in Laminar Shear Flow
08:01

The Diffusion of Passive Tracers in Laminar Shear Flow

Published on: May 1, 2018

8.5K

通过生成扩散模型的合成拉格朗流动.

T Li1, L Biferale1, F Bonaccorso1

  • 1Dept. of Physics and INFN, University of Rome Tor Vergata, Rome, Italy.

Nature machine intelligence
|June 13, 2025
PubMed
概括

一个新的机器学习模型在流中生成现实的粒子轨迹,克服了当前模拟方法的局限性. 这一突破提供了高质量的合成数据,以推进对拉格朗动荡的研究.

科学领域:

  • 流体动力学 流体动力学
  • 流物理 流物理
  • 机器学习应用 机器学习应用

背景情况:

  • 拉格朗的流对于理解各种科学领域的分散和混合至关重要.
  • 现有的模型无法准确地捕捉流中的粒子轨迹的统计和拓特征.

研究的目的:

  • 开发一种能够在高雷诺德数流中生成现实的单粒子轨迹的机器学习模型.
  • 为了绕过计算上昂贵的直接数值模拟或实验对拉格朗的数据的需求.

主要方法:

  • 利用最先进的扩散模型,一种机器学习方法.
  • 应用该模型在高雷诺兹数的3D流中生成合成单粒子轨迹.

主要成果:

  • 该模型成功地重现了关键的统计基准,包括脂肪尾分布和异常功率定律.
  • 它准确地捕捉了离散度尺度附近的间歇性,并显示了极端事件的强烈概括性.
  • 在减速和平度统计数据中,在消散量级以下,注意到了轻微的偏差.

结论:

  • 拟议的机器学习方法有效地产生高质量的合成拉格朗流动数据.
  • 这种方法克服了传统模拟和实验的局限性,为研究开辟了新的途径.
关键词:
流体动力学 流体动力学统计物理学的统计物理.

更多相关视频

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
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

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

Published on: December 4, 2017

8.5K

相关实验视频

Last Updated: Jun 15, 2025

The Diffusion of Passive Tracers in Laminar Shear Flow
08:01

The Diffusion of Passive Tracers in Laminar Shear Flow

Published on: May 1, 2018

8.5K
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
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

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

Published on: December 4, 2017

8.5K
  • 生成的数据集可以用于预训练在拉格朗的流研究下游应用.