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

Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

63
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
63
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

59
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
59
Velocity and Acceleration in Steady and Unsteady Flow01:11

Velocity and Acceleration in Steady and Unsteady Flow

100
In fluid mechanics, velocity and acceleration are key concepts for analyzing particle motion in both steady and unsteady flow. Consider a fluid particle moving along a pathline, where its velocity depends on its position and time. The particle's acceleration is obtained by differentiating the velocity with respect to time.
The acceleration can be generalized to any point in the flow, and expressed as components along three perpendicular directions, representing changes in velocity over...
100
Rapidly Varying Flow01:24

Rapidly Varying Flow

56
Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
56
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
Steady Flow of a Fluid Stream01:27

Steady Flow of a Fluid Stream

275
Consider a control volume, such as a pipe with solid boundaries, through which fluid flows and changes direction due to the impulse exerted by the resulting force from the pipe walls. In steady flow, the mass of fluid entering the control volume at a given time, t, with velocity v1, is equal to the mass leaving after infinitesimal time dt, with velocity v2.
During this process, the momentum of the fluid within the control volume remains constant over the time interval dt. By applying the...
275

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

Modeling Reveals How Direct-Acting Antivirals Redirect HBV Capsid Assembly Pathways to Noninfectious Products.

bioRxiv : the preprint server for biology·2026
Same author

Cycling molecular assemblies for Golgi imaging and disruption.

Nature communications·2026
Same author

From toroids to helical tubules: Kirigami-inspired programmable assembly of two-periodic curved crystals from DNA origami.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Measuring multisubunit mechanics of geometrically programmed colloidal assemblies via cryo-EM multi-body refinement.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Topology and kinetic pathways of colloidosome assembly and disassembly.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Computer Simulations Show That Liquid-Liquid Phase Separation Enhances Self-Assembly.

ACS nano·2025
Same journal

Nanopore sequencing with proteins: synchronization and dischronization of molecular dynamics simulations with laboratory and industrial developments.

Soft matter·2026
Same journal

Catanionics from biosurfactants and regular surfactants: miscibility and structure.

Soft matter·2026
Same journal

Adhesives with a thickness smaller than the fractocohesive length enhance adhesion.

Soft matter·2026
Same journal

Non-equilibrium phase transitions in hybrid Voronoi models of cell colonies.

Soft matter·2026
Same journal

Effects of methoxy substituents on self-assembly and gelation performance of benzamide-based organogelators.

Soft matter·2026
Same journal

Rheology of <i>Escherichia coli</i> suspensions with various bacterial morphologies and motion characteristics.

Soft matter·2026
查看所有相关文章

相关实验视频

Updated: Jun 14, 2025

Determining 3D Flow Fields via Multi-camera Light Field Imaging
14:25

Determining 3D Flow Fields via Multi-camera Light Field Imaging

Published on: March 6, 2013

16.6K

从实验数据中测量速度场的深度学习光流.

Phu N Tran1, Sattvic Ray2, Linnea Lemma1,2

  • 1Department of Physics, Brandeis University, Waltham, MA 02453, USA. hagan@brandeis.edu.

Soft matter
|September 3, 2024
PubMed
概括
此摘要是机器生成的。

基于深度学习的光流 (DLOF) 准确地量化了基于微管的活性阴性流,在密集条件下优于粒子图像速度测量 (PIV). DLOF为软和生物物理流体动力学提供了一种多功能工具.

更多相关视频

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques
10:53

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Published on: March 12, 2019

7.0K
Blood Flow Imaging with Ultrafast Doppler
05:57

Blood Flow Imaging with Ultrafast Doppler

Published on: October 14, 2020

7.6K

相关实验视频

Last Updated: Jun 14, 2025

Determining 3D Flow Fields via Multi-camera Light Field Imaging
14:25

Determining 3D Flow Fields via Multi-camera Light Field Imaging

Published on: March 6, 2013

16.6K
Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques
10:53

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Published on: March 12, 2019

7.0K
Blood Flow Imaging with Ultrafast Doppler
05:57

Blood Flow Imaging with Ultrafast Doppler

Published on: October 14, 2020

7.6K

科学领域:

  • 生物物理学的生物物理.
  • 软物质物理学 软物质物理学
  • 流体动力学 流体动力学

背景情况:

  • 基于微管的活体体质表现出复杂的流体流.
  • 量化这些流量对于理解活性物质系统至关重要.
  • 像粒子图像速度计 (PIV) 这样的传统方法在密集或复杂的生物样本中面临局限性.

研究的目的:

  • 评估基于深度学习的光流 (DLOF) 来量化主动阴性流.
  • 在不同的样本标记密度下,将DLOF性能与PIV进行比较.
  • 建立DLOF作为生物物理流体流量测量的强大工具.

主要方法:

  • 深度卷积神经网络被用于从视频中提取DLOF特征.
  • 使用半自动粒子跟踪和被动跟踪珠验证了流速.
  • DLOF和PIV方法应用于不同标签密度的基于微管的活体内马特样本.

主要成果:

  • 对于密集标记的样本,DLOF提供了比PIV更准确的速度场.
  • DLOF成功地沿着阴性导体解决了流量细节,克服了PIV在高密度下对比度的限制.
  • 对于标签稀疏的样本,DLOF给出了与PIV相似的结果,但分辨率更高.

结论:

  • DLOF是一种比PIV更优越的方法,用于量化活性阴性流,特别是在密集条件下.
  • 在复杂的生物物理系统中,DLOF提供了更高的分辨率并克服了PIV的局限性.
  • 这项研究验证了DLOF作为一种多功能和准确的工具,用于在活性,软和生物物质中进行流体流动分析.