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関連する概念動画

Poiseuille's Law and Reynolds Number01:10

Poiseuille's Law and Reynolds Number

6.9K
Any fluid in a horizontal tube can flow due to pressure differences—fluid flows from high to low pressure. The flow rate (Q) is the ratio of pressure difference and resistance through a horizontal tube. The greater the pressure difference, the higher the flow rate. The flow resistance is expressed as:
6.9K
The Buckingham Pi Theorem01:09

The Buckingham Pi Theorem

914
The Buckingham Pi theorem provides a structured method to simplify fluid dynamics problems by reducing complex systems of variables to dimensionless terms.
914
Major Losses in Pipes01:28

Major Losses in Pipes

1.3K
When a fluid flows through a pipe, it experiences energy losses due to frictional resistance along the pipe walls, known as major losses. These energy losses result in a pressure drop, which varies based on the flow conditions — whether laminar or turbulent — and the specific physical properties of the fluid and pipe.
Fluid flow can be classified as laminar or turbulent, primarily based on the Reynolds number. This dimensionless number reflects the relative influence of inertial to...
1.3K
Reynolds Transport Theorem01:24

Reynolds Transport Theorem

1.3K
The Reynolds transport theorem provides a framework to relate the time rate of change of an extensive property within a system to that in a control volume, which is crucial for analyzing fluid dynamics. Extensive properties, such as mass, velocity, acceleration, temperature, and momentum, can be expressed in terms of the mass of a fluid portion. These properties are called extensive because they depend on the system's size, while intensive properties are their corresponding values per unit...
1.3K
Dimensionless Groups in Fluid Mechanics01:15

Dimensionless Groups in Fluid Mechanics

428
Dimensionless groups in fluid mechanics provide simplified ratios that help analyze fluid behavior without relying on specific units. The Reynolds number (Re), which represents the ratio of inertial to viscous forces, distinguishes between laminar and turbulent flows, making it essential in the design of pipelines and aerodynamic surfaces. The Froude number (Fr), the ratio of inertial to gravitational forces, is particularly useful in predicting wave formation and hydraulic jumps in...
428
Turbulent Flow01:24

Turbulent Flow

276
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...
276

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関連する実験動画

Updated: Sep 10, 2025

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
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Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

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高レイノルド数タービュレンスデータベース:AeroFlowData

Weiwei Zhang1,2,3, Xianglin Shan4,5,6, Yilang Liu4,5,6

  • 1School of Aeronautics, Northwestern Polytechnical University, Xi'an, 710072, China. aeroelastic@nwpu.edu.cn.

Scientific data
|August 27, 2025
PubMed
まとめ

科学的研究を支援するために,新しい高レイノルズ数乱流データベース"AeroFlowData"が作成されました. 複雑なエンジニアリングアプリケーションのための広範なデータを提供し,既存の乱流データベースの限界を克服します.

さらに関連する動画

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions
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Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions

Published on: February 22, 2018

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Power Input Measurements in Stirred Bioreactors at Laboratory Scale
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Power Input Measurements in Stirred Bioreactors at Laboratory Scale

Published on: May 16, 2018

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関連する実験動画

Last Updated: Sep 10, 2025

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
13:02

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

Published on: February 27, 2016

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Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions
11:51

Visually Based Characterization of the Incipient Particle Motion in Regular Substrates: From Laminar to Turbulent Conditions

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Power Input Measurements in Stirred Bioreactors at Laboratory Scale
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Power Input Measurements in Stirred Bioreactors at Laboratory Scale

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科学分野:

  • 流体力学
  • コンピュータ科学

背景:

  • 渦巻シミュレーションは多層構造によって困難です
  • 既存の乱流データベースには,エンジニアリングアプリケーションのための高レイノルズ数データがない.

研究 の 目的:

  • 世界的に共有される高レイノルズ数乱流データベースを確立する.
  • トルブルエンスの機械学習と複雑なエンジニアリングの流れに関する研究を支援する.

主な方法:

  • 数値シミュレーション
  • 実験的な測定
  • データの同化

主要な成果:

  • AeroFlowDataを確立し,高レイノルズ数タービュレンスデータベースを確立しました.
  • データベースには,様々なアプリケーションで約40のモデルが含まれています.
  • 500以上のフロー条件と ~100TBのデータを含んでいます.

結論:

  • AeroFlowDataは,高レイノルズ数による乱流データへのニーズに対応しています.
  • このデータベースは,渦巻の研究と機械学習の進歩を容易にする.