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相关概念视频

Turbulent Flow01:24

Turbulent Flow

277
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...
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Computed Tomography01:10

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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Laminar and Turbulent Flow01:07

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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...
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Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

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Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures...
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Deconvolution01:20

Deconvolution

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Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
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Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

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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...
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相关实验视频

Updated: Sep 11, 2025

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques
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用模型驱动和数据驱动的深度学习来计算大气动荡的幽灵成像.

Yangjun Li, Hangyu Zhang, Chenzhe Jiang

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    概括
    此摘要是机器生成的。

    计算幽灵成像 (CGI) 克服了大气流的扭曲. 这项研究整合了基于模型和数据的深度学习,以实现强大的,高质量的成像,即使采样率低.

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    相关实验视频

    Last Updated: Sep 11, 2025

    Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques
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    Published on: March 12, 2019

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    科学领域:

    • 光学和光子学 在光学和光子学.
    • 计算成像技术的成像
    • 机器学习应用 机器学习应用

    背景情况:

    • 大气动荡严重扭曲图像,挑战传统的成像技术.
    • 计算幽灵成像 (CGI) 提供流阻力,但受到采样速率的限制.
    • 现有的CGI深度学习方法缺乏通用性和解释性.

    研究的目的:

    • 开发一种用于大气动荡的新型计算幽灵成像方法.
    • 在低采样条件下增强图像重建性能.
    • 将模型驱动和数据驱动的深度学习结合起来,以提高概括性和可解释性.

    主要方法:

    • 集成基于模型和数据的深度学习策略,用于CGI.
    • 利用数据驱动方法的隐性特征和模型驱动方法的概括.
    • 使用二次相关算法进行对象重建.

    主要成果:

    • 拟议的混合深度学习 (CGI) 方法在各种采样比率中显示出强度.
    • 这种方法有效地减轻了大气流引起的图像扭曲.
    • 模拟和实验结果证实了该方法的高质量成像能力.

    结论:

    • 综合模型和数据驱动的深度学习方法为CGI在动荡环境中提供了卓越的解决方案.
    • 这种方法克服了传统的CGI和纯数据驱动技术的局限性.
    • 这些发现为在大气流下实现高准确度成像提供了一条有效的途径.