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Rapidly Varying Flow01:24

Rapidly Varying Flow

163
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...
163
Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

191
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...
191
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

140
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...
140
Pipe Flowrate Measurement01:28

Pipe Flowrate Measurement

845
In pipe flow measurement, orifice, nozzle, and Venturi meters are commonly used to determine fluid flowrates by constricting the flow area, which increases fluid velocity and reduces pressure. This pressure difference, governed by Bernoulli's principle and adjusted for real-world conditions, is essential for calculating flowrate. Each meter type is suited to specific applications based on accuracy, efficiency, and compatibility with various flow conditions.
The orifice meter is a simple,...
845
Steady Flow of a Fluid Stream01:27

Steady Flow of a Fluid Stream

424
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...
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Pipe Flowrate Measurement: Problem Solving01:28

Pipe Flowrate Measurement: Problem Solving

610
A spray tank system is engineered to uniformly distribute a pest-control liquid across plants by using a pressurized mechanism. The tank, pressurized to 150 kPa, holds the pesticide at a height of 0.80 meters. Liquid flows from the tank through a 1.9 meter pipe with a diameter of 0.015 meters, angled at 0.698 radians, ultimately reaching a 0.007 meter nozzle that sprays the pesticide. Accurate calculation of the system's flow rate is crucial to ensure uniform application, and this is...
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Related Experiment Video

Updated: Oct 7, 2025

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
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Flow Sensing-Based Congestion Detection for D2D Streaming on a 5G gNB.

Chongdeuk Lee1

  • 1Division of Electronic Engineering, Jeonbuk National University, Jeonju-si 54896, Korea.

Sensors (Basel, Switzerland)
|January 11, 2022
PubMed
Summary

This study introduces a new algorithm to manage traffic flow in device-to-device (D2D) communications, improving streaming quality. The flow sensing-based congestion detecting algorithm (FS-CDA) optimizes performance in 5G networks.

Keywords:
5G wireless mobileD2D streamingDUEchannel bandwidthmedia flow

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Area of Science:

  • Wireless Communications
  • Network Engineering
  • Data Streaming

Background:

  • High-quality streaming in device-to-device (D2D) communications requires monitoring of encoding, decoding, and flow rates.
  • Traffic flow imbalance and congestion negatively impact D2D streaming performance.

Purpose of the Study:

  • To propose a novel algorithm, FS-CDA, for detecting and controlling flow imbalance in D2D streaming.
  • To enhance D2D streaming service performance in 5G wireless mobile networks by preventing high congestion rates.

Main Methods:

  • Developed the flow sensing-based congestion detecting algorithm (FS-CDA).
  • Implemented transmission rate monitoring, rate adjustment, and underflow/overflow sensing.
  • Derived individual weights for streaming flow versions for performance evaluation.

Main Results:

  • The proposed FS-CDA algorithm effectively controls traffic flow rates influenced by bandwidth, bit errors, and radio interference.
  • Simulation results demonstrate superior performance compared to existing methods in average congestion control ratio, PSNR, and average throughput.

Conclusions:

  • FS-CDA significantly enhances D2D streaming service performance in 5G networks.
  • The algorithm provides effective congestion control and rate management for optimized streaming.