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Related Concept Videos

Design Example: Flow of Oil Through Circular Pipes01:25

Design Example: Flow of Oil Through Circular Pipes

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Understanding fluid flow behavior through pipes is critical in fluid mechanics, especially in applications like oil transportation through pipelines. Hagen-Poiseuille's law provides an exact solution derived from the Navier-Stokes equations for steady, incompressible, and laminar flow within a circular pipe. Hagen-Poiseuille's law helps determine the necessary pressure drop across a pipeline section by determining parameters like pipe length, radius, oil viscosity, and the desired...
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Pipe Flowrate Measurement: Problem Solving01:28

Pipe Flowrate Measurement: Problem Solving

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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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Pipe Flowrate Measurement01:28

Pipe Flowrate Measurement

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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.
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Multiple Pipe Systems01:21

Multiple Pipe Systems

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Multipipe systems consist of complex configurations of interconnected pipes designed to transport fluids efficiently across intricate networks. They are essential in engineering applications requiring precise control over flow distribution, pressure, and head loss. They are categorized into series, parallel, loop, and network configurations, each distinguished by unique flow characteristics and applications.
Series Configuration
In a series configuration, fluid flows sequentially from one pipe...
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Single Pipe Systems01:24

Single Pipe Systems

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In pipe flow analysis, problems are typically categorized into three types — Type I, Type II, and Type III — based on the known parameters and the desired outcome. Each type of problem addresses specific engineering requirements using fluid properties, pipe characteristics, and operational conditions.
In a Type I problem, fluid properties (density and viscosity), pipe characteristics (including diameter, length, and surface roughness), and the flow rate or average velocity are...
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General Characteristics of Pipe Flow II01:24

General Characteristics of Pipe Flow II

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When fluid enters a pipe, it first passes through the entrance region, where the velocity profile adjusts due to viscous effects. In this region, a boundary layer forms along the pipe walls and grows until it fully occupies the pipe's cross-section. Once the boundary layer merges, the flow becomes fully developed, with a steady velocity profile that remains consistent along the pipe's length.
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Related Experiment Video

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Visualization of Flow Field Around a Vibrating Pipeline Within an Equilibrium Scour Hole
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Optimization for Pipeline Corrosion Sensor Placement in Oil-Water Two-Phase Flow Using CFD Simulations and Genetic

Shuomang Shi1, Baiyu Jiang2, Simone Ludwig3

  • 1Department of Civil, Construction, and Environmental Engineering, North Dakota State University, Fargo, ND 58105, USA.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
Summary

This study introduces a hybrid Computational Fluid Dynamics (CFD) and Genetic Algorithm (GA) model to optimize sensor placement for detecting internal pipeline corrosion. The method improves safety by efficiently identifying high-risk areas.

Keywords:
Computational Fluid Dynamics (CFD)Genetic Algorithm (GA)Structural Health Monitoring (SHM)corrosionpipelines

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Area of Science:

  • Engineering
  • Materials Science
  • Computational Science

Background:

  • Internal corrosion poses significant risks to pipeline safety, necessitating effective Structural Health Monitoring (SHM).
  • Current methods often require extensive sensor deployment to cover areas prone to high corrosion rates.
  • Optimizing sensor placement is crucial for cost-effective and comprehensive corrosion detection.

Purpose of the Study:

  • To develop and validate a hybrid modeling strategy for optimizing sensor placement in pipelines for internal corrosion monitoring.
  • To integrate Computational Fluid Dynamics (CFD) for flow simulation and Genetic Algorithm (GA) for optimization.
  • To enhance the efficiency and accuracy of corrosion detection systems in the pipeline industry.

Main Methods:

  • A hybrid approach combining CFD for simulating oil-water two-phase flow and GA for global search optimization.
  • CFD-based corrosion rate prediction, validated against experimental data.
  • GA optimization incorporating fitness criteria for sensing effectiveness and sensor coverage cost.

Main Results:

  • The hybrid strategy demonstrated high accuracy in sensor placement for corrosion detection in pipeline fittings.
  • Case studies on U-shaped, upward-inclined, and downward-inclined pipes showed optimal fitness values of 0.9415, 0.9064, and 0.9183, respectively.
  • The model effectively balances sensing capabilities with the economic considerations of sensor deployment.

Conclusions:

  • The hybrid CFD-GA modeling strategy offers a promising tool for practical sensor layout design in pipeline corrosion monitoring.
  • This approach can significantly improve the safety and efficiency of Structural Health Monitoring in transmission and gathering pipelines.
  • The validated methodology provides a foundation for advanced sensor placement optimization in industrial applications.