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Updated: Aug 4, 2025

Visualization of Flow Field Around a Vibrating Pipeline Within an Equilibrium Scour Hole
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Theoretical and experimental research on two-phase flow image reconstruction and flow pattern recognition.

Guoyuan Zhang1, Liewen Wang1, Hao Wang1

  • 1School of Mechano-Electronic Engineering, Xidian University, Xi'an 710071, China.

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Accurately identifying complex two-phase flow patterns is challenging. This study developed advanced electrical resistance tomography and neural network methods, achieving over 97% accuracy for precise flow pattern recognition.

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Area of Science:

  • Fluid Dynamics
  • Tomography
  • Artificial Intelligence

Background:

  • Two-phase flow patterns are complex and difficult to characterize accurately.
  • Existing methods for flow pattern identification have limitations in precision and speed.

Purpose of the Study:

  • To develop an accurate method for two-phase flow pattern image reconstruction and recognition.
  • To enhance the precision of flow pattern identification using advanced algorithms.

Main Methods:

  • Utilized electrical resistance tomography (ERT) for two-phase flow pattern image reconstruction.
  • Applied and compared back propagation (BP), wavelet, and radial basis function (RBF) neural networks for image identification.
  • Developed a deep learning fusion algorithm combining RBF networks and convolutional neural networks (CNNs).

Main Results:

  • RBF neural networks demonstrated higher fidelity (>80%) and faster convergence than BP and wavelet networks.
  • The fusion recognition algorithm achieved a high accuracy of over 97% for flow pattern identification.
  • Experimental verification confirmed the correctness of the developed theoretical simulation model.

Conclusions:

  • The developed ERT-based method with RBF and CNN fusion significantly improves two-phase flow pattern recognition accuracy.
  • This research provides crucial theoretical guidance for accurate two-phase flow pattern acquisition.
  • The findings are vital for optimizing processes involving complex fluid flows.