Vertical two-phase flow regimes in an annulus image dataset - Texas A&M university

Kaushik Manikonda*, Chinemerem Obi, Aarya Abhay Brahmane, Mohammad Azizur Rahman, Abu Rashid Hasan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The Vertical Two-Phase Flow Regimes in an annulus Image Dataset, generated at Texas A&M University, presents an extensive collection of high-resolution images capturing various gas-liquid two-phase flow dynamics within a vertical flow setup. This dataset results from meticulous experimental work in the 140 ft Tower Lab, utilizing a combination of water and air flows to simulate real-world conditions and employing high-quality video recordings to document flow regime transitions. Designed to support research in fluid dynamics, machine vision, and computational modeling, the dataset offers valuable resources for developing machine vision models for accurate regime detection and differentiation, enhancing the fidelity of computational fluid dynamics simulations, and facilitating the estimation of critical flow parameters. Despite its comprehensive nature, the dataset notes limitations such as the absence of annular flow regime images and its exclusive focus on vertical flow conditions.

Original languageEnglish
Article number111245
JournalData in Brief
Volume58
DOIs
Publication statusPublished - Feb 2025

Keywords

  • Computer vision
  • Gas-liquid Two-phase flow
  • Machine learning
  • Machine vision
  • Multi-phase flow

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