Vertical Two-Phase Flow Regimes in an Annulus Image Dataset - Texas A&M University

Published: 27 August 2024| Version 2 | DOI: 10.17632/nxncbzzz38.2
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Description

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.

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Institutions

Georgia Institute of Technology College of Computing, Dell Technologies Inc, Texas A&M University at Qatar, Texas A&M University Department of Petroleum Engineering

Categories

Fluid Flow, Computer Vision, Fluid Dynamics, Object Detection, Machine Learning, Multiphase Flow, Image Classification, Drilling Engineering, Machine Vision, Production Engineering, Computer Vision Algorithms

Funding

National Academies of Sciences, Engineering, and Medicine

Qatar National Research Fund

NPRP10-0101-170091

National Academies of Sciences, Engineering, and Medicine

Licence