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

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2025-02-01 Epub Date: 2025-01-04 DOI:10.1016/j.dib.2024.111245
Kaushik Manikonda , Chinemerem Obi , Aarya Abhay Brahmane , Mohammad Azizur Rahman , Abu Rashid Hasan
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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.

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垂直两相流在环空图像数据集中的分布-德克萨斯A&M大学。
德克萨斯A&M大学生成的环空图像数据集中的垂直两相流状态,提供了广泛的高分辨率图像集合,捕获了垂直流动设置中的各种气液两相流动动力学。该数据集是在140英尺高的塔实验室进行的细致实验工作的结果,利用水和空气流动的组合来模拟现实世界的条件,并采用高质量的视频记录流动状态的转变。该数据集旨在支持流体动力学、机器视觉和计算建模方面的研究,为开发用于精确状态检测和区分的机器视觉模型提供了宝贵的资源,增强了计算流体动力学模拟的保真度,并促进了关键流量参数的估计。尽管该数据集具有综合性,但也存在一些局限性,例如缺乏环空流态图像,并且只关注垂直流动条件。
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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