在一个环形图像数据集中的垂直双相流程 - 德克萨斯A&M大学
Kaushik Manikonda1,2,3, Chinemerem Obi1, Aarya Abhay Brahmane1
1Texas A&M University, College Station, TX 77840, United States.
Data in brief
|February 3, 2025
概括
该数据集使用高分辨率图像捕获垂直气液两相流程. 它有助于机器视觉和计算流体动力学流体动力学研究.
科学领域:
- 流体动力学 流体动力学
- 机器视觉 机器视觉 机器视觉
- 计算建模 计算建模
背景情况:
- 气液双相流在各种工业过程中至关重要.
- 了解流动模式对于流程优化和安全至关重要.
- 现有的数据集可能缺乏对垂直环状流的全面视觉数据.
研究的目的:
- 呈现垂直双相流程的高分辨率图像数据集.
- 支持机器视觉模型的开发,以识别流动模式.
- 为了增强计算流体动力学 (CFD) 模拟和参数估计.
主要方法:
- 在垂直设置中进行气液流 (空气和水) 的实验生成.
- 流动动态和调节过渡的高质量视频录制.
- 在德克萨斯A&M大学140英尺高的塔楼实验室内收集数据.
主要成果:
- 一个全面的图像集合,记录了各种两相流动模式.
- 在受控条件下的流量调节过渡的详细视觉记录.
- 该数据集不包括环状流量模式,仅限于垂直方向.
结论:
- 该数据集为推进流体动力学和机器视觉研究提供了宝贵的资源.
- 它有助于创建更准确的流量模式检测模型.
- 进一步的研究可能会扩大数据集,包括其他流动方向和模式.
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