Image intensifier unit for PIV system

PIV 系统图像增强器单元

• 批准号: 345143-2007
• 负责人: Tachie, MarkFrancis
• 金额: $ 5.21万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Research Tools and Instruments - Category 1 (<$150,000)
• 财政年份: 2006
• 资助国家: 加拿大
• 起止时间: 2006-01-01 至 2007-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=326286
• 关键词: Image; intensifier; unit; PIV; system

The vast majority of flows of environmental and engineering importance are turbulent. Many fluid engineering systems have rough surfaces, and the flow may be subjected to streamwise pressure gradients. Because of the complex nature of these flows, their structural characteristics are not well understood. The objective of this proposal is to obtain funds to acquire an image intensifier unit. The equipment will be used together with an existing high resolution particle image velocimetry (PIV) system to conduct cutting-edge research on a variety of complex near-wall turbulent flows. The research will conduct investigation of pressure gradient turbulent flows over rough surfaces, turbulent wall jets and shallow turbulent wakes over rough surfaces. The PIV data will be used to identify coherent or eddy structures within these flows, and to elucidate how these structures affects the transport of flow and mixing characteristics. The data will also enable the applicant to obtain accurate measurement of the mean velocities, Reynolds stresses, triple correlations and the budget terms in the transport equation for turbulent kinetic energy and Reynolds stresses. The proposed research will advance state of knowledge of complex turbulent flows of engineering importance. The physical understanding and high quality data sets will be valuable to the turbulence community in developing and validating more accurate turbulence models, to design more efficient effluent discharge systems, and to improve efficiency of fluid engineering systems. The research will also provide an opportunity to train high quality personnel. These will lead to dramatic and sustained improvements to society in terms of cost savings to manufacturers and safer environment through reduced vehicle emissions and enhanced dilution and mixing of wastewater in water bodies.

绝大多数具有环境和工程重要性的流动都是动荡的。许多流体工程系统具有粗糙的表面，并且流动可能会受到流向压力梯度的影响。由于这些流的复杂性，它们的结构特征尚不清楚。该提案的目的是获得资金来购买图像增强器单元。该设备将与现有的高分辨率粒子图像测速（PIV）系统一起使用，对各种复杂的近壁湍流进行前沿研究。该研究将对粗糙表面上的压力梯度湍流、湍流壁射流和粗糙表面上的浅湍流尾流进行研究。 PIV 数据将用于识别这些流中的相干或涡流结构，并阐明这些结构如何影响流的传输和混合特性。这些数据还将使申请人能够准确测量平均速度、雷诺应力、三重相关性以及湍流动能和雷诺应力输运方程中的预算项。拟议的研究将提高对具有工程重要性的复杂湍流的认识。物理理解和高质量的数据集对于湍流界开发和验证更准确的湍流模型、设计更高效的废水排放系统以及提高流体工程系统的效率非常有价值。该研究还将为培养高素质人才提供机会。通过减少车辆排放和加强水体中废水的稀释和混合，这些将在节省制造商成本和更安全的环境方面给社会带来显着和持续的改善。