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Upgrade of a time-resolved particle image velocimetry system

Upgrade of a time-resolved particle image velocimetry system
时间分辨粒子图像测速系统的升级
批准号:
RTI-2019-00333
负责人:
Maciel, Yvan
金额:
$9.35万
依托单位:
依托单位国家:
加拿大
项目类别:
Research Tools and Instruments
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

项目摘要

项目成果

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中文摘要
翻译
拉瓦尔大学液压机实验室对产生水力发电的水轮机进行研究。它是加拿大唯一的独立实验室,专门从事水轮机的研发。它的研究目的是为了更好地理解水力涡轮机的水动力和结构行为。实验室的合作伙伴是参与水力涡轮机设计的领先公司,Andritz Hydro, GE可再生能源,福伊特水电,以及水力涡轮机运营商Hydro- quacimbec和EDF。我们目前的研究项目旨在了解由混流式涡轮机的流动引起的潜在破坏性涡轮振动的性质。弗朗西斯涡轮机是加拿大水力发电厂中数量最多的涡轮机。该项目将为参与的工业合作伙伴的研发部门提供知识、工具和方法,以优化涡轮机的设计或操作,以提高灵活性,而不会影响机器的寿命。这反过来又会简化可再生能源(风能、太阳能)在电网中的整合。***本项目(以及我们实验室中的许多其他项目)的主要测量系统是时间分辨粒子图像测速(TR-PIV)系统。PIV系统测量流动内部的速度场,以提供有关流动行为的信息。我们的PIV系统的时间分辨特性意味着它可以高速获取速度场,高达每秒725个速度场。用这种方法,可以分析流动现象的快速变化。例如,我们可以跟踪引起涡轮振动的大涡在时间上的演变。***本提案的目标是大幅升级我们的TR-PIV系统。这种系统与高速摄像机一起工作。我们的相机性能很高,但有两个限制。首先,它们有相对较小的内存库来存储流图像。有限的内存大小意味着,对于大多数关键的流现象,采集时间太短,无法跟踪重要的流变化。因此,我们将无法完全描述流动现象并完全理解它们在结构上激励涡轮机的作用。其次,将图像从相机传输到计算机需要很长时间,这大大减少了一天内可以进行的测量次数。因此,它降低了测试台对其他类型测量的可用性,它导致巨大的能源浪费,因为钻机在图像传输期间无法停止,并且它增加了设备(钻机,涡轮模型,传感器)的不必要磨损
英文摘要
The Laboratory of Hydraulic Machines of Laval University performs research on hydraulic turbines that produce hydroelectricity. It is the only independent laboratory in Canada specializing in R&D on hydraulic turbines. Its research aims at providing a better understanding of the hydrodynamic and structural behaviour of hydraulic turbines. The Laboratory partners are leading companies involved in hydraulic turbine design, Andritz Hydro, GE Renewable Energy, Voith Hydro, and turbine operators, Hydro-Québec and EDF. Our current research project aims at understanding the nature of potentially damaging turbine vibrations induced by the flow in Francis turbines. Francis turbines are the most numerous turbines in hydro power plants in Canada. The project will provide the R&D departments of the participating industrial partners with knowledge, tools and methodologies to optimize turbine designs or operation in order to increase flexibility without penalizing the machine life. This will in turn ease the integration of renewable energy sources (wind, solar) on the power grid.***The prime measurement system for this project (and many others in our laboratories) is a Time-Resolved Particle Image Velocimetry (TR-PIV) system. A PIV system measures velocity fields inside a flow in order to provide information about the flow behaviour. The time-resolved feature of our PIV system implies that it can acquire velocity fields at high speed, up to 725 velocity fields per second. In this manner, it is possible to analyze fast variations of flow phenomena. For example, we can follow the evolution in time of large vortices that induce turbine vibrations.***The goal of the present proposal is to upgrade substantially our TR-PIV system. Such a system functions with high-speed cameras. Our cameras are highly performant, but they have two limitations. First, they have relatively small memory banks to store the flow images. The limited memory size implies that for a majority of crucial flow phenomena, the acquisition time is too short to track important flow variations. Consequently, we will not be able to fully characterize the flow phenomena and to entirely understand their role in structurally exciting the turbine. Second, the transfer of the images from the cameras to a computer takes a long time, which considerably reduces the number of measurements that can be performed in a day. Consequently, it diminishes the test bench availability for other types of measurements, it leads to an enormous waste of energy since the rig cannot be stopped during image transfers and it increases needlessly the wear of the equipment (rig, turbine model, sensors).**
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Decelerated turbulent boundary layers
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    RGPIN-2019-04194
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2022
  • 负责人:
    Maciel, Yvan
  • 依托单位:
Decelerated turbulent boundary layers
  • 批准号:
    RGPIN-2019-04194
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2021
  • 负责人:
    Maciel, Yvan
  • 依托单位:
Decelerated turbulent boundary layers
  • 批准号:
    RGPIN-2019-04194
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2020
  • 负责人:
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  • 依托单位:
Decelerated turbulent boundary layers
  • 批准号:
    RGPIN-2019-04194
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2019
  • 负责人:
    Maciel, Yvan
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