Upgrade of a time-resolved particle image velocimetry system

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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).**