Improved Particle Image Velocimetry Methods in Large-Scale Production Wind Tunnels
Abstract
Implementing particle image velocimetry (PIV) data collection in wind tunnel testing increases understanding of the model flow field by providing velocity field data, as compared to single-point velocity data produced by traditional measurement approaches. However, using PIV poses challenges for operational tempo, mechanical setup, component alignment, and limited field of view (FOV) dimensions. These issues have prevented PIV from becoming an industry-standard in large-scale production facilities. To overcome some of these challenges, this work designs and implements procedures and support infrastructure to increase the capabilities of 2-D PIV data collection at the Oran W. Nicks Low-Speed Wind Tunnel (LSWT) at Texas A&M University. Specifically, this work aims to overcome the current field of view size restrictions in a generalizable way while emphasizing operational efficiency. Stitching asynchronously measured fields of view captured by a single translating camera was the selected approach to increasing the PIV region of interest. The advantage of this approach is that it does not limit the measurement area’s size or shape based on the setup’s components. The usefulness of the approach is demonstrated through application to two experiments at the LSWT, which achieved a measurement area 3.3 times larger than previously possible. It is anticipated that the procedures outlined in this work, including the developed stitching methodology and calibration technique, will serve as a model for improving the capabilities of PIV in other large-scale production-type facilities.
Citation
Mainka, Grace Elizabeth (2023). Improved Particle Image Velocimetry Methods in Large-Scale Production Wind Tunnels. Master's thesis, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /198914.