Physics-based stitching of multi-FOV PIV measurements for urban wind fields

Abstract

Particle image velocimetry (PIV) is commonly used to measure multiple field-of-views (FOVs) of the flow in large urban domains, performed in wind tunnels using an array of cameras located at fixed positions or a single camera setup that traverses during the measurements. With respect to the large amount of data produced in this type of measurement, traditional stitching approaches are no longer adequate to efficiently merge the image data. A physics-based flow field stitching method is proposed for stitching flows in urban wind fields, named regional-flow stitching. It matches the flow characteristics within neighboring FOVs of flow using a vorticity-based reference window. The method is based on finding the optimal similarity between a reference window in one FOV and another possible matching window in the other FOV. The matching window rolls in both directions at the interval of two adjacent data points, which determines the stitching resolution. The matching in flow similarity is evaluated using the normalized root-mean-squared error (NRMSE) between reference and possible matching windows, which is evaluated by comparison to a traditional stitching method and further verified using planar and stereo wind tunnel PIV measurement results. A comparison of computational cost with 8 FOVs and approximate 7% surface overlap between FOVs shows that our method is faster, taking about 46% of processing time, than a traditional stitching method. 3D visualization of the merged FOVs is further demonstrated with ParaView. The proposed stitching method may serve as a powerful tool for experimental studies involving large domains of urban wind flow fields.