Lagrangian Particle Image Velocimetry
Abstract
The existing methods for reconstructing the 3D Eulerian velocity fields generally require two subsequent optimization procedures. For example, voxel-based method, such as Tomographic PIV (Tomo-PIV), first reconstructs the 3D voxel intensity followed by motion analysis on the voxel field. Another group of methods interpolates the Lagrangian data field obtained by Lagrangian particle tracking (LPT) schemes (e.g. Shake- The-Box (STB)) to Eulerian fixed grids. In this paper, we propose a novel method for volumetric velocity reconstruction exploring the locality of 3D object space. Under this formulation, the velocity of local patch is sought to match the projection of the particles within the local patch in image space to the image recorded by camera. The core algorithm to solve the matching problem is an instance-based estimation scheme that can overcome the difficulties of optimization originated from the nonlinear relationship between the image intensity residual and the volumetric velocity. The proposed method, labeled as Lagrangian Particle Image Velocimetry (LaPIV), is quantitatively evaluated with synthetic particle image data. The promising results indicate the potential application of LaPIV to a large variety of volumetric velocity reconstruction problems.
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