Computationally efficient storage of 3D particle intensity and position data for use in 3D PIV and 3D PTV

Abstract

Three-dimensional (3D) volumetric velocity measurement techniques, such as tomographic or holographic particle image velocimetry (PIV), rely upon the computationally intensive formation, storage and localized interrogation of multiple 3D particle intensity fields. Calculation of a single velocity field typically requires the extraction of particle intensities into tens of thousands of 3D sub-volumes or discrete particle clusters, the processing of which can significantly affect the performance of 3D cross-correlation based PIV and 3D particle tracking velocimetry (PTV). In this paper, a series of popular and customized volumetric data formats are presented and investigated using synthetic particle volumes and experimental data arising from tomographic PIV measurements of a turbulent boundary layer. Results show that the use of a sub-grid ordered non-zero intensity format with a sub-grid size of 16 × 16 × 16 points provides the best performance for cross-correlation based PIV analysis, while a particle clustered non-zero intensity format provides the best format for PTV applications. In practical tomographic PIV measurements the sub-grid ordered non-zero intensity format offered a 29% improvement in reconstruction times, while providing a 93% reduction in volume data requirements and a 28% overall improvement in cross-correlation based velocity analysis and validation times.