Volumetric Flow Field Measurement: An Implementation of Shake-The-Box

Abstract

This thesis deals with volumetric flow field measurements using particle imaging with multiple cameras. Focus of interest is the 3D Lagrangian-Particle-Tracking (LPT) technique Shake-The-Box (STB) and 3D Particle-Tracking-Velocimetry (3D-PTV). A completely new framework PySTB for 3D particle tracking is developed and implemented. During the development nearly all associated algorithms were extensively revised, rewritten and adapted for higher flexibility, improved robustness and faster processing. PySTB is written in C++ and Python and shows the best of both worlds; C++ provides high performance and Python makes the development of new algorithms and techniques really simple and fast. The new algorithm Two-Pulse STB allows to use 3D-PTV techniques for the evaluation of two-pulse measurements what was reserved to Tomo-PIV in the past. Thereby, Two-Pulse STB shows significant improvements over the results that were achieved with previous reconstruction methods (tested at the synthetic Case C of the 4th international PIV challenge and an experimental data set). Further, the Online Volume-SelfCalibration is presented, which enables to simultaneously calibrate the camera system and reconstruct the particle positions and intensities, promising the possibility to use STB on measurements under tough circumstances, like strong vibrations. Also, some new techniques for flow-field estimation from noisy point clouds are presented (in addition, or as an alternative to the Particle-Space Correlation).