Novel Techniques for Improving the Accuracy of 3D3C Optical Velocimetry

3D3C (three-dimensional and three-component) optical velocimetry has long been desired to resolve the 3D spatial structures of turbulent flows. Recent advancements have demonstrated tomographic particle image velocimetry (tomo-PIV) as a powerful technique to enable such velocimetry. The current tomo-PIV technique obtains 3D3C velocimetry by combining PIV measurements with 3D tomographic reconstruction, i.e., cross-correlating the 3D particles distributions reconstructed by tomography at two consecutive times. However, the current tomo-PIV technique, due to the significant complexity of tomography (e.g., the view registration VR process and the reconstruction algorithm), suffers from the relatively low accuracy of velocity measurements. This further deteriorates the subsequent determinations of velocity derivatives which are usually of ultimate interests. To study and address such accuracy issue, this dissertation first reports an experimental quantification of the tomo-PIV accuracy, and then reports the developments and demonstrations of two novel techniques to enhance the tomo-PIV accuracy.
First, the accuracy of the existing tomo-PIV technique was quantified experimentally. Precisely controlled experiments were designed using tracer particles embedded in a solid sample, and tomo-PIV measurements were performed on the sample while it was moved both translationally and rotationally to simulate various known displacement fields. So that the 3D3C displacements measured by tomo-PIV can be directly compared to the known displacements created by the sample to quantify the accuracy. With these controlled experiments, the accuracies in both velocity magnitude and direction were quantified and analyzed in this dissertation.
Then, after recognizing the current tomo-PIV accuracy, two techniques were proposed in this dissertation to significantly enhance the accuracy of tomo-PIV measurements. These two techniques were code-named the RTPIV (regularized tomo-PIV) method and the RIVR (reconstruction integrating view registration) method. Conceptually, the RTPIV method improved the accuracy of 3D3C velocity measurements by incorporating the conservation of mass (COM) equation as a priori information into the cross-correlation. The RIVR method enhanced the accuracies of tomography and the resulting velocity by integrating the tomography and VR. The accuracy enhancement could be achieved, because the integration of tomography and VR established a feedback mechanism between them and enabled each step to leverage the information provided by the other. Both the RTPIV and RIVR methods were validated experimentally and numerically, and were demonstrated to indeed enhance the accuracy of tomo-PIV measurements significantly. The measurements with enhanced accuracy by these two techniques are expected to improve the understanding of flow and combustion physics and the design of propulsion systems.