Toloui, Mostafa2017-11-272017-11-272016-03https://hdl.handle.net/11299/191425University of Minnesota Ph.D. dissertation. 2016. Major: Mechanical Engineering. Advisor: Jiarong Hong. 1 computer file (PDF); 106 pages.Three-dimensional non-invasive measurement capability is often a necessity to unravel the physical phenomenon in fluid mechanic problems such as flow field characterization in wall-bounded turbulent flows and microfluidic devices. Among all the 3D optical flow diagnostic techniques, digital inline holographic particle tracking velocimetry (DIH-PTV) provides the highest spatial resolution with low cost, simple and compact optical setups. Despite these advantages, DIH-PIV suffers from major limitations including poor longitudinal resolution, human intervention (i.e. requirement for manually determined tuning parameters during tracer field reconstruction and extraction), limited tracer concentration, small sampling volume and expensive computations. These limitations have prevented this technique from being widely implemented for high resolution 3D flow measurements. In this study, we present our novel high-fidelity DIH-PTV algorithm with the goal of overcoming all the above mentioned limitations. Specifically, the proposed particle extraction method consists of multiple steps including 3D reconstruction, 3D deconvolution, automatic signal-to-noise ratio enhancement and thresholding, particle segmentation and centroid cacluation, and inverse iterative particle extraction. In addition, the processing package is enriched with a multi-pass 3D tracking method and a cross-correlation based longitudinal displacement refinement scheme. The entire method is implemented using GPU-based algorithm to increase the computational speed significantly. Validated with synthetic particle holograms, the proposed method can achieve particle extraction rate above 95% with ghost particles less than 3% and maximum position error below a particle diameter for holograms with particle concentration above 3000 particles/mm3 within sampling volumes of ~1 mm longitudinal length. Such improvements will substantially enhance the implementation of DIH-PTV for 3D flow measurements and enable the potential commercialization of this technique. The applicability of the technique is validated using the experiment of laminar flow in a microchannel and the synthetic tracer flow fields generated using a DNS turbulent channel flow database. In addition, the proposed method is applied to smooth- and rough-wall turbulent channel flows under two different settings of high-resolution near-wall and whole-channel measurements (i.e. sampling volume is extended to the entire depth of the channel). In the first case, using a microscopic objective and local seeding mechanism, DIH-PTV resolves near-wall flow structures within a sampling volume of 1 × 1.5 × 1 mm3 (streamwise × wall-normal × spanwise) with velocity resolution of ~100 μm (vector spacing). In the second case, the measurement volume is extended to the whole-channel depth by seeding the entire channel. Under this setting, the 3D velocity fields are obtained within a sampling volume of 14.7 × 50.0 × 14.4 mm3 with a velocity resolution of ~ <1.3 mm per vector, comparable to other the-state-of-the-art 3D whole-field flow measurement techniques. Overall, the presented DIH-PTV measurements under two different settings highlight the potential of DIH-PTV to obtain 3D characterization of the turbulent structures over a full range of scales, covering both the near wall and the out-layer regions of wall-bounded turbulent flows.en3D Optical Flow MeasurementHolographyMicrofluidicsPIVTurbulent Channel FlowThesis or Dissertation