Rotating three-dimensional velocimetry

Gururaj, Abbishek; Moaven, Mahyar; Tan, Zu Puayen; Thurow, Brian S.; Raghav, Vrishank

doi:10.1007/s00348-021-03241-4

Cited by 4 publications

(1 citation statement)

References 43 publications

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“…With this attractive feature, the LF-PIV has great potential to be an alternative to the multi-camera-based volumetric velocimetry techniques in spaceconstrained applications. Further development of the high-speed LF camera and the spectral LF camera may allow access to the temporal information of the unsteady flows and the scalar field measurement [63][64][65].…”

Section: Resultsmentioning

confidence: 99%

Approach to select optimal cross-correlation parameters for light field particle image velocimetry

Zhu

Hossain

et al. 2022

Physics of Fluids

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The light field particle image velocimetry (LF-PIV) has shown a great potential for three-dimensional (3D) flow measurement in space-constrained applications. Usually, the parameters of the cross-correlation calculation in the LF-PIV are chosen based on empirical analysis or introduced from conventional planar PIV, which lowers the accuracy of 3D velocity field measurement. This study presents an approach to selecting optimal parameters of the cross-correlation calculation and thereby offers systematic guidelines for experiments. The selection criterion of the interrogation volume size is studied based on the analysis of the valid detection probability of the correlation peak. The optimal seeding concentration and the size of tracer particles are then explored through synthetic Gaussian vortex field reconstruction. The optimized parameters are employed in a cylinder wake flow measurement in a confined channel. A comparative study is conducted between the LF-PIV and a planar PIV system. Results indicate that the LF-PIV along with the optimized parameters can measure the 3D flow velocity of the cylinder wakes accurately. It has been observed that the mean and max errors of velocity decrease by 32.6% and 18.8%, respectively compared to the related LF-PIV techniques without consideration of optimal parameters. Therefore, it is suggested that the optimized cross-correlation parameters in the LF-PIV can improve the accuracy of 3D flow measurement.

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Section: Resultsmentioning

confidence: 99%

Approach to select optimal cross-correlation parameters for light field particle image velocimetry

Zhu

Hossain

et al. 2022

Physics of Fluids

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Improving depth uncertainty in plenoptic camera-based velocimetry

Moaven,

Gururaj,

Raghav

et al. 2024

Exp Fluids

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This work describes the development of a particle tracking velocimetry (PTV) algorithm designed to improve three-dimensional (3D), three-component velocity field measurements using a single plenoptic camera. Particular focus is on mitigating the longstanding depth uncertainty issues that have traditionally plagued plenoptic particle image velocimetry (PIV) experiments by leveraging the camera’s ability to generate multiple perspective views of a scene in order to assist both particle triangulation and tracking. 3D positions are first estimated via light field ray bundling (LFRB) whereby particle rays are projected into the measurement volume using image-to-object space mapping. Tracking is subsequently performed independently within each perspective view, providing a statistical amalgamation of each particle’s predicted motion through time in order to help guide 3D trajectory estimation while simultaneously protecting the tracking algorithm from physically unreasonable fluctuations in particle depth positions. A synthetic performance assessment revealed a reduction in the average depth errors obtained by LFRB as compared to the conventional multiplicative algebraic reconstruction technique when estimating particle locations. Further analysis using a synthetic vortex ring at a magnification of − 0.6 demonstrated plenoptic-PIV capable of maintaining the equivalent of 0.1–0.15 voxel accuracy in the depth domain at a spacing to displacement ratio of 5.3–10.5, an improvement of 84–89% compared to plenoptic-PIV. Experiments were conducted at a spacing to displacement ratio of approximately 5.8 to capture the 3D flow field around a rotor within the rotating reference frame. The resulting plenoptic-PIV/PTV vector fields were evaluated with reference to a fixed frame stereoscopic-PIV (stereo-PIV) validation experiment. A systematic depth-wise (radial) component of velocity directed toward the wingtip, consistent with observations from prior literature and stereo-PIV experiments, was captured by plenoptic-PTV at magnitudes similar to the validation data. In contrast, the plenoptic-PIV did not discern any coherent indication of radial motion. Our algorithm constitutes a significant advancement in enhancing the functionality and versatility of single-plenoptic camera flow diagnostics by directly addressing the primary limitation associated with plenoptic imaging. Graphical abstract

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Development of raw-image ray-bundling for focused and unfocused plenoptic 3D-PTV

Chen,

Tan

2024

Opt. Express

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This paper introduces a new plenoptic 3D particle tracking velocimetry (3D-PTV) technique called raw-image ray-bundling (RIRB), which combines the 3D clustering algorithm of light-field ray-bundling (LFRB) with the raw image segmentation concept of epipolar triangular connectivity (ETC). The combined approach provides flexibility towards accommodating both unfocused and focused plenoptic cameras. Additionally, the RIRB algorithm bypasses the computational step of perspective-view generation in LFRB, thereby allowing lower specification microlens arrays (MLA) to be used without excessive loss of measurement resolution. As part of RIRB’s development, synthetic particle-field data and experimental dot-panel targets were used to demonstrate the viability of RIRB. The latter was performed through a VEO640 high-speed camera retrofitted for plenoptic imaging with a 2.5 mm focal-length, F/10 MLA. For the synthetic dataset, RIRB demonstrated better performance than LFRB in processing low-resolution images, with mean errors below 0.85% of the field-of-view (FOV). Additionally, a synthetic Hagen-Poiseuille flow dataset was used to demonstrate the feasibility of RIRB for 3D flow velocimetry using both high and low-resolution images. For the experimental dataset, x/y errors below 0.15% of the FOV and z error below 1.0% were achieved. The combination of synthetic and experimental validations suggests RIRB is a promising approach for 3D triangulation from both focused and unfocused raw plenoptic images, overcoming the low-resolution issue inherent with perspective-view decoding in plenoptic systems.

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Rotating three-dimensional velocimetry

Cited by 4 publications

References 43 publications

Approach to select optimal cross-correlation parameters for light field particle image velocimetry

Approach to select optimal cross-correlation parameters for light field particle image velocimetry

Improving depth uncertainty in plenoptic camera-based velocimetry

Development of raw-image ray-bundling for focused and unfocused plenoptic 3D-PTV

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