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Flow evolution over helicopter rotors, wind turbine blades, and insect wings are unsteady, three-dimensional (3D), and influenced by phenomena unique to the rotating frame of reference (FoR), e.g., Coriolis and centrifugal forces. Conventional 3D-PIV techniques are unable to fully characterize these rotating FoR physics, since the measurements are limited to a fixed FoR of a relatively small volume through which the rotor blade or wing traverses intermittently. In this paper, a new “Rotating Three-Dimensional Velocimetry (R3DV)” technique is proposed to address these gaps. R3DV consists of 3D measurements made with a single stationary plenoptic camera in combination with a hub-mounted mirror that aligns the camera’s field of view with a rotating wing. In post-processing R3DV data, a rotational volumetric calibration method is developed to account for image acquisition through a rotating mirror. Rotating FoR volumes are then reconstructed using the Multiplicative Algebraic Reconstruction Technique (MART) algorithm with the adapted calibration scheme and subsequently cross-correlated to derive a 3D velocity field. R3DV was experimentally demonstrated in a study of 3D unsteady flow over an impulsively rotated flat-plate wing. Prominent flow features like the formation and shedding of the primary and secondary leading-edge vortices (LEVs) were observed, which corroborate well with the existing literature on rotating wings. The time-resolved variation of LEV velocity profiles and circulation with azimuthal angle exhibited expected trends. The ability to quantify 3D and time-resolved velocity fields in the rotating FoR demonstrates the feasibility of adopting R3DV as a technique to investigate rotating flows.

Vortex topology is analyzed from measurements of flow over a flat, rectangular plate with an aspect ratio of 2 which was articulated in pitch and roll, individually and simultaneously. The plate was immersed into a $$\text {Re} = 10,000$$ flow (based on chord length). Measurements were made using a 3D–3C plenoptic PIV system to allow for the study of complete vortex topology of the entire wing. The prominent focus is the early development of the leading-edge vortex (LEV) and resulting topology. The effect of the wing kinematics on the topology was explored through a parameter space involving multiple values of pitch rate and roll rate at pitch and roll angles up to $${50}^{\circ }$$ . Characterization and comparisons across the expansive data set are made possible through the use of a newly defined dimensionless parameter, $${\textit{k}_{\text {Rg}}}$$ . Termed the effective reduced pitch rate, $${\textit{k}_{\text {Rg}}}$$ , is a measure of the pitch rate that takes into account the relative rolling motion of the wing in addition to the pitching motion and freestream velocity. This study has found that for a purely pitching wing, increasing the reduced pitch rate $${\textit{k}}$$ delays the vortex evolution with respect to $$\alpha _\mathrm {eff}$$ . For a purely rolling wing, as the advance coefficient $${\textit{J}}$$ is increased, the vortex evolution is advanced with respect to nondimensionalized time and the bifurcation point of the LEV shifts inboard. For a pitching and rolling wing, the addition of roll stabilizes and delays the evolution of the LEV in both nondimensionalized time and effective angle of attack.

A recently developed 3-D flow visualization system is used to capture instantaneous 3-D images in the near-field of an axisymmetric jet at Reynolds number 6,700 and 10,200. The 3-D images, which are acquired through the scanning of a pulsed MHz-rate laser sheet, have spatial resolution of up to 312 × 260 × 100 voxels and time resolution of 100 μs, producing effectively instantaneous, high-resolution 3-D images of the jet. These images represent the first truly volumetric flow visualization images to be captured in the near-field of a jet over this range of Reynolds numbers. The images show the formation of large-scale axisymmetric vortex rings along with the formation of counter-rotating streamwise vortex pairs that surround the periphery of the jet in a periodic manner and co-exist with the ring vortices. The azimuthal frequency of the streamwise vortices increases with Reynolds number from 10 to 14 structures around the circumference at Re = 6,700 to 18–22 structures at Re = 10,200. In some instances, the streamwise vortices are observed to maintain their phase and span across several vortex rings in the streamwise direction. In other instances, however, the streamwise vortices display abrupt changes in the downstream direction. The images also display a complex interaction between the vortex rings and streamwise structures in the transition region near the end of the potential core illustrating the importance of the streamwise vortices on the evolution of the jet flow.

Simultaneous particle image velocimetry (PIV) and flow visualization measurements were performed in a turbulent boundary layer in an effort to better quantify the relationship between the velocity field and the image intensity typically observed in a classical flow visualization experiment. The freestream flow was lightly seeded with smoke particles to facilitate PIV measurements, whereas the boundary layer was densely seeded with smoke through an upstream slit in the wall to facilitate both PIV and classical flow visualization measurements at Reynolds numbers, Re θ , ranging from 2,100 to 8,600. Measurements were taken with and without the slit covered as well as with and without smoke injection. The addition of a narrow slit in the wall produces a minor modification of the nominal turbulent boundary layer profile whose effect is reduced with downstream distance. The presence of dense smoke in the boundary layer had a minimal effect on the observed velocity field and the associated proper orthogonal decomposition (POD) modes. Analysis of instantaneous images shows that the edge of the turbulent boundary layer identified from flow visualization images generally matches the edge of the boundary layer determined from velocity and vorticity. The correlation between velocity deficit and smoke intensity was determined to be positive and relatively large (>0.7) indicating a moderate-to-strong relationship between the two. This notion was extended further through the use of a direct correlation approach and a complementary POD/linear stochastic estimation (LSE) approach to estimate the velocity field directly from flow visualization images. This exercise showed that, in many cases, velocity fields estimated from smoke intensity were similar to the actual velocity fields. The complementary POD/LSE approach proved better for these estimations, but not enough to suggest using this technique to approximate velocity measurements from a smoke intensity image. Instead, the correlations further validate the use of flow visualization techniques for determining the edge and large-scale shape of a turbulent boundary layer, specifically when quantitative velocity measurements, such as PIV, are not possible in a given experiment.