Advancements in volumetric PIV measurements

Abstract

Particle Image Velocimetry (PIV) constitutes the state-of-the-art for quantitative flow diagnostics. Its volumetric variant is nowadays also well established, able to provide a full description of the three-dimensional flow field. Despite the maturity of the technique, the use of volumetric PIV in industrial facilities is seldom considered, due to the challenges associated with the high Reynolds numbers, the presence of complex wind tunnel models in the domain of interest or the long distances with respect to the PIV instrumentation. In an attempt to aid the dissemination of volumetric PIV in industrial large-scale facilities and promote its use for engineering design and validation of flow simulations, four elements of the PIV working principle are critically reviewed in this dissertation, namely: the scalability of tracer particles for experiments in air flows; image preprocessing to deal with complex light reflections; the recording strategy and particle tracking algorithm; and data reduction techniques that exploit the modal decomposition of the velocity field.

The scalability of experiments using PIV relies upon several parameters: primarily the tracers scattering cross section and their concentration, the power and distribution of illumination; and the imagers sensor size and their amount. Given their larger cross section, helium-filled soap bubbles (HFSB) allow measurements in air flows over a significantly larger domain compared to traditional oil or water droplets. Controlling their diameter translates into scalability of the experiment. In chapter 3, a technique is presented to extend the control of HFSB diameter by geometrical variations of the generator. A theoretical model predicts the bubble size and production rate, which is verified experimentally by high-speed shadow visualization. The overall range of HFSB produced in a stable regime can be varied from approximately 150 μm, targeting experiments in research facilities at high spatial resolution, to a few millimetres, sufficient for large-scale measurements in industrial facilities as well as full-scale on-site experiments. Imaging by light scattering of such tracers is also investigated, in view of controversies in the literature on whether diffraction or geometrical imaging dominate the imaging regime. For large-scale volumetric applications, it is shown that varying the bubble diameter allows increasing both the measurement domain as well as the working distance of the imagers at 10 m and beyond.

Measuring the velocity field around a complex object by volumetric PIV is hindered by shadow formation (illumination), camera occlusion (imaging) and light reflections from the object surface. The former have been recently dealt with by multiplying illumination and imaging directions (redundancy) and by the integration of ray-tracing techniques to include the effect of visual blockage caused by the object. Instead, the problem of light reflections blinding regions of the images has not been afforded yet. The latter pertains to interactions between illumination and imaging through the object surface and it poses additional challenges to ghost particle formation, particle detection and tracking in general, increasing the computational cost and reducing the accuracy of the measured velocity field. In chapter 4, a method is proposed to effectively detect such regions, and measures to modify the particle triangulation algorithm are devised. The viability of this novel approach is examined by application to two experiments of increasing complexity. The first case is the flow around a stationary wall-mounted cube as imaged with a redundant number of cameras. The second experiment tackles an elite runner sprinting across the measurement region obtained with the Ring-of-Fire technique. A considerable reduction of ghost particles (false positives) is attained, while the formation of voids (false negatives) is also minimized. The overall result of the method maximizes the measurement region around and in proximity of the object of interest.

Multiple-exposure (ME) recording is a variant of PIV whereby more than two samples of the particle position are obtained to overcome some limitations of single-exposure dual-frame recordings, such as accelerometry, pressure from instantaneous PIV data, or to further extend the dynamic velocity range. Compared to time-resolved systems, ME lowers system requirements in terms of laser power and camera frame rate, thus making it more suitable for applications involving a redundant number of cameras and higher flow velocities. In chapter 5, the reliability and accuracy of volumetric particle tracking in ME recordings comprising up to 5 exposures with one or two frames is first scrutinized on a synthetic particle field motion based on a Taylor-Green vortex lattice, yielding viable results. The measurement accuracy in terms of dynamic velocity and acceleration ranges is reported, as a function of particle image density, number of pulses and timing sequence. Besides, ME recordings are simulated from a time-resolved experiment around a wall-mounted cube, which yield equivalence between ME and time-resolved conditions. A demonstration of volumetric ME for accelerometry and pressure from PIV is also included, with experiments in the turbulent wake of a circular cylinder.

Modal decomposition of PIV measurements is a common approach to reduce data complexity and aid interpretability. In chapter 6, a method to reconstruct the dense velocity field from relatively sparse particle tracks, as obtained for instance from volumetric ME recordings, is introduced. The goal is to provide a representation of the 3D flow field on a Cartesian grid, for inspection of derived flow quantities, at high spatial resolution. The approach leverages the properties of proper orthogonal decomposition (POD) and it iteratively reconstructs the detailed spatial modes from a first, coarse estimation thereof. The initially coarse Cartesian representation of the velocity field is obtained by local data averaging, where POD is applied. The spatial resolution of the POD modes is enhanced by reprojecting them onto the sparse particles velocity to iteratively improve the reconstruction of the temporal coefficients. Finally, the enhanced velocity field is represented at high-resolution with a reduced order model using the dominant POD modes. Experiments in the wake of a cylinder at Re_D = 27,000 are used to assess the suitability of the method to resolve the turbulent Kármán-Benard wake. The approach is benchmarked against traditional as well as state-of-the-art reconstruction methods, illustrating the capability of enhancing the spatial resolution of sparse velocity data.