To improve the performance of particle image velocimetry in measuring instantaneous velocity fields, direct cross-correlation of image fields can be used in place of auto-correlation methods of interrogation of double- or multiple-exposure recordings. With improved speed of photographic recording and increased resolution of video array detectors, cross-correlation methods of interrogation of successive single-exposure frames can be used to measure the separation of pairs of particle images between successive frames. By knowing the extent of image shifting used in a multiple-exposure and by a priori knowledge of the mean flow-field, the cross-correlation of different sized interrogation spots with known separation can be optimized in terms of spatial resolution, detection rate, accuracy and reliability.

Theory of cross-correlation analysis of PIV images : Image analysis as measuring technique in flows

/pdf/volumetric-velocimetry-for-fluid-flows-1aecqbeg0a.pdf

Volumetric velocimetry for fluid flows

Bicycle aerodynamics: History, state-of-the-art and future perspectives

Flow past a single stationary sphere, 1. Experimental and numerical techniques

This paper solves an approximate form of conservation of mass and momentum for a turbine in a wind farm array. The solution is a fairly simple explicit relationship that predicts the streamwise velocity distribution within a wind farm with an arbitrary layout. As this model is obtained by solving flow governing equations directly for a turbine that is subject to upwind turbine wakes, no ad hoc superposition technique is needed to predict wind farm flows. A suite of large-eddy simulations (LES) of wind farm arrays is used to examine self-similarity as well as validity of the so-called conservation of momentum deficit for turbine wakes in wind farms. The simulations are performed with and without the presence of some specific turbines in the wind farm. This allows us to systematically study some of the assumptions made to develop the analytical model. A modified version of the conservation of momentum deficit is also proposed to provide slightly better results at short downwind distances, as well as in the far wake of turbines deep inside a wind farm. Model predictions are validated against the LES data for turbines in both full-wake and partial-wake conditions. While our results highlight the limitation in capturing the flow speed-up between adjacent turbine columns, the model is overall able to acceptably predict flow distributions for a moderately sized wind farm. Finally, the paper employs the new model to provide insights on the accuracy of common wake superposition methods.

/pdf/analytical-solution-for-the-cumulative-wake-of-wind-turbines-ojyp4a9sfm.pdf

Analytical solution for the cumulative wake of wind turbines in wind farms

A method is introduced to measure the aerodynamic drag of moving objects such as ground vehicles or athletes in speed sports. Experiments are conducted as proof-of-concept that yield the aerodynamic drag of a sphere towed through a square duct in stagnant air. The drag force is evaluated using large-scale tomographic PIV and invoking the time-average momentum equation within a control volume in a frame of reference moving with the object. The sphere with 0.1 m diameter moves at a velocity of 1.45 m/s, corresponding to a Reynolds number of 10,000. The measurements in the wake of the sphere are conducted at a rate of 500 Hz within a thin volume of approximately 3 × 40 × 40 cubic centimeters. Neutrally buoyant helium-filled soap bubbles are used as flow tracers. The terms composing the drag are related to the flow momentum, the pressure and the velocity fluctuations and they are separately evaluated. The momentum and pressure terms dominate the momentum budget in the near wake up to 1.3 diameters downstream of the model. The pressure term decays rapidly and vanishes within 5 diameters. The term due to velocity fluctuations contributes up to 10% to the drag. The measurements yield a relatively constant value of the drag coefficient starting from 2 diameters downstream of the sphere. At 7 diameters the measurement interval terminates due to the finite length of the duct. Error sources that need to be accounted for are the sphere support wake and blockage effects. The above findings can provide practical criteria for the drag evaluation of generic bluff objects with this measurement technique.

/pdf/aerodynamic-drag-of-a-transiting-sphere-by-large-scale-4f6tc78eud.pdf

Aerodynamic drag of a transiting sphere by large-scale tomographic-PIV

The aerodynamic drag of a human-scale wind tunnel model is obtained from large-scale particle tracking velocimetry measurements invoking the conservation of momentum in a control volume surrounding the model. Lagrangian particle tracking is employed to obtain the velocity and static pressure statistics in a thin volume in the wake of a cyclist mannequin at freestream velocities between 12.5 and 15 m/s, corresponding to Reynolds numbers from 5 $$\times$$
 105 to 6 $$\times$$
 105 based on the torso length. The spatial distributions of the time-average streamwise velocity and pressure coefficient match well with previous works reported in literature. The streamwise velocity fluctuations in the wake of the cyclist’s model are presented, clearly demonstrating the unsteady nature of the main wake flow structures. Furthermore, the obtained aerodynamic drag follows the expected quadratic increase with increasing freestream velocity. The accuracy of this drag estimation is evaluated by comparison to force balance data and corresponds to 30 drag counts. The three terms composing the overall drag force, ascribed to the mean and fluctuating streamwise velocity and the mean pressure, are also evaluated separately, demonstrating that the resistive force is dominated by the contribution of the mean streamwise momentum deficit, whereas the contribution of the pressure term is negligible.

/pdf/aerodynamic-drag-determination-of-a-full-scale-cyclist-1qqqp2cp71.pdf

Aerodynamic drag determination of a full-scale cyclist mannequin from large-scale PTV measurements

The Ring of Fire (RoF) measurement concept, introduced by Terra et al. (Exp Fluids 58:83. https://doi.org/10.1007/s00348-017-2331-0, 2017; Experiments in Fluids 59:120, 2018), is applied to real cyclists to enable the aerodynamic drag determination during sport action. This principle is based on large-scale stereoscopic particle image velocimetry (PIV) measurements over a plane crossed by the athlete during cycling. The momentum before and after the passage of the athlete poses the basis for the control volume analysis in the athlete’s frame of reference, which returns the aerodynamic drag. This approach extrapolates aerodynamic studies towards more realistic conditions, compared to experiments performed in wind tunnels with scaled or stationary athletes. The measurement concept is termed Ring of Fire as the rider crosses a region of intense light. Two experiments are conducted, indoor and outdoor, with attention placed on the effects of the environmental conditions and the confinement of the measurement region. Stereo-PIV measurements feature a plane of approximately 2 × 2 m 2 , using neutrally buoyant sub-millimeter helium-filled soap bubbles (HFSB) as flow tracers. The drag measurement is obtained examining the wake produced by the athlete. It is observed that the drag value becomes independent of time after about 5 torso lengths from the passage. A statistical estimate of the drag is produced combining the results of several passages. Fluctuations of the drag value during a single passage are associated with the unsteady wake flow. Overall fluctuations among different transits are ascribed to the varying conditions of the airflow prior to the passage of the athlete. The experiments conducted outdoor exhibit significantly larger dispersion of the drag value, compared to the quieter conditions indoor. Repetition of the transit 10–30 times yields a basis for statistical convergence of the average drag value. The flow topology past the cyclist compares satisfactorily between both experiments and with wind tunnel experiments reported in literature. The current measurements clearly separate drag values from upright and time–trial athlete’s positions, indicating the suitability of this principle for aerodynamic analysis and optimization studies. Graphical abstract: [Figure not available: see fulltext.].

/pdf/on-site-cycling-drag-analysis-with-the-ring-of-fire-3zni619ijr.pdf

On-site cycling drag analysis with the Ring of Fire

Large-scale Particle Tracking Velocimetry (PTV) measurements are cond ucted in the wake of a fu ll-scale cyclist model in time-trial position at freestream velocities between 12.5 and 15 m/ s, corresponding to Reynolds numbers of the order of 5×105. Lagrangian particle tracking is employed to determine the velocity and static pressure statistics in the wake plane, showing good agreement with previous results reported in literature. The aerodynamic drag is estimated from the large-scale PTV measurements invoking the conservation of momentum in a control volume enclosing the model (PIV wake rake approach). The estimated drag follows the expected quadratic increase with increasing freestream velocity. The accuracy of the drag estimate is evaluated by comparison to state-of-the-art force balance measurements, resulting in a resolution of the PIV wake rake approach of 30 drag counts. The three terms composing the overall drag force, associated with the time-average streamwise velocity, its fluctuations and the time-averaged pressure, respectively, are evaluated separately, demonstrating that the contribution of the pressure term is negligible and the resistive force is dominated by the time-average streamwise momentum deficit.

/pdf/aerodynamic-drag-determination-of-a-full-scale-cyclist-46ale3lgzu.pdf

Aerodynamic drag determination of a full-scale cyclist mannequin from largescale PTV measurements

https://repository.tudelft.nl/islandora/object/uuid%3A6310c44c-b63a-4cb5-b2f0-b377b34f723e/datastream/OBJ/download

W. Terra

Papers

Aerodynamic drag of a transiting sphere by large-scale tomographic-PIV

Aerodynamic drag determination of a full-scale cyclist mannequin from large-scale PTV measurements

On-site cycling drag analysis with the Ring of Fire

Aerodynamic drag determination of a full-scale cyclist mannequin from largescale PTV measurements

Cyclist Reynolds number effects and drag crisis distribution