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Göttingen, Germany

Schafer L.,RWTH Aachen | Dierksheide U.,LaVision GmbH | Klaas M.,RWTH Aachen | Schroder W.,RWTH Aachen
Physics of Fluids | Year: 2011

A new method to describe statistical information from passive scalar fields has been proposed by Wang and Peters ["The length-scale distribution function of the distance between extremal points in passive scalar turbulence," J. Fluid Mech.554, 457 (2006)]. They used direct numerical simulations (DNS) of homogeneous shear flow to introduce the innovative concept. This novel method determines the local minimum and maximum points of the fluctuating scalar field via gradient trajectories, starting from every grid point in the direction of the steepest ascending and descending scalar gradients. Relying on gradient trajectories, a dissipation element is defined as the region of all the grid points, the trajectories of which share the same pair of maximum and minimum points. The procedure has also been successfully applied to various DNS fields of homogeneous shear turbulence using the three velocity components and the kinetic energy as scalar fields [L. Wang and N. Peters, "Length-scale distribution functions and conditional means for various fields in turbulence," J. Fluid Mech.608, 113 (2008)]. In this spirit, dissipation elements are, for the first time, determined from experimental data of a fully developed turbulent channel flow. The dissipation elements are deduced from the gradients of the instantaneous fluctuation of the three velocity components u', v', and w' and the instantaneous kinetic energy k', respectively. The measurements are conducted at a Reynolds number of 1.7×104 based on the channel half-height δ and the bulk velocity U. The required three-dimensional velocity data are obtained investigating a 17.75×17.75×6 mm3(0.355δ×0.355δ×0.12δ) test volume using tomographic particle-image velocimetry. Detection and analysis of dissipation elements from the experimental velocity data are discussed in detail. The statistical results are compared to the DNS data from Wang and Peters ["The length-scale distribution function of the distance between extremal points in passive scalar turbulence," J. Fluid Mech.554, 457 (2006); "Length-scale distribution functions and conditional means for various fields in turbulence," J. Fluid Mech.608, 113 (2008)]. Similar characteristics have been found especially for the pdf's of the large dissipation element length regarding the exponential decay. In agreement with the DNS results, over 99% of the experimental dissipation elements possess a length that is smaller than three times the average element length. © 2011 American Institute of Physics. Source


Sciacchitano A.,Technical University of Delft | Scarano F.,Technical University of Delft | Wieneke B.,LaVision GmbH
Experiments in Fluids | Year: 2012

A novel technique is introduced to increase the precision and robustness of time-resolved particle image velocimetry (TR-PIV) measurements. The innovative element of the technique is the linear combination of the correlation signal computed at different separation time intervals. The domain of the correlation signal resulting from different temporal separations is matched via homo-thetic transformation prior to the averaging of the correlation maps. The resulting ensemble-Averaged correlation function features a significantly higher signal-to-noise ratio and a more precise velocity estimation due to the evaluation of a larger particle image displacement. The method relies on a local optimization of the observation time between snapshots taking into account the local out-of-plane motion, continuum deformation due to in-plane velocity gradient and acceleration errors. The performance of the pyramid correlation algorithm is assessed on a synthetically generated image sequence reproducing a three-dimensional Batchelor vortex; experiments conducted in air and water flows are used to assess the performance on time-resolved PIV image sequences. The numerical assessment demonstrates the effectiveness of the pyramid correlation technique in reducing both random and bias errors by a factor 3 and one order of magnitude, respectively. The experimental assessment yields a significant increase of signal strength indicating enhanced measurement robustness. Moreover, the amplitude of noisy fluctuations is considerably attenuated and higher precision is obtained for the evaluation of time-resolved velocity and acceleration. © 2012 Springer-Verlag. Source


Bomphrey R.J.,University of Oxford | Henningsson P.,University of Oxford | Michaelis D.,LaVision GmbH | Hollis D.,LaVision UK Ltd
Journal of the Royal Society Interface | Year: 2012

Aerodynamic structures generated by animals in flight are unstable and complex. Recent progress in quantitative flow visualization has advanced our understanding of animal aerodynamics, but measurements have hitherto been limited to flow velocities at a plane through the wake. We applied an emergent, high-speed, volumetric fluid imaging technique (tomographic particle image velocimetry) to examine segments of the wake of desert locusts, capturing fully three-dimensional instantaneous flow fields. We used those flow fields to characterize the aerodynamic footprint in unprecedented detail and revealed previously unseen wake elements that would have gone undetected by two-dimensional or stereoimaging technology. Vortex iso-surface topographies show the spatio-temporal signature of aerodynamic force generation manifest in the wake of locusts, and expose the extent to which animal wakes can deform, potentially leading to unreliable calculations of lift and thrust when using conventional diagnostic methods.We discuss implications for experimental design and analysis as volumetric flow imaging becomes more widespread. © 2012 The Royal Society. Source


Wieneke B.,LaVision GmbH
Measurement Science and Technology | Year: 2015

The uncertainty of a PIV displacement field is estimated using a generic post-processing method based on statistical analysis of the correlation process using differences in the intensity pattern in the two images. First the second image is dewarped back onto the first one using the computed displacement field which provides two almost perfectly matching images. Differences are analyzed regarding the effect of shifting the peak of the correlation function. A relationship is derived between the standard deviation of intensity differences in each interrogation window and the expected asymmetry of the correlation peak, which is then converted to the uncertainty of a displacement vector. This procedure is tested with synthetic data for various types of noise and experimental conditions (pixel noise, out-of-plane motion, seeding density, particle image size, etc) and is shown to provide an accurate estimate of the true error. © 2015 IOP Publishing Ltd. Source


Sciacchitano A.,Technical University of Delft | Wieneke B.,LaVision GmbH | Scarano F.,Technical University of Delft
Measurement Science and Technology | Year: 2013

A novel method is presented to quantify the uncertainty of PIV data. The approach is a posteriori, i.e. the unknown actual error of the measured velocity field is estimated using the velocity field itself as input along with the original images. The principle of the method relies on the concept of super-resolution: the image pair is matched according to the cross-correlation analysis and the residual distance between matched particle image pairs (particle disparity vector) due to incomplete match between the two exposures is measured. The ensemble of disparity vectors within the interrogation window is analyzed statistically. The dispersion of the disparity vector returns the estimate of the random error, whereas the mean value of the disparity indicates the occurrence of a systematic error. The validity of the working principle is first demonstrated via Monte Carlo simulations. Two different interrogation algorithms are considered, namely the cross-correlation with discrete window offset and the multi-pass with window deformation. In the simulated recordings, the effects of particle image displacement, its gradient, out-of-plane motion, seeding density and particle image diameter are considered. In all cases good agreement is retrieved, indicating that the error estimator is able to follow the trend of the actual error with satisfactory precision. Experiments where time-resolved PIV data are available are used to prove the concept under realistic measurement conditions. In this case the 'exact' velocity field is unknown; however a high accuracy estimate is obtained with an advanced interrogation algorithm that exploits the redundant information of highly temporally oversampled data (pyramid correlation, Sciacchitano et al (2012 Exp. Fluids 53 1087-105)). The image-matching estimator returns the instantaneous distribution of the estimated velocity measurement error. The spatial distribution compares very well with that of the actual error with maxima in the highly sheared regions and in the 3D turbulent regions. The high level of correlation between the estimated error and the actual error indicates that this new approach can be utilized to directly infer the measurement uncertainty from PIV data. A procedure is shown where the results of the error estimation are employed to minimize the measurement uncertainty by selecting the optimal interrogation window size. © 2013 IOP Publishing Ltd. Source

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