Particle Image Velocimetry Interrogation Research Articles

Error quantification of 3D homogeneous and isotropic turbulence measurements using 2D PIV

Particle image velocimetry (PIV) has become a popular non-intrusive tool for measuring various types of flows. However, when measuring three dimensional flows with 2D PIV, there is inherent measurement error due to out-of-plane motion. Errors in the measured velocity field propagate to turbulence statistics. Since this can distort the overall flow characteristics, it is important to understand the effect of this out-of-plane error. In this study, the effect of out-of-plane motion on turbulence statistics is quantified. Using forced isotropic turbulence direct numerical simulation (DNS) flow field data provided by the Johns Hopkins turbulence database (JHTDB), synthetic image tests are performed. Turbulence statistics such as turbulence kinetic energy, dissipation rate, Taylor microscale, Kolmogorov scale, and velocity correlations are calculated. Various test cases were simulated while controlling three main parameters which affect the out-of-plane motion: PIV interrogation window size, camera inter-frame time, and laser sheet thickness. The amount of out-of-plane motion was first quantified, and then the error variation according to these parameters was examined. This information can be useful when examining fully three dimensional flows such as homogeneous and isotropic turbulence via 2D PIV.

Particle image velocimetry (PIV) uncertainty quantification using moment of correlation (MC) plane

We present a new uncertainty estimation method for particle image velocimetry (PIV), that uses the correlation plane as a model for the probability density function (PDF) of displacements and calculates the second order moment of the correlation (MC). The cross-correlation between particle image patterns is the summation of all particle matches convolved with the apparent particle image diameter. MC uses this property to estimate the PIV uncertainty from the shape of the cross-correlation plane. In this new approach, the generalized cross-correlation (GCC) plane corresponding to a PIV measurement is obtained by removing the particle image diameter contribution. The GCC primary peak represents a discretization of the displacement PDF, from which the standard uncertainty is obtained by convolving the GCC plane with a Gaussian function. Then a Gaussian least-squares-fit is applied to the peak region, accounting for the stretching and rotation of the peak, due to the local velocity gradients and the effect of the convolved Gaussian. The MC method was tested with simulated image sets and the predicted uncertainties show good sensitivity to the error sources and agreement with the expected RMS error. Subsequently, the method was demonstrated in three PIV challenge cases and two experimental datasets and was compared with the published image matching (IM) and correlation statistics (CS) techniques. Results show that the MC method has a better response to spatial variation in RMS error and the predicted uncertainty is in good agreement with the expected standard uncertainty. The uncertainty prediction was also explored as a function of PIV interrogation window size. Overall, the MC method performance establishes itself as a valid uncertainty estimation tool for planar PIV.

On the applicability of numerical image mapping for PIV image analysis near curved interfaces

This paper scrutinises the general suitability of image mapping for particle image velocimetry (PIV) applications. Image mapping can improve PIV measurement accuracy by eliminating overlap between the PIV interrogation windows and an interface, as illustrated by some examples in the literature. Image mapping transforms the PIV images using a curvilinear interface-fitted mesh prior to performing the PIV cross correlation. However, degrading effects due to particle image deformation and the Jacobian transformation inherent in the mapping along curvilinear grid lines have never been deeply investigated. Here, the implementation of image mapping from mesh generation to image resampling is presented in detail, and related error sources are analysed. Systematic comparison with standard PIV approaches shows that image mapping is effective only in a very limited set of flow conditions and geometries, and depends strongly on a priori knowledge of the boundary shape and streamlines. In particular, with strongly curved geometries or streamlines that are not parallel to the interface, the image-mapping approach is easily outperformed by more traditional image analysis methodologies invoking suitable spatial relocation of the obtained displacement vector.

POD-based background removal for particle image velocimetry

State-of-art preprocessing methods for Particle Image Velocimetry (PIV) are severely challenged by time-dependent light reflections and strongly non-uniform background. In this work, a novel image preprocessing method is proposed. The method is based on the Proper Orthogonal Decomposition (POD) of the image recording sequence and exploits the different spatial and temporal coherence of background and particles. After describing the theoretical framework, the method is tested on synthetic and experimental images, and compared with well-known pre-processing techniques in terms of image quality enhancement, improvements in the PIV interrogation and computational cost. The results show that, unlike existing techniques, the proposed method is robust in the presence of significant background noise intensity, gradients, and temporal oscillations. Moreover, the computational cost is one to two orders of magnitude lower than conventional image normalization methods. A downloadable version of the preprocessing toolbox has been made available at http://seis.bris.ac.uk/~aexrt/PIVPODPreprocessing/.

Collaborative framework for PIV uncertainty quantification: the experimental database

The uncertainty quantification of particle image velocimetry (PIV) measurements has recently become a topic of great interest as shown by the recent appearance of several different methods within the past few years. These approaches have different working principles, merits and limitations, which have been speculated upon in subsequent studies. This paper reports a unique experiment that has been performed specifically to test the efficacy of PIV uncertainty methods. The case of a rectangular jet, as previously studied by Timmins et al () and Wilson and Smith (), is used. The novel aspect of the experiment is simultaneous velocity measurements using two different time-resolved PIV systems and a hot-wire anemometry (HWA) system. The first PIV system, called the PIV measurement system (‘PIV-MS’), is intended for nominal measurements of which the uncertainty is to be evaluated. It is based on a single camera and features a dynamic velocity range (DVR) representative of typical PIV experiments. The second PIV system, called the ‘PIV-HDR’ (high dynamic range) system, features a significantly higher DVR obtained with a higher digital imaging resolution. The hot-wire is placed in close proximity to the PIV measurement domain. The three measurement systems were carefully set to simultaneously measure the flow velocity at the same time and location. The comparison between the PIV-HDR system and the HWA provides an estimate of the measurement precision of the reference velocity for evaluation of the instantaneous error in the measurement system. The discrepancy between the PIV-MS and the reference data provides the measurement error, which is later used to assess the different uncertainty quantification methods proposed in the literature. A detailed comparison of the uncertainty estimation methods based on the present datasets is presented in a second paper from Sciacchitano et al (). Furthermore, this database offers the potential to be used for comparison of the measurement accuracy of existing or newly developed PIV interrogation algorithms. The database is publicly available on the website www.piv.de/uncertainty.

Porous Medium Flow and an Overlying Parallel Flow: PIV Interrogation Area and Overlaps, Interfacial Location, and Depth Ratio Effects

This paper presents an experimental work aimed at studying the effects of particle image velocimetry (PIV) interrogation area and overlaps, location of the interface, as well as depth ratios on the flow at the interface between a model porous medium and an overlying free flow. The porous media were modeled using square arrays of circular rods of diameter and porosity 0.88, filling fraction ranging from 0.47 to 0.75, and depth-to-porous medium pore ratio ranging from 5.75 to 13.69. Using a pressure-driven refractive-index matched viscous fluid, the bulk Reynolds number was kept approximately constant at a regime in which inertia was not a factor. PIV measurements were made across various streamwise-transverse planes of the test section. For the present tests, it was observed that PIV interrogation area (IA) and overlap effects on the interfacial velocities are negligible when the IA sizes in dimensionless units ranged from 0.017 to 0.145 in flow parameters and 0.036 to 0.300 in porous media parameters. Other dimensionless slip parameters are however significantly affected. Interfacial slip parameters of porous media models were found to change by as much as 120 % with change in the interfacial location. The interfacial location sensitivity was also found to be dependent on the direction of deviation, the type of porous medium, and depth ratios. Volume averaged results showed that for flows over models of porous media, the depth-to-porous medium pore ratio effects are more prominent compared with the filling fraction effects, for both two- and three-dimensional porous media.

Evaluation of Turbulent Kinetic Energy Dissipation Rate in a Free Jet Flow from PIV Measurements

The present paper reports PIV (Particle Image Velocimetry) measurements of turbulent velocity fluctuations statistics in development region of an axisymmetric free jet (Re = 28 000). To minimize measurement uncertainty, adaptive calibration, image processing and data post-processing algorithms were utilized. On the basis of theoretical analysis and direct measurements, the paper discusses effect of PIV spatial resolution on measured statistical characteristics of turbulent fluctuations. Underestimation of the second-order moments of velocity derivatives and of the turbulent kinetic energy dissipation rate due to a finite size of PIV interrogation area and finite thickness of laser sheet was analyzed from model spectra of turbulent velocity fluctuations. The results are in a good agreement with the measured experimental data. The paper also describes performance of possible ways to account for unresolved small-scale velocity fluctuations in PIV measurements of the dissipation rate. In particular, a turbulent viscosity model can be efficiently used to account for the unresolved pulsations in a free turbulent flow

High-Resolution Scalar and Velocity Measurements in an Internal Combustion Engine

High-resolution planar laser-induced fluorescence and particle image velocimetry (PIV) measurements were acquired during the intake stroke in a motored engine to investigate the mixing behavior of in-cylinder flows. The data were analyzed to determine the scalar energy and kinetic energy spectra, which were used to find the corresponding dissipation spectra. The results were compared with a model turbulent spectrum. The scalar energy and scalar dissipation spectra were shown to be resolved through the full dissipation range, enabling the determination of the Batchelor/Kolmogorov length scale and agreed well with the model turbulent spectrum at all but the highest wavenumbers where the effects of random noise were present. The 2% point in the scalar dissipation spectra was used to estimate the Batchelor scale, which was found to be approximately 32 μm. The PIV data, which had a 675 μm interrogation region, were used to calculate a one-dimensional kinetic energy spectrum. The kinetic energy spectrum agreed well with the scalar energy spectrum and the model spectrum up to wavenumbers corresponding to approximately two times the PIV interrogation region size. For the present measurements, this meant that the PIV data were not able to resolve the peak in the dissipation spectrum, i.e., the full high-wavenumber part of the inertial subrange.

Dissipation rate estimation from PIV in zero-mean isotropic turbulence

Measuring the turbulent kinetic energy dissipation rate in an enclosed turbulence chamber that produces zero-mean flow is an experimental challenge. Traditional single-point dissipation rate measurement techniques are not applicable to flows with zero-mean velocity. Particle image velocimetry (PIV) affords calculation of the spatial derivative as well as the use of multi-point statistics to determine the dissipation rate. However, there is no consensus in the literature as to the best method to obtain dissipation rates from PIV measurements in such flows. We apply PIV in an enclosed zero-mean turbulent flow chamber and investigate five methods for dissipation rate estimation. We examine the influence of the PIV interrogation cell size on the performance of different dissipation rate estimation methods and evaluate correction factors that account for errors related to measurement uncertainty, finite spatial resolution, and low Reynolds number effects. We find the Re λ corrected, second-order, longitudinal velocity structure function method to be the most robust method to estimate the dissipation rate in our zero-mean, gaseous flow system.

Influence of PIV interrogation area on turbulent statistics up to 4th order moments in smooth and rough wall turbulent flows

The paper presents measurements performed over a smooth surface, a transitionally rough surface generated by wire mesh and a fully rough surface that comprised transverse square ribs in a channel. The flow was seeded using fluorescent particles and the high quality vectors obtained using particle image velocimetry (PIV) technique were used to compute the mean velocity, turbulent statistics up to the fourth order moments as well as the production and dissipation terms in the transport equation for the turbulent kinetic energy. By using different interrogation areas and overlaps to process the PIV images, the interrogation area sizes in wall units varied from 2.9 to 52.4. In the first part of the paper, these interrogation areas were used to study the spatial resolution effects on the mean and higher order moments over the smooth and rough surfaces. For the second part of the paper, classical scaling and the scaling proposed by George and Castillo [W.K. George, L. Castillo, Zero-pressure-gradient turbulent boundary layer, Appl. Mech. Rev. 50 (12) (1997) 689–729] and Zagarola and Smits [M.V. Zagarola, A.J. Smits, Mean-flow scaling of turbulent pipe flow, J. Fluid Mech. 373 (1998) 33–79] were used to document the salient effects of surface roughness on the flow characteristics. The results show spatial resolution effects on some of the turbulent statistics, and it is evident that these effects are more pronounced over the rough surfaces than on the smooth surface. The smaller interrogation area sizes used in this study are adequate to reasonably evaluate all the statistics and production term but not the dissipation rate. It was observed that the power law proposed by George and Castillo [W.K. George, L. Castillo, Zero-pressure-gradient turbulent boundary layer, Appl. Mech. Rev. 50 (12) (1997) 689–729] is better than the log law for modeling low Reynolds number turbulent flows over rough surfaces. The results also support the premise that the mechanisms for turbulence production and transport close to the ribs are markedly different from those for a smooth surface.

A comparative study of five different PIV interrogation algorithms

Five different particle image velocimetry (PIV) interrogation algorithms are tested with numerically generated particle images and two real data sets measured in turbulent flows with relatively small particle images of size 1.0–2.5 pixels. The size distribution of the particle images is analyzed for both the synthetic and the real data in order to evaluate the tendency for peak-locking occurrence. First, the accuracy of the algorithms in terms of mean bias and rms error is compared to simulated data. Then, the algorithms’ ability to handle the peak-locking effect in an accelerating flow through a 2:1 contraction is compared, and their ability to estimate the rms and Reynolds shear stress profiles in a near-wall region of a turbulent boundary layer (TBL) at Re τ =510 is analyzed. The results of the latter case are compared to direct numerical simulation (DNS) data of a TBL. The algorithms are: standard fast Fourier transform cross-correlation (FFT-CC), direct normalized cross-correlation (DNCC), iterative FFT-CC with discrete window shift (DWS), iterative FFT-CC with continuous window shift (CWS), and iterative FFT-CC CWS with image deformation (CWD). Gaussian three-point peak fitting for sub-pixel estimation is used in all the algorithms. According to the tests with the non-deformation algorithms, DNCC seems to give the best rms estimation by the wall, and the CWS methods give slightly smaller peak-locking observations than the other methods. With the CWS methods, a bias error compensation method for the bilinear image interpolation, based on the particle image size analysis, is developed and tested, giving the same performance as the image interpolation based on the cardinal function. With the CWD algorithms, the effect of the spatial filter size between the iteration loops is analyzed, and it is found to have a strong effect on the results. In the near-wall region, the turbulence intensity varies by up to 4%, depending on the chosen interrogation algorithm. In addition, the algorithms’ computational performance is tested.

Traversing field of view and AR-PIV for mid-field wake vortex investigation in a towing tank

Wake vortex flow experiments are performed in a water tank where a 1:48 scaled model of a large transport aircraft A340–300 is towed at the speed of 3 and 5 ms–1 with values of the angle of attack α={2°, 4°, 8°}. Particle image velocimetry (PIV) measurements are performed in a plane perpendicular to the towing direction describing the streamwise component of the wake vorticity. The instantaneous field of view (I-FOV) is traversed vertically with an underwater moving-camera device tracking the vortex core during the downward motion. An adaptive resolution (AR) image-processing technique is introduced that enhances the PIV interrogation in terms of spatial resolution and accuracy. The main objectives of the investigation are to demonstrate the applicability of PIV diagnostics in wake vortex research with towing-tank facilities. The specific implementation of the traversing field-of-view (T-FOV) technique and the AR image processing are driven by the need to characterize the vortex wake global properties as well as the vortex decay phenomenon in the mid- and far-field. Relevant aerodynamic information is obtained in the mid-field where the time evolution of the vortex structure (core radius and tangential velocity) and of the overall vortex wake (vortex trajectory, descent velocity, circulation) are discussed.