On improvement of PIV image interrogation near stationary interfaces

In this paper the problem posed by interfaces when present in PIV measurements is addressed. Different image pre-processing, processing and post-processing methodologies with the intention to minimize the interface effects are discussed and assessed using Monte Carlo simulations. Image treatment prior to the correlation process is shown to be incapable of fully removing the effects of the intensity pedestal across the object edge. The inherent assumption of periodicity in the signal causes the FFT-based correlation technique to perform the worst when the correlation window contains a signal truncation. Instead, an extended version of the masking technique introduced by Ronneberger et al. (Proceedings of the 9th international symposium on applications of laser techniques to fluid mechanics, Lisbon, 1998) is able to minimize the interface-correlation, resolving only the particle displacement peak. Once the displacement vector is obtained, the geometric center of the interrogation area is not the correct placement. Instead, the centre of mass position allows an unbiased representation of the wall flow (Usera et al. in Proceedings of the 12th international symposium on applications of laser techniques to fluid mechanics, Lisbon, 2004). The aforementioned concepts have been implemented in an adaptive interrogation methodology (Theunissen et al. in Meas Sci Technol 18:275–287, 2007) where additionally non-isotropic resolution and re-orientation of the correlation windows is applied near the interface, maximizing the wall-normal spatial resolution. The increase in resolution and robustness are demonstrated by application to a set of experimental images of a flat-plate, subsonic, turbulent boundary layer and a hypersonic flow over a double compression ramp.     

Improvements to PIV image analysis by recognizing the velocity gradients

Two iterative PIV image processing methods are introduced, which utilize displacement and deformation of the interrogation areas to maximize the correlation. The velocity gradients used for the window deformation are iteratively estimated directly from the images and no velocity values are required from neighbouring interrogation areas, as with numerical differentiation. The improved accuracy and resolution of the velocity gradient estimation compared to numerical differentiation is shown using synthetic images. The performance in a real application is shown using experimental reference images.     

Spatially adaptive PIV interrogation based on data ensemble

This paper proposes a specific application of the approach recently proposed by the authors to achieve an autonomous and robust adaptive interrogation method for PIV data sets with the focus on the determination of mean velocity fields. Under circumstances such as suboptimal flow seeding distribution and large variations in the velocity field properties, neither multigrid techniques nor adaptive interrogation with criteria based on instantaneous conditions offer enough robustness for the flow field analysis. A method based on the data ensemble to select the adaptive interrogation parameters, namely, the window size, aspect ratio, orientation, and overlap factor is followed in this study. Interrogation windows are sized, shaped and spatially distributed on the basis of the average seeding density and the gradient of the velocity vector field. Compared to the instantaneous approach, the ensemble-based criterion adapts the windows in a more robust way especially for the implementation of non-isotropic windows (stretching and orientation), which yields a higher spatial resolution. If the procedure is applied recursively, the number of correlation samples can be optimized to satisfy a prescribed level of window overlap ratio. The relevance and applicability of the method are illustrated by an application to a shock-wave-boundary layer interaction problem. Furthermore, the application to a transonic airfoil wake verifies by means of a dual-resolution experiment that the spatial resolution in the wake can be increased by using non-isotropic interrogation windows.     

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=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.     

On the accuracy of velocity and vorticity measurements with PIV

A number of numerical techniques aimed at improving the accuracy of measurements using the correlation approach in Particle Image Velocimetry, PIV, are proposed and investigated. In this approach the velocity (displacement) is found as the location of a peak in the correlation map. Based on an experimental model the best performing peak finding approaches are selected among different strategies. Second, an algorithm is proposed which minimizes errors on the estimates of vorticity using velocity distributions obtained by means of PIV. The proposed methods are experimentally validated against a flow with known properties. Work supported by NASA Ames Research Center     

A combination correlation-based interrogation and tracking algorithm for digital PIV evaluation

A combination of the correlation-based interrogation algorithm and the correlation-based tracking algorithm is proposed for digital PIV evaluation. A zero-padding interrogation algorithm is adopted in which the interrogation windows differ in size and in which the number of pixels in the side length of the smaller window is not restricted to a power of 2. This greatly improves the algorithm's accuracy and measurement range. The correlation-based tracking algorithm is employed when the already-measured vector can serve as a good predictor of the next vector to be measured. In this case, only a very small searching scope is required and computation can be fast. Computational intensity analysis shows that, using the same-sized sampled window, the correlation-based tracking algorithm is more efficient than the conventional correlation-based interrogation algorithm if the searching scope is less than 4. Compared with some of the other correlation-based algorithms, the proposed combination method is faster, is more accurate, has a larger measurable range, and can utilize a sampled window of any size.     

Biases of PIV measurement of turbulent flow and the masked correlation-based interrogation algorithm

Influences of evaluation bias of the correlation-based interrogation algorithm on particle image velocimetry (PIV) measurement of turbulent flow are investigated. Experimental tests in the Iowa Institute of Hydraulic Research towing tank with a towed PIV system and a surface-piercing flat plate and simulations demonstrate that the experimentally determined mean velocity and Reynolds stress components are affected by the evaluation bias and the gradient of the evaluation bias, respectively. The evaluation bias and gradient of the evaluation bias can both be minimized effectively by using Gaussian digital masks on the interrogation window, so that the measurement uncertainty can be reduced. Received: 16 September 1999/Accepted: 7 February 2000     

A digital mask technique for reducing the bias error of the correlation-based PIV interrogation algorithm

 In this paper the bias phenomenon in the evaluation of PIV recordings by using the correlation-based interrogation algorithm is discussed, and a digital mask technique, that can effectively reduce the bias error, is introduced. The correlation-based interrogation algorithm, when masked with a Gaussian window function, can achieve a higher evaluation accuracy not only for PIV recordings of flows with small velocity gradients, but also for that of flows with large gradients. Received: 14 October 1998/Accepted: 20 July 1999     

Analysis of velocity interpolation schemes for image deformation methods in PIV

The spatial resolution of PIV can be increased significantly by using an image deformation method (IDM) and very small grid distance (i.e. the final distance between vectors), therefore, also increasing the processing time. By using an interpolation scheme with a good spectral response, in the dense predictor step of the algorithm, it is possible to increase the grid distance without decreasing the spatial resolution therefore decreasing the total processing time.

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Volumetric-correlation PIV to measure particle concentration and velocity of microflows

Volumetric-correlation particle image velocimetry (VPIV) is a new technique that provides a 3-dimensional 2-component velocity field from a single image plane. This single camera technique is simpler and cheaper to implement than multi-camera systems and has the capacity to measure time-varying flows. Additionally, this technique has significant advantages over other 3D PIV velocity measurement techniques, most notably in the capacity to measure highly seeded flows. Highly seeded flows, often unavoidable in industrial and biological flows, offer considerable advantages due to higher information density and better overall signal-to-noise ratio allowing for optimal spatial and temporal resolution. Here, we further develop VPIV adding the capability to measure concentration and increasing the robustness and accuracy of the technique. Particle concentrations are calculated using volumetric auto-correlations, and subsequently the velocities are calculated using volumetric cross-correlation corrected for variations in particle concentration. Along with the ability to calculate the particle concentration profile, our enhanced VPIV produces significant improvement in the accuracy of velocity measurements. Furthermore, this technique has been demonstrated to be insensitive to out-of-plane flows. The velocity measurement accuracy of the enhanced VPIV exceeds that of standard micro-PIV measurements, especially in near-wall regions. The 3D velocity and particle-concentration measurement capability of VPIV are demonstrated using both synthetic and experimental results.     

Holographic sensor for measurement of wall velocity gradients

Time-resolved measurements of skin friction and boundary layer turbulence are important to the design of more fuel efficient aircraft. In this paper we describe the design and testing of a holographic fan fringe sensor that can non-intrusively measure time-resolved velocity gradients near an aerodynamic surface. The holographic sensor produces a set of optical interference fringes inside the viscous sub-layer that form a fan rather than a linear array. Particles scattering light in the sub-layer produce a Doppler frequency that is a direct measurement of the velocity gradient and is proportional to aerodynamic shear stress and skin friction. The holographic recording condenses the optics necessary to form the fringes into a small 3–5 mm package, eliminates the need for optical access from behind the model, and produces a compact and robust sensor.     

Assessment of PIV to measure mean velocity and turbulence in open-channel flow

The complementary nature of PIV and LDV, in readily available configurations, is demonstrated along with their strengths and limitations by measurements in the flow over a two-dimensional dune in an open channel. This flow field is well suited to evaluate the relative performance of the two techniques as it contains much of the complexity found in practical hydraulic engineering. Agreement in the data obtained with the two techniques, even in regions of flow reversal and high shear, show that PIV is fast reaching a stage where it can be applied with a level of confidence similar to LDV.     

Experimental estimation of fluctuating velocity and scalar gradients in turbulence

The effect of numerical differentiation is investigated in the context of evaluating fluctuating velocity and scalar quantities in turbulent flows. In particular, 2-point forward-difference and 3-, 5-, 7-, and 9-point centred-difference schemes are investigated. The spectral technique introduced by Wyngaard (in J Sci Instr 1(2):1105–1108, 1968) for homogeneous turbulence is used to quantify the effects of the schemes. Numerical differentiation is shown to attenuate gradient spectra over a range of wavenumbers. The spectral attenuation, which varies with the order of the scheme, results in a reduction in the measured mean-squared gradients. High-order schemes (e.g. 7- or 9-point) are shown to significantly decrease the attenuation at all wavenumbers and as a result produce more accurate gradients. Hot-wire measurements and direct numerical simulations of decaying homogeneous, isotropic turbulence are found to be in good agreement with the predictions of the analysis, which suggests that high-order schemes can be used to improve empirical gradient estimates. The shape of the probability density functions is also found to be sensitive to the choice of numerical differentiation scheme. The effect of numerical differentiation is also discussed with respect to particle image velocimetry (PIV) measurements of a nominally two-dimensional planar mixing layer. It is found that the relatively low signal-to-noise ratio inherent in typical PIV measurements necessitates the use of low-order schemes to prevent excessive noise amplification, which increases with the order of the scheme. The results of the present work demonstrate that high-order numerical differentiation schemes can be employed to more accurately resolve gradients measured at a given resolution provided the measurements have an adequate signal-to-noise ratio.     

Statistics of velocity gradients in turbulence at moderate reynolds numbers

A direct numerical simulation of the Navier-Stokes equation is performed in order to investigate the small scale structure of turbulence at moderately large microscale Reynolds numbers 40–140, using the spectral method with 340³ modes starting from a high-symmetric flow. It is shown that the small scale motion is statistically isotropic. The probability density distribution of the velocity is Gaussian, while those of the velocity gradients and the vorticity are not Gaussian but have long exponential tails. The moments of the velocity gradients are expressed in terms of the gamma function, and the ratio of the moments of the velocity gradients of successive orders increases linearly with the order. A comparison is made with a laboratory experiment.     

Errors in hot-wire X-probe measurements induced by unsteady velocity gradients

 Errors in hot-wire X-probe measurements due to unsteady velocity gradients are investigated by a comparison of hot-wire and laser Doppler velocimetry (LDV) measurements. The studied flow case is a laminar boundary layer subjected to high levels of free-stream turbulence, and the hot-wire data shows a local maximum in the wall-normal fluctuation velocity inside the boundary layer. The observed maximum is in agreement with existing hot-wire data, but in conflict with the present LDV measurements as well as existing results from numerical simulations. An explanation for the measurement error is suggested in the paper. Received: 16 October 2000 / Accepted: 23 July 2001     

Systematic errors in PIV by realizing velocity offsets with the rotating mirror method

The observation of a flowfield in PIV via a mirror causes aberrations in the image plane which can reach several percent of the displacement to be measured. These imaging errors are investigated theoretically and the results are confirmed by comparison with experimental data. Several experimental parameters are discussed in respect to their influence on the displacement errors.