Tomographic particle image velocimetry

This paper describes the principles of a novel 3D PIV system based on the illumination, recording and reconstruction of tracer particles within a 3D measurement volume. The technique makes use of several simultaneous views of the illuminated particles and their 3D reconstruction as a light intensity distribution by means of optical tomography. The technique is therefore referred to as tomographic particle image velocimetry (tomographic-PIV). The reconstruction is performed with the MART algorithm, yielding a 3D array of light intensity discretized over voxels. The reconstructed tomogram pair is then analyzed by means of 3D cross-correlation with an iterative multigrid volume deformation technique, returning the three-component velocity vector distribution over the measurement volume. The principles and details of the tomographic algorithm are discussed and a parametric study is carried out by means of a computer-simulated tomographic-PIV procedure. The study focuses on the accuracy of the light intensity field reconstruction process. The simulation also identifies the most important parameters governing the experimental method and the tomographic algorithm parameters, showing their effect on the reconstruction accuracy. A computer simulated experiment of a 3D particle motion field describing a vortex ring demonstrates the capability and potential of the proposed system with four cameras. The capability of the technique in real experimental conditions is assessed with the measurement of the turbulent flow in the near wake of a circular cylinder at Reynolds 2,700.     

Large-scale tomographic particle image velocimetry using helium-filled soap bubbles

To measure large-scale flow structures in air, a tomographic particle image velocimetry (tomographic PIV) system for measurement volumes of the order of one cubic metre is developed, which employs helium-filled soap bubbles (HFSBs) as tracer particles. The technique has several specific characteristics compared to most conventional tomographic PIV systems, which are usually applied to small measurement volumes. One of them is spot lights on the HFSB tracers, which slightly change their position, when the direction of observation is altered. Further issues are the large particle to voxel ratio and the short focal length of the used camera lenses, which result in a noticeable variation of the magnification factor in volume depth direction. Taking the specific characteristics of the HFSBs into account, the feasibility of our large-scale tomographic PIV system is demonstrated by showing that the calibration errors can be reduced down to 0.1 pixels as required. Further, an accurate and fast implementation of the multiplicative algebraic reconstruction technique, which calculates the weighting coefficients when needed instead of storing them, is discussed. The tomographic PIV system is applied to measure forced convection in a convection cell at a Reynolds number of 530 based on the inlet channel height and the mean inlet velocity. The size of the measurement volume and the interrogation volumes amount to 750 mm × 450 mm × 165 mm and 48 mm × 48 mm × 24 mm, respectively. Validation of the tomographic PIV technique employing HFSBs is further provided by comparing profiles of the mean velocity and of the root mean square velocity fluctuations to respective planar PIV data.     

Volumetric correlation PIV: a new technique for 3D velocity vector field measurement

A method is proposed that allows three-dimensional (3D) two-component measurements to be made by means of particle image velocimetry (PIV) in any volume illuminated over a finite thickness. The method is based on decomposing the cross-correlation function into various contributions at different depths. Because the technique is based on 3D decomposition of the correlation function and not reconstruction of particle images, there is no limit to particle seeding density as experienced by 3D particle tracking algorithms such as defocusing PIV and tomographic PIV. Correlations from different depths are differentiated by the variation in point spread function of the lens used to image the measurement volume over that range of depths. A number of examples are demonstrated by use of synthetic images which simulate micro-PIV (μPIV) experiments. These examples vary from the trivial case of Couette flow (linear variation of one velocity component over depth) to a general case where both velocity components vary by different complex functions over the depth. A final validation—the measurement of a parabolic velocity profile over the depth of a microchannel flow—is presented. The same method could also be applied using a thick light sheet in macro-scale PIV and in a stereo configuration for 3D three-component PIV.     

Volume self-calibration for 3D particle image velocimetry

Planar self-calibration methods have become standard for stereo PIV to correct misalignments between laser light sheet and calibration plane. Computing cross-correlation between images from camera 1 and 2 taken at the same time, non-zero disparity vectors indicate rotational and translational misalignments relative to the coordinate system defined by a calibration plate. This approach works well for thin light sheets but fails for extended volumes recorded in 3D-PTV or tomographic PIV experiments. Here it is primarily necessary to correct calibration errors leading to triangulation errors in 3D-PTV or in degraded tomographic volume reconstruction. Tomographic PIV requires calibration accuracies of a fraction of a pixel throughout the complete volume, which is difficult to achieve experimentally. A new volumetric self-calibration technique has been developed based on the computation of the 3D position of matching particles by triangulation as in 3D-PTV. The residual triangulation error (‘disparity’) is then used to correct the mapping functions for all cameras. A statistical clustering method suitable for dense particle images has been implemented to find correct disparity map peaks from true particle matches. Disparity maps from multiple recordings are summed for better statistics. This self-calibration scheme has been validated using several tomographic PIV experiments improving the vector quality significantly. The relevance for other 3D velocimetry methods is discussed.     

Tomographic PIV measurements in a turbulent lifted jet flame

Measurements of instantaneous volumetric flow fields are required for an improved understanding of turbulent flames. In non-reacting flows, tomographic particle image velocimetry (TPIV) is an established method for three-dimensional (3D) flow measurements. In flames, the reconstruction of the particles location becomes challenging due to a locally varying index of refraction causing beam-steering. This work presents TPIV measurements within a turbulent lifted non-premixed methane jet flame. Solid seeding particles were used to provide the 3D flow field in the vicinity of the flame base, including unburned and burned regions. Four cameras were arranged in a horizontal plane around the jet flame. Following an iterative volumetric self-calibration procedure, the remaining disparity caused by the flame was less than 0.2 pixels. Comparisons with conventional two-component PIV in terms of mean and rms values provided additional confidence in the TPIV measurements.     

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.     

Deep field noise in holographic particle image velocimetry (HPIV): numerical and experimental particle image field modelling

 Holographic recording overcomes the limits in 2-D particle image velocimetry (PIV) to cover a 3-D flow field volume. Interrogation by focusing on single planes in a reconstructed particle field is disturbed by noise from out-of-focus particles. A numerical simulation models image reconstruction and shows how validation rates depend on aperture and volume depth. An experimental model environment of scattering particles in moveable plastic slices gives support to the numerical results. Simulations and tests are carried out for interrogation by autocorrelation and crosscorrelation techniques and furnish guidelines for system design. Received: 27 December 1996 / Accepted: 14 August 1997     

An efficient and accurate approach to MTE-MART for time-resolved tomographic PIV

The motion-tracking-enhanced MART (MTE-MART; Novara et al. in Meas Sci Technol 21:035401, 2010) has demonstrated the potential to increase the accuracy of tomographic PIV by the combined use of a short sequence of non-simultaneous recordings. A clear bottleneck of the MTE-MART technique has been its computational cost. For large datasets comprising time-resolved sequences, MTE-MART becomes unaffordable and has been barely applied even for the analysis of densely seeded tomographic PIV datasets. A novel implementation is proposed for tomographic PIV image sequences, which strongly reduces the computational burden of MTE-MART, possibly below that of regular MART. The method is a sequential algorithm that produces a time-marching estimation of the object intensity field based on an enhanced guess, which is built upon the object reconstructed at the previous time instant. As the method becomes effective after a number of snapshots (typically 5–10), the sequential MTE-MART (SMTE) is most suited for time-resolved sequences. The computational cost reduction due to SMTE simply stems from the fewer MART iterations required for each time instant. Moreover, the method yields superior reconstruction quality and higher velocity field measurement precision when compared with both MART and MTE-MART. The working principle is assessed in terms of computational effort, reconstruction quality and velocity field accuracy with both synthetic time-resolved tomographic images of a turbulent boundary layer and two experimental databases documented in the literature. The first is the time-resolved data of flow past an airfoil trailing edge used in the study of Novara and Scarano (Exp Fluids 52:1027–1041, 2012); the second is a swirling jet in a water flow. In both cases, the effective elimination of ghost particles is demonstrated in number and intensity within a short temporal transient of 5–10 frames, depending on the seeding density. The increased value of the velocity space–time correlation coefficient demonstrates the increased velocity field accuracy of SMTE compared with MART.     

Pulsed, high-power LED illumination for tomographic particle image velocimetry

This paper investigates the use of high-power light-emitting diode (LED) illumination for tomographic particle image velocimetry (PIV) as an alternative to traditional laser-based illumination. Modern solid-state LED devices can provide averaged radiant power in excess of 10 W and by operating the LED with short high current pulses theoretical pulse energies up to several tens of mJ can be achieved. In the present work, a custom-built drive circuit is used to drive a Luminus PT-120 high-power LED at pulsed currents of up to 150 A and 1 μs duration. Volumetric illumination is achieved by directly projecting the LED into the flow to produce a measurement volume of ≈3–4 times the size of the LED die. The feasibility of the volumetric LED illumination is assessed by performing tomographic PIV of homogenous, grid-generated turbulence. Two types of LEDs are investigated, and the results are compared with measurements of the same flow using pulsed Nd:YAG laser illumination and DNS data of homogeneous isotropic turbulence. The quality of the results is similar for both investigated LEDs with no significant difference between the LED and Nd:YAG illumination. Compared with the DNS, some differences are observed in the power spectra and the probability distributions of the fluctuating velocity and velocity gradients. These differences are attributed to the limited spatial resolution of the experiments and noise introduced during the tomographic reconstruction (i.e. ghost particles). The uncertainty in the velocity measurements associated with the LED illumination is estimated to approximately 0.2–0.3 pixel for both LEDs, which compares favourably with similar tomographic PIV measurements of turbulent flows. In conclusion, the proposed high-power, pulsed LED volume illumination provides accurate and reliable tomographic PIV measurements in water and presents a promising technique for flow diagnostics and velocimetry.     

Simultaneous measurements of velocity and density in buoyancy-driven mixing

A variant of the particle image velocimetry (PIV) technique is described for measuring velocity and density simultaneously in a turbulent Rayleigh-Taylor mixing layer. The velocity field is computed by the usual PIV technique of cross-correlating two consecutive images, and deducing particle displacements from correlation peaks of intensity fields. Different concentrations of seed particles are used in the two streams of different temperature (density) fluids, and a local measure of the density is obtained by spatially averaging over an interrogation window. Good agreement is reported between the first- and second-order statistics for density obtained from this technique and from a thermocouple. Velocity-density correlations computed by cross-correlating individual time series are presented. The errors in the density measurements are quantified and analyzed, and the issue of spatial resolution is also discussed. Our purpose for this paper is to introduce the PIV-S method and validate its accuracy against corresponding thermocouple measurements.     

Non-intrusive temperature measurement using microscale visualization techniques

μPIV is a widely accepted tool for making accurate measurements in microscale flows. The particles that are used to seed the flow, due to their small size, undergo Brownian motion which adds a random noise component to the measurements. Brownian motion introduces an undesirable error in the velocity measurements, but also contains valuable temperature information. A PIV algorithm which detects both the location and broadening of the correlation peak can measure velocity as well as temperature simultaneously using the same set of images. The approach presented in this work eliminates the use of the calibration constant used in the literature (Hohreiter et al. in Meas Sci Technol 13(7):1072–1078, 2002), making the method system-independent, and reducing the uncertainty involved in the technique. The temperature in a stationary fluid was experimentally measured using this technique and compared to that obtained using the particle tracking thermometry method and a novel method, low image density PIV. The method of cross-correlation PIV was modified to measure the temperature of a moving fluid. A standard epi-fluorescence μPIV system was used for all the measurements. The experiments were conducted using spherical fluorescent polystyrene-latex particles suspended in water. Temperatures ranging from 20 to 80°C were measured. This method allows simultaneous non-intrusive temperature and velocity measurements in integrated cooling systems and lab-on-a-chip devices.     

A scanning PIV method for fine-scale turbulence measurements

A hybrid technique is presented that combines scanning PIV with tomographic reconstruction to make spatially and temporally resolved measurements of the fine-scale motions in turbulent flows. The technique uses one or two high-speed cameras to record particle images as a laser sheet is rapidly traversed across a measurement volume. This is combined with a fast method for tomographic reconstruction of the particle field for use in conjunction with PIV cross-correlation. The method was tested numerically using DNS data and with experiments in a large mixing tank that produces axisymmetric homogeneous turbulence at \(R_\lambda \simeq 219\) . A parametric investigation identifies the important parameters for a scanning PIV set-up and provides guidance to the interested experimentalist in achieving the best accuracy. Optimal sheet spacings and thicknesses are reported, and it was found that accurate results could be obtained at quite low scanning speeds. The two-camera method is the most robust to noise, permitting accurate measurements of the velocity gradients and direct determination of the dissipation rate.     

Construction of three-dimensional flow structure out of two-dimensional steady flow field velocity measurements

 Two-dimensional particle image velocimetry (PIV) is used to obtain a set of parallel vector maps in spanwise direction over the delta wing configuration ELAC. The out-of-plane velocity component is then constructed by application of continuity equation. This yields the whole three-dimensional separated flow field over the leeward side of the model. The spatial resolution of the measurements enables a detailed examination of the three-dimensional flow structure. The growth and the helical structure of primary vortex as well as smaller flow structures caused by secondary separation can be observed. Accuracy of the constructed velocity component is estimated with help of a numerically obtained three-dimensional dataset of the flow field around this configuration. The reconstruction procedure was applied to this data set taking the experimental uncertainty and the grid spacing of the PIV measurements into consideration. A comparison of reconstructed out-of-plane component and data of the numerical solution of Navier–Stokes equations results in a promising low error. A statistical analysis of different procedures allows interpretation of reconstruction capabilities. Received: 15 April 1998 / Accepted: 15 September 1998     

Vector post-processing algorithm for phase discrimination of two-phase PIV

A simple phase separation method using vector post-processing techniques is evaluated to measure velocity fields in a bubble plume. To provide for validation, fluorescent seeding is used, and two sets of synoptic images are obtained: mixed-phase images containing bubbles and fluorescent particles, and fluid-phase images containing only fluorescent particles. A third dataset is derived by applying a digital mask to remove bubbles from the mixed-phase images. All datasets are processed using cross-correlation particle image velocimetry (PIV). The resulting vector maps for the raw, mixed-phase data contain both bubble and continuous-phase velocity vectors. To separate the phases, a vector post-processing algorithm applies a maximum velocity threshold for the continuous-phase velocities coupled with the vector median filter to identify remaining bubble-velocity vectors and remove them from the mixed-phase velocity field. To validate the phase separation algorithm, the post-processed fluid-phase vectors are compared to PIV results obtained from both the optically separated and digitally masked data. The comparison among these methods shows that the post-processed mixed-phase data have small errors in regions near some bubbles, but for dilute environmental flows (low void fraction and slip velocity approximately equal to the entrained fluid velocity), the algorithm predicts well both instantaneous and time average statistical quantities. The method is reliable for flows having 10% or less of the field of view occupied by bubbles. The resulting instantaneous data provide information on plume wandering and eddy-size distributions within the bubble plume. By comparison among the datasets, it is shown that the patchiness of the vector-post processed and image masked data limit the diameter of identifiable eddy structures to the average distance between bubbles in the image, and that both datasets give identical probability density functions of eddy size. The optically filtered data have better data coverage and predict a greater probability of larger eddies as compared to the other two datasets.     

Interpretation of PIV autocorrelation mesurements in complex particle-laden flows

Particle image velocimetry (PIV) was used to measure instantaneous and average particle velocity fields near the stagnation zone of a particle-laden impinging air jet. The results were compared with Lagrangian particle tracking measurements. Ensemble averages from the two methods agree well except in regions where particles have different histories, and a specific trajectory is dominant but not exclusive. The PIV autocorrelation method loses information regarding non-dominant particle trajectories. Thus, although instantaneous PIV measurements yield the dominant particle velocities correctly, the averaged measurements are biased in some regions.This work was supported by the Electric Power Research Institute under Contract RP 8034-01. We thank the 3M Corporation for their generous materials support.     

On the velocity of ghost particles and the bias errors in Tomographic-PIV

The paper discusses bias errors introduced in Tomographic-PIV velocity measurements by the coherent motion of ghost particles under some circumstances. It occurs when a ghost particle is formed from the same set of actual particles in both reconstructed volumes used in the cross-correlation analysis. The displacement of the resulting ghost particle pair is approximately the average displacement of the set of associated actual particles. The effect is further quantified in a theoretical analysis and in numerical simulations and illustrated in an actual experiment. It is shown that the bias error does not significantly affect the measured flow topology as deduced in an evaluation of the local velocity gradients. Instead, it leads to a systematic underestimation of the measured particle displacement gradient magnitude. This phenomenon is alleviated when the difference between particles displacement along the volume depth is increased beyond a particle image diameter, or when the reconstruction quality is increased or when the accuracy of the tomographic reconstruction is improved. Furthermore, guidelines to detect and avoid such bias errors are proposed.     

Measurement of the acoustic velocity field of nonlinear standing waves using the synchronized PIV technique

The motion of gas within an air-filled rigid-walled square channel subjected to acoustic standing waves is experimentally investigated. The synchronized particle image velocimetry (PIV) technique has been used to measure the acoustic velocity fields at different phases over the excitation signal period. The acoustic velocity measurements have been conducted for two different acoustic intensities in the quasi-nonlinear range (in which the nonlinear effects can be neglected in comparison with the dissipation effects), and one acoustic intensity in the finite-amplitude nonlinear range (in which both the nonlinear term and the dissipative term play a role in the wave equation). The experimental velocity fields for the quasi-nonlinear cases are compared with the analytical results obtained from the time-harmonic solution of the wave equation. Good agreement between the experimental and analytical velocity fields proves the ability of the synchronized PIV technique to accurately measure both temporal and spatial variations of the acoustic velocity fields. The verified technique is then used to measure the acoustic velocity fields of the finite-amplitude nonlinear case at different phases.     

Dual-plane stereoscopic particle image velocimetry: system set-up and its application on a lobed jet mixing flow

 The technical basis and system set-up of a dual-plane stereoscopic particle image velocimetry (PIV) system, which can obtain the flow velocity (all three components) fields at two spatially separated planes simultaneously, is summarized. The simultaneous measurements were achieved by using two sets of double-pulsed Nd:Yag lasers with additional optics to illuminate the objective fluid flow with two orthogonally linearly polarized laser sheets at two spatially separated planes, as proposed by Kaehler and Kompenhans in 1999. The light scattered by the tracer particles illuminated by laser sheets with orthogonal linear polarization were separated by using polarizing beam-splitter cubes, then recorded by high-resolution CCD cameras. A three-dimensional in-situ calibration procedure was used to determine the relationships between the 2-D image planes and three-dimensional object fields for both position mapping and velocity three-component reconstruction. Unlike conventional two-component PIV systems or single-plane stereoscopic PIV systems, which can only get one-component of vorticity vectors, the present dual-plane stereoscopic PIV system can provide all the three components of the vorticity vectors and various auto-correlation and cross-correlation coefficients of flow variables instantaneously and simultaneously. The present dual-plane stereoscopic PIV system was applied to measure an air jet mixing flow exhausted from a lobed nozzle. Various vortex structures in the lobed jet mixing flow were revealed quantitatively and instantaneously. In order to evaluate the measurement accuracy of the present dual-plane stereoscopic PIV system, the measurement results were compared with the simultaneous measurement results of a laser Doppler velocimetry (LDV) system. It was found that both the instantaneous data and ensemble-averaged values of the stereoscopic PIV measurement results and the LDV measurement results agree well. For the ensemble-averaged values of the out-of-plane velocity component at comparison points, the differences between the stereoscopic PIV and LDV measurement results were found to be less than 2%. Received: 18 April 2000/Accepted: 2 February 2001     

Acceleration of Tomo-PIV by estimating the initial volume intensity distribution

Tomographic particle image velocimetry (Tomo-PIV) is a promising new PIV technique. However, its high computational costs often make time-resolved measurements impractical. In this paper, a new preprocessing method is proposed to estimate the initial volume intensity distribution. This relatively inexpensive “first guess” procedure significantly reduces the computational costs, accelerates solution convergence, and can be used directly to obtain results up to 35 times faster than an iterative reconstruction algorithm (with only a slight accuracy penalty). Reconstruction accuracy is also assessed by examining the errors in recovering velocity fields from artificial data (rather than errors in the particle reconstructions themselves).