Three-dimensional particle imaging with a single camera

A new approach to the instantaneous three-dimensional mapping of flow fields is introduced. A single camera system uses defocusing in conjunction with a mask (three pin holes) embedded in the camera lens to decode three-dimensional point sources of light (i.e., illuminated particles) on a single image. The sizes and locations of the particle image patterns on the image plane relate directly to the three-dimensional positions of the individual particles. Using sequential images, particles may be tracked in space and time, yielding whole-field velocity information. Calibration of the system is straightforward, whereas the self-similarity of the particle image patterns can be used in automating the data-extraction process. The described technique was used to obtain particle trajectories in the flow field of a vortex ring impinging on a wall.     

Three-dimensional particle tracking method using FPGA-based real-time image processing and four-view image splitter

We present a cost-effective solution of the three-dimensional particle tracking velocimetry (3D-PTV) system based on the real-time image processing method (Kreizer et al. Exp Fluids 48:105–110, 2010) and a four-view image splitter. The image processing algorithm, based on the intensity threshold and intensity gradients estimated using the fixed-size Sobel kernel, is implemented on the field-programmable gate array integrated into the camera electronics. It enables extracting positions of tracked objects, such as tracers or large particles, in real time. The second major component of this system is a four-view split-screen device that provides four views of the observation volume from different angles. An open-source ray-tracing software package allows for a customized optical setup for the given experimental settings of working distances and camera parameters. The specific design enables tracking in larger observation volumes when compared to the designs published up to date. The present cost-effective solution is complemented with open-source particle tracking software that receives raw data acquired by the real-time image processing system and returns trajectories of the identified particles. The combination of these components simplifies the 3D-PTV technique by reducing the size and increasing recording speed and storage capabilities. The system is capable to track a multitude of particles at high speed and stream the data over the computer network. The system can provide a solution for the remotely controlled tracking experiments, such as in microgravity, underwater or in applications with harsh experimental conditions.     

三维射流PIV图像处理方法的研究及其精度分析

本文利用三台照相机系统记录三维射流的流动，通过照相机系统的标定、三维空间粒子的重构、空间粒子的对应及误对应向量的判断和消除等，建立了一种三个图像记录设备组成的三维PIV图像处理算法，并对其精度进行了分析，通过对三维射流图像的处理和分析表明，该方法是切实可行的。     

Shock tube spherical particle accelerating study for drag coefficient determination

An original particle accelerating technique has been developed for a shock tube. The trajectories of calibrated spherical particles and in diameter have been measured by the multiple exposure shadowgraph technique coupled with a high speed drum camera. Both particle velocity and acceleration, deduced from the experimental trajectories, allow the determination of the drag coefficients for different, subsonic and supersonic, flow regimes for the particle Reynolds numbers from to and the particle Mach numbers from 0.6 to 1.2. The drag coefficient values have been compared with different correlations found in the literature. Received 8 April 2002/ Accepted 17 June 2002 Published online 19 December 2002 Correspondence to: L. Houas (e-mail: Lazhar.Houas@polytech.univ-mrs.fr)     

Bichromatic particle streak velocimetry bPSV

We propose a novel technique for three-dimensional three-component (3D3C) interfacial flow measurement. It is based on the particle streak velocimetry principle. A relatively long integration time of the camera is used for capturing the movement of tracer particles as streaks on the sensor. The velocity along these streaks is extracted by periodically changing the illumination using a known pattern. A dye with different absorption characteristics in two distinct wavelengths is used to color the fluid. The depth of particles relative to the fluid interface can then be computed from their intensities when illuminated with light sources at those two different wavelengths. Hence, from our approach, a bichromatic, periodical illumination together with an image processing routine for precisely extracting particle streak features is used for measuring 3D3C fluid flow with a single camera. The technique is applied to measuring turbulent Rayleigh–Bénard convection at the free air--water interface. Using Lagrangian statistics, we are able to demonstrate a clear transition from the Batchelor regime to the Richardson regime, both of which were postulated for isotropic turbulence. The relative error of the velocity extraction of our new technique was found to be below 0.5?%.     

Measurement of Dean flow in a curved micro-tube using micro digital holographic particle tracking velocimetry

Digital micro holographic particle tracking velocimetry (HPTV) was used to measure the three-dimensional (3D) velocity field of a laminar flow in a curved micro-tube with a circular cross-section. The micro HPTV system consists of a high-speed camera and a single laser with an acoustic optical modulator (AOM) chopper. We obtained the temporal evolution of the instantaneous velocity field of water flow within curved micro-tubes with inner diameters of 100 and 300 μm. The 3D mean velocity-field distribution was obtained quantitatively by statistically averaging the instantaneous velocity fields. At low Dean numbers (De), a secondary flow was not generated in the curved tube; however, with increasing Dean number a secondary flow consisting of two large-scale counter-rotating vortices arose due to enhanced centrifugal force. To reveal the flow characteristics at high Dean numbers, the trajectories of fluid particles were evaluated experimentally from the 3D velocity-field data measured using the HPTV technique. The present experimental results, especially the 3D particle trajectories, are likely to be helpful in understanding mixing phenomena in curved sections of various 3D curved micro-tubes or micro-channels, as well as in the design of such structures.     

3D Flow reconstruction using ultrasound PIV

Ultrasound particle image velocimetry (PIV) can be used to obtain velocity fields in non-transparent geometries and/or fluids. In the current study, we use this technique to document the flow in a curved tube, using ultrasound contrast bubbles as flow tracer particles. The performance of the technique is first tested in a straight tube, with both steady laminar and pulsatile flows. Both experiments confirm that the technique is capable of reliable measurements. A number of adaptations are introduced that improve the accuracy and applicability of ultrasound PIV. Firstly, due to the method of ultrasound image acquisition, a correction is required for the estimation of velocities from tracer displacements. This correction accounts for the fact that columns in the image are recorded at slightly different instances. The second improvement uses a slice-by-slice scanning approach to obtain three-dimensional velocity data. This approach is here demonstrated in a strongly curved tube. The resulting flow profiles and wall shear stress distribution shows a distinct asymmetry. To meaningfully interpret these three-dimensional results, knowledge of the measurement thickness is required. Our third contribution is a method to determine this quantity, using the correlation peak heights. The latter method can also provide the third (out-of-plane) component if the measurement thickness is known, so that all three velocity components are available using a single probe.     

Three-dimensional simulation of a dust lifting process with varying parameters

This article presents modelling considerations and simulation results for a dust lifting process in a three-dimensional domain. The Eulerian–Lagrangian modelling technique is used. Multiple simulations with different values for the number of particles were performed. The results of the simulations are shown as snapshots of particle position at certain points in time after the passage of a shock wave. Statistical data for the particle positions and collisions are presented. These are: the average height of the particles, the mean square displacement of the particles and the cumulative number of recorded collisions plotted as functions of time. The particle averaged kinetic energy and the mechanical energy lost by particles during collisions are recorded as functions of time in order to study the motion of particles. The results show that simulations of an increasing number of particles render a less intense lifting effect and, more importantly, that the inter-particle and particle–wall collisions represent essential phenomena and need to be included in this type of model. Also, a comparison between two-dimensional and three-dimensional simulations was performed. It was found that, although 2D simulations are still useful, they overestimate the lifting process and therefore a 3D model is preferable. The influence of the magnitude of the restitution and friction coefficients on the process was also studied.     

A quantitative study of three-dimensional Lagrangian particle tracking algorithms

A neural network particle finding algorithm and a new four-frame predictive tracking algorithm are proposed for three-dimensional Lagrangian particle tracking (LPT). A quantitative comparison of these and other algorithms commonly used in three-dimensional LPT is presented. Weighted averaging, one-dimensional and two-dimensional Gaussian fitting, and the neural network scheme are considered for determining particle centers in digital camera images. When the signal to noise ratio is high, the one-dimensional Gaussian estimation scheme is shown to achieve a good combination of accuracy and efficiency, while the neural network approach provides greater accuracy when the images are noisy. The effect of camera placement on both the yield and accuracy of three-dimensional particle positions is investigated, and it is shown that at least one camera must be positioned at a large angle with respect to the other cameras to minimize errors. Finally, the problem of tracking particles in time is studied. The nearest neighbor algorithm is compared with a three-frame predictive algorithm and two four-frame algorithms. These four algorithms are applied to particle tracks generated by direct numerical simulation both with and without a method to resolve tracking conflicts. The new four-frame predictive algorithm with no conflict resolution is shown to give the best performance. Finally, the best algorithms are verified to work in a real experimental environment.     

A method for automatic particle tracking in a three-dimensional flow field

A technique has been developed whereby the three-dimensional motion of tracers in a fluid flow is automatically analysed. Simultaneous orthogonal views of the tracer-seeded flow were recorded by a single high speed cine camera through a split field mirror system, and subsequently converted to machine readable form by a video digitizer. Digital enhancement was used to separate the tracers from the contrasting background. Algorithms were developed to match the projections of individual tracers in the two views, obtain the three-dimensional coordinates, follow the tracers from frame to frame and compute the velocity vectors along the particle trajectories. Eulerian information was derived from the pooled velocity data points by interpolation on a regular spatial grid. Tests of the method on particle trajectories obtained in a small water tunnel have shown that the tracking is reliable even for rapidly changing and closely spaced paths.     

New tracking algorithm for particle image velocimetry

The cross correlation tracking technique is widely used to analyze image data, in Particle Image Velocimetry (PIV). The technique assumes that the fluid motion, within small regions of the flow field, is parallel over short time intervals. However, actual flow fields may have some distorted motion, such as rotation, shear and expansion. Therefore, if the distortion of the flow field is not negligible, the fluid motion can not be tracked well using the cross correlation technique. In this study, a new algorithm for particle tracking, called the Spring Model technique, has been proposed. The algorithm can be applied to flow fields which exhibit characteristics such as rotation, shear and expansion.The algorithm is based on pattern matching of particle clusters between the first and second image. A particle cluster is composed of particles which are assumed to be connected by invisible elastic springs. Depending on the deformation of the cluster pattern (i.e., the particle positions), the invisible springs have some forces. The smallest force pattern in the second image is the most probable pattern match to the correspondent original pattern in the first image. Therefore, by finding the best matches, particle movements can be tracked between the two images. Three-dimensional flow fields can also be reconstructed with this technique.The effectiveness of the Spring Model technique was verified with synthetic data from both a two-dimensional flow and three-dimensional flow. It showed a high degree of accuracy, even for the three-dimensional calculation. The experimental data from a vortex flow field in a cylinder wake was also measured by the Spring model technique.     

Dust suspensions accelerated by shock waves

The motion of dust suspensions accelerated by shock waves has been experimentally investigated in a vertical shock tube, in which a completely developed plane shock wave of moderate strength propagates into a homogeneously distributed dust suspension with a planar interface. Trajectories of the accelerated interfaces as well as transmitted and reflected shock waves are recorded by using a shadowgraph system with a Cranz-Schardin camera. Two kinds of particle samples, i.e. porous lycopodium particles 30 μm in diameter and corn starch particles with a mean diameter of 10 μm, are employed. The effects of shock wave strength and particle loading ratio are also examined. Experimental data are compared with theoretical results, and the agreement is good. Received: 7 October 1998/Accepted: 1 June 1999     

Explosively driven particle fields imaged using a high speed framing camera and particle image velocimetry

A high speed framing camera and a particle image velocimetry instrument were used to determine the properties of explosively driven particle fields in early microsecond and later millisecond times. Test items were configured in a two inch long cylindrical shape with a half inch diameter core of organic explosive. The core was surrounded by a particle bed of aluminum or tungsten powder of a specific particle size distribution. Position data from the leading edge of the particle fronts for each charge was recorded with a high speed framing camera at early time and with a particle image velocimetry (PIV) instrument at later time to determine particle velocity. Using a PIV image, a velocity gradient along the length of the particle field was established by using the mean particle velocity value determined from three separate horizontal bands that transverse the particle field. The results showed slower particles at the beginning of the particle field closest to the source and faster ones at the end. Differences in particle dispersal, luminescence, and agglomeration were seen when changes in the initial particle size and material type were made. The aluminum powders showed extensive luminescence with agglomeration forming large particle structures while the tungsten powder showed little luminescence, agglomeration and no particle structures. Combining velocity data from the high speed framing camera and PIV, the average drag coefficient for each powder type was determined. The particle field velocities and drag coefficients at one meter showed good agreement with the numerical data produced from a computational fluid dynamics code that takes advantage of both Eulerian and Lagrangian solvers to track individual particles after a set post detonation time interval.     

Three-dimensional tracking of the long time trajectories of suspended particles in a lid-driven cavity flow

Stereo imaging methods are used to measure the positions of solid spherical particles suspended in a viscous liquid and enclosed in a transparent cubic cavity. The liquid and particle motions are driven at the top lid by a conveyor belt operated at constant speed. Based on sequences of stereo views of the full cavity, the particles are tracked continuously along their three-dimensional orbits. The corresponding position histories are treated as noisy stochastic data and processed using Kalman filters to fill data gaps and attenuate the effect of measurement errors. The lid-driven viscous flow is characterised by an intricate internal structure which is mirrored in the particle paths. The tracks of the solid particles align with long exposure images of laser-illuminated micro-particles in selected transverse planes. Nevertheless, their long time trajectories appear to cluster along preferential pathways of the internal circulation pattern.     

Numerical investigation of particle lateral migration in straight channel flows using a direct-forcing immersed boundary method

Inertia-induced cross-stream migration has been recently exploited for precise position of particles in confined channel flows. In this work, a three-dimensional finite volume based immersed boundary method has been developed to study the lateral migration and hydrodynamic self-assembly of neutrally-buoyant particles in pressure-driven flows. Simulation results show that, in 2D channel flows, the equilibrium position for a circular particle is closer to the centreline for larger particle Reynolds number due to the increasing flow rate, while in 3D square duct flow, the equilibrium position for a spherical particle is near a face centre and is closer to the wall for larger particle Reynolds number. Self-assembly of a pair of particles is observed in 3D square duct flows but not in 2D channel flows. Mechanisms for the self-assembly are discussed.     

Three-dimensional, three-component wall-PIV

This paper describes a new time-resolved three-dimensional, three-component (3D-3C) measurement technique called wall-PIV. It was developed to assess near wall flow fields and shear rates near non-planar surfaces. The method is based on light absorption according to Beer–Lambert’s law. The fluid containing a molecular dye and seeded with buoyant particles is illuminated by a monochromatic, diffuse light. Due to the dye, the depth of view is limited to the near wall layer. The three-dimensional particle positions can be reconstructed by the intensities of the particle’s projection on an image sensor. The flow estimation is performed by a new algorithm, based on learned particle trajectories. Possible sources of measurement errors related to the wall-PIV technique are analyzed. The accuracy analysis was based on single particle experiments and a three-dimensional artificial data set simulating a rotating sphere.     

On the resolution limit of digital particle image velocimetry

This work analyzes the spatial resolution that can be achieved by digital particle image velocimetry (DPIV) as a function of the tracer particles and the imaging and recording system. As the in-plane resolution for window-correlation evaluation is related by the interrogation window size, it was assumed in the past that single-pixel ensemble-correlation increases the spatial resolution up to the pixel limit. However, it is shown that the determining factor limiting the resolution of single-pixel ensemble-correlation are the size of the particle images, which is dependent on the size of the particles, the magnification, the f-number of the imaging system, and the optical aberrations. Furthermore, since the minimum detectable particle image size is determined by the pixel size of the camera sensor in DPIV, this quantity is also considered in this analysis. It is shown that the optimal magnification that results in the best possible spatial resolution can be estimated from the particle size, the lens properties, and the pixel size of the camera. Thus, the information provided in this paper allows for the optimization of the camera and objective lens choices as well as the working distance for a given setup. Furthermore, the possibility of increasing the spatial resolution by means of particle tracking velocimetry (PTV) is discussed in detail. It is shown that this technique allows to increase the spatial resolution to the subpixel limit for averaged flow fields. In addition, PTV evaluation methods do not show bias errors that are typical for correlation-based approaches. Therefore, this technique is best suited for the estimation of velocity profiles.     

Dynamics of particles floating on liquid flowing in a semicircular open channel

The dynamic characteristics of surface-floating particles in liquids flowing in a two-dimensional, semicircular open channel is studied experimentally. For high visibility in the experiments, relatively large particles are employed whose particle-liquid density ratio is either equal to or less than unity. Particles of different size and geometry are tested in a water-glycerin mixture. A video camera traces the pathline of each particle from which the velocity and direction of particle motion are evaluated. Liquid velocity distribution is determined by hot-film anemometry. A modified dynamics (Basset-Boussinesq-Oseen) equation is derived and numerically solved by means of a finite-difference technique to determine fluid velocity. A new dimensionless parameter is disclosed which is pertinent to both particle geometry and fluid flow conditions. It correlates particle trajectory and velocity, trajectory dispersion and fluid-particle velocity ratio.Visiting Scholar on leave from Department of Mechanical Engineering, Fukuyama University, Fukujama, Japan     

Polysiloxane coatings on microspheres based on Multiphase Flow with Interface Exchange-Discrete Element Modelling

Polysiloxane coatings on yttria stabilized zirconia (YSZ) microspheres of 500 μm were simulated in a spout fluidized bed coater using Multiphase Flow with Interface Exchange-Discrete Element Modelling (MFiX-DEM). Two different coater configurations were developed to study the influence of gas velocity and its distribution on particle dynamics. The presence of the Wurster tube not only enhances the distribution but also increases the overall residence time of the particles. Investigations were also carried out with different Wurster tube positions (normal, 10% and 20% lowered from its initial position). Among these, 20% lowered Wurster tube position demonstrated the most effective coating process. The effects of gas inlet pressure on the average gas velocity and the distribution of particles were analyzed. More than 97% of the particles can be retained. The derived results, including average gas velocity, particle retention percentage, and distribution of particles with gas velocity, are being used to guide the experimental work in obtaining defect-free coatings for YSZ microspheres.     

A genetic algorithm particle pairing technique for 3D velocity field extraction in holographic particle image velocimetry

 This research explores a novel technique, using Genetic Algorithm Particle Pairing (GAPP) to extract three-dimensional (3D) velocity fields of complex flows. It is motivated by Holographic Particle Image Velocimetry (HPIV), in which intrinsic speckle noise hinders the achievement of high particle density required for conventional correlation methods in extracting 3D velocity fields, especially in regions with large velocity gradients. The GA particle pairing method maps particles recorded at the first exposure to those at the second exposure in a 3D space, providing one velocity vector for each particle pair instead of seeking statistical averaging. Hence, particle pairing can work with sparse seeding and complex 3D velocity fields. When dealing with a large number of particles from two instants, however, the accuracy of pairing results and processing speed become major concerns. Using GA’s capability to search a large solution space parallelly, our algorithm can efficiently find the best mapping scenarios among a large number of possible particle pairing schemes. During GA iterations, different pairing schemes or solutions are evaluated based on fluid dynamics. Two types of evaluation functions are proposed, tested, and embedded into the GA procedures. Hence, our Genetic Algorithm Particle Pairing (GAPP) technique is characterized by robustness in velocity calculation, high spatial resolution, good parallelism in handling large data sets, and high processing speed on parallel architectures. It has been successfully tested on a simple HPIV measurement of a real trapped vortex flow as well as a series of numerical experiments. In this paper, we introduce the principle of GAPP, analyze its performance under different parameters, and evaluate its processing speed on different computer architectures. Received: 7 September 1997/Accepted: 3 February 1998