Holographic Particle Image Velocimetry Research Articles

The Mechanism of Droplet Thermocapillary Migration Coupled with Multi-Physical Fields

In this paper, the coupling effect of multiphysical fields of droplet migration is deeply studied by constructing a physical model of droplet migration with multiphysical fields. Digital holographic interferometry and particle image velocimetry are used to simultaneously measure the temperature and velocity fields of the mother liquor in the process of droplet migration for the first time. Due to the advancements of measuring, the zero-velocity region is also in the region where the thermal wake appears, four vortexes appear in the droplet migration and the off-axis behavior of double-droplet migration is found. The aim of this work is to analyze the coupling relationship of multiphysical fields, so as to reveal the physical laws of thermocapillary migration of single droplet and multiple droplets with the same phase and heterophase and to study the driving mechanism of the thermocapillary force and the flow of the mother liquor.

Efficient removal of indoor particulate matter using water microdroplets generated by a MHz-frequency ultrasonic atomizer

Airborne particulate matter (PM) has emerged as an important global environmental and social issue due to its harmful health effects. Various techniques have been introduced to remove indoor PM. However, an effective and sustainable method has not been established yet because of complex mechanisms and various factors. Here, we propose the use of water microdroplets generated by a MHz-frequency ultrasound, and experimentally examine the effects of the generated microdroplets on PM removal. The PM removal efficiency and PM deposition constant are analyzed by measuring the temporal variation of PM concentration. The measured experimental results are compared with analytical deposition constants. Two collection efficiencies derived in previous studies are employed to substitute a mathematical model used for determining the analytical deposition constants. In addition, the mean diameter and the moving velocity of the microdroplets are experimentally measured via a digital holographic microscopy and particle image velocimetry generated by a MHz-frequency atomizer. The present results demonstrate that water microdroplets generated by the atomizer can be effectively used to remove PM.

Particle depth position detection by 2D correlation in digital in-line holography.

In digital holographic particle image velocimetry, hologram truncation is a very prominent problem when the projection of the particle position to the sensor is close to the sensor edge. Using the convolution approach to reconstruct such a hologram yields a deformed particle image compared to a particle image resulting from a particle with a projection to the center of the sensor. This Letter shows that the deformation complicates particle position detection based on an algorithm originally developed for analog holography by Choo and Kang, and later applied to digital holography by Yang and Kang. This algorithm is refined for the detection of particle positions from the deformed images and applied to numerical and experimental data.

A review on noise suppression and aberration compensation in holographic particle image velocimetry

AbstractUnderstanding three-dimensional (3D) fluid flow behaviour is undeniably crucial in improving performance and efficiency in a wide range of applications in engineering and medical fields. Holographic particle image velocimetry (HPIV) is a potential tool to probe and characterize complex flow dynamics since it is a truly three-dimensional three-component measurement technique. The technique relies on the coherent light scattered by small seeding particles that are assumed to faithfully follow the flow for subsequent reconstruction of the same the event afterward. However, extraction of useful 3D displacement data from these particle images is usually aggravated by noise and aberration which are inherent within the optical system. Noise and aberration have been considered as major hurdles in HPIV in obtaining accurate particle image identification and its corresponding 3D position. Major contributions to noise include zero-order diffraction, out-of-focus particles, virtual image and emulsion grain sc...

Holographic time-resolved particle tracking by means of three-dimensional volumetric deconvolution.

Holographic particle image velocimetry allows tracking particle trajectories in time and space by means of holography. However, the drawback of the technique is that in the three-dimensional particle distribution reconstructed from a hologram, the individual particles can hardly be resolved due to the superimposed out-of-focus signal from neighboring particles. We demonstrate here a three-dimensional volumetric deconvolution applied to the reconstructed wavefront which results in resolving all particles simultaneously in three-dimensions. Moreover, we apply the three-dimensional volumetric deconvolution to reconstructions of a time-dependent sequence of holograms of an ensemble of polystyrene spheres moving in water. From each hologram we simultaneously resolve all particles in the ensemble in three dimensions and from the sequence of holograms we obtain the time-resolved trajectories of individual polystyrene spheres.

Holographic particle image velocimetry measurements in a four-valve combustion engine

This is a feasibility study to show that the nonreacting three-dimensional flow in the cylinder of a four-valve internal combustion engine at 160° after top dead center (atdc) at 1,500 rpm can be accurately measured by holographic particle image velocimetry. The results evidence the quality of holographic PIV measurements in engine flows and the capability of the holographic method to instantaneously capture the complete three-dimensional flow field in a large area of the highly intricate cylinder flow. The resolved measurement volume has a diameter of about 60 mm and a height of 80 mm with a vector spacing of 0.75 mm per vector. To validate the measurements, the flow structure as well as the turbulent kinetic energy of the flow field is compared with planar two-component/two-dimensional (2C/2D-PIV) measurements performed in the same engine (Dannemann et al., in Exp Fluids 2010). Furthermore, the spatial propagation of the flow field as well as the vortical structures is visualized by 3D streamlines and λ2-contours. The current results confirm the existence of several large-scale flow structures, such as a counter-rotating ring-vortex pair below the inlet valve and the tumble vortex. The latter possesses a U-shaped propagation of the vortex core. The analysis of the two-point correlation shows the integral length scale to be in the range 2.5–6.1 mm, which is in agreement with literature data.

Review on development of volumetric particle image velocimetry

Volumetric particle image velocimetry (PIV) is a laser technique measuring three-component velocity field in a volume. Common volumetric PIV techniques are defocusing PIV, multi-view PIV and holographic PIV. Tomographic PIV is an advanced approach of multi-view PIV, which significantly improves the spatial resolution of the measurement by using the multiplicative algebraic reconstruction technique (MART) to reconstruct the particle field. Due to the rapid progress being made in volumetric PIV measurements, this article focuses on introducing the principles of different volumetric PIV methods from aspects of particle reconstruction and velocity reconstruction. Advantages and limitations on applications are elaborated. Issues specific to volumetric PIV regarding illumination, digital imaging, depth of focus, ghost particle and spatial resolution are discussed.

Computationally efficient storage of 3D particle intensity and position data for use in 3D PIV and 3D PTV

Three-dimensional (3D) volumetric velocity measurement techniques, such as tomographic or holographic particle image velocimetry (PIV), rely upon the computationally intensive formation, storage and localized interrogation of multiple 3D particle intensity fields. Calculation of a single velocity field typically requires the extraction of particle intensities into tens of thousands of 3D sub-volumes or discrete particle clusters, the processing of which can significantly affect the performance of 3D cross-correlation based PIV and 3D particle tracking velocimetry (PTV). In this paper, a series of popular and customized volumetric data formats are presented and investigated using synthetic particle volumes and experimental data arising from tomographic PIV measurements of a turbulent boundary layer. Results show that the use of a sub-grid ordered non-zero intensity format with a sub-grid size of 16 × 16 × 16 points provides the best performance for cross-correlation based PIV analysis, while a particle clustered non-zero intensity format provides the best format for PTV applications. In practical tomographic PIV measurements the sub-grid ordered non-zero intensity format offered a 29% improvement in reconstruction times, while providing a 93% reduction in volume data requirements and a 28% overall improvement in cross-correlation based velocity analysis and validation times.

On measuring the joint probability density function of three-dimensional velocity components in turbulent flows

This paper presents the underlying theory to directly measure the joint probability density function (JPDF) of turbulent velocity fields. The raw data for these measurements can come from either reconstructed tomographic particle image velocimetry (PIV) volumes or holographic PIV volumes in 3D or from planar PIV images in 2D suitably pre-processed to satisfy the conditions required as per the analysis presented here. The underlying theory has been applied to 2D and 3D Gaussian turbulence velocity fields to illustrate its ability in determining mean velocities, standard deviations of the turbulent velocity fluctuations and correlation coefficients between the turbulent velocity fluctuation components. These examples have demonstrated that the mean velocity can be estimated to very high accuracy, i.e. to better than 1% even when estimating the 2D and 3D JPDF with the simplified equation that does not account for particle size. The turbulence velocity fluctuations through their standard deviations can be measured with a typical error of 1.5% and the correlation coefficients with a typical error of 2.5% when estimating the JPDF with the result that accounts for the particle size. This is the first technique that allows the estimation of 3C-3D turbulent velocity statistics via the direct measurement of the JPDF without any detrimental effects due to the high values of velocity gradients that are typically encountered in turbulent shear flows because it is not restricted by the requirement of uniform velocity within the measurement volume.

Comparison of Holographic and Tomographic Particle-Image Velocimetry Turbulent Channel Flow Measurements

Based on velocity measurements of a fully developed turbulent channel flow, the methods of holographic and tomographic particle-image velocimetry (PIV) are compared. The emphasis of this comparison is on the measurement of time-dependent three-dimensional small-scale flow structures, i.e., structures at a characteristic length on the order of the Taylor scale since such flow patterns can be hardly captured by any two-dimensional experimental technique. The findings show that the holographic PIV method is useful to measure flow patterns in larger volumes whereas the tomographic PIV should be used to resolve three-dimensional small-scale structures.

Coal powder measurement by digital holography with expanded measurement area

The field of view of digital in-line holography for flow field diagnostics is restricted to a small volume due to the finite size and the low spatial resolution of the available CCD. Expansion of the measurement cross section of digital holographic particle image velocimetry was investigated with a lens-based holography configuration. By sampling the chirp signal in the center lobe completely and undersampling the chirp signal in the second- and higher-order lobes by a magnified virtual recording plane produced by an imaging camera lens, the field of view is expanded. Simulation results show that the three-dimensional (3D) location and size of the relatively large particle can be reconstructed with good accuracy. A digital holographic particle image velocimetry system was established for coal particle flow field diagnostics. Compared with the lensless configuration, the field of view of the digital holography system was enlarged 1.9 times, up to 2.78 cm × 2.78 cm × 3 cm. The 3D location, size distribution, and the 3D vector field of coal powder were obtained. The results show that the application of digital in-line holography to measure large particle flow field is feasible.

Stretching of turbulent eddies generates cavitation near a stagnation point

Cavitation inherently occurs in regions with low pressure. However, in recent experiments involving a high-speed bubbly jet impinging on a blunt body, we have observed rapid growth and stretching of bubbles near the stagnation point. The analysis of holographic particle image velocimetry data shows that turbulent eddies which originated from the jet are being stretched by the strain field in the vicinity of the stagnation point to form powerful vortices. Their strength and size along with the local strain rate are sufficient for decreasing the pressure in the vortex core below the vapor pressure, explaining the occurrence of cavitation in this region.

Measurement of inertial particle clustering and relative velocity statistics in isotropic turbulence using holographic imaging

We present the first measurements of relative velocity statistics of inertial particles in a homogeneous isotropic turbulent flow with three-dimensional holographic particle image velocimetry (holographic PIV). From the measurements we are able to obtain the radial relative velocity probability density function (PDF) conditioned on the interparticle separation distance, for distances on the order of the Kolmogorov length scale. Together with measurements of the three-dimensional radial distribution function (RDF) in our turbulence chamber, these statistics, in principle, can be used to determine interparticle collision rates via the formula derived by Sundaram and Collins (1997). In addition, we show temporal development of the RDF, which reveals the existence of an extended quasi-steady-state regime in our facility. Over this regime the measured two-particle statistics are compared to direct numerical simulations (DNS) with encouraging qualitative agreement. Statistics at the same Reynolds number but different Stokes numbers demonstrate the ability of the experiment to correctly capture the trends associated with particles of different inertia. Our results further indicate that even at moderate Stokes numbers turbulence may enhance collision rates significantly. Such experimental investigations may prove valuable in validating, guiding and refining numerical models of particle dynamics in turbulent flows.

Particle image identification and correlation analysis in microscopic holographic particle image velocimetry

This paper discusses the different analysis methods used in holographic particle image velocimetry to measure particle displacement and compares their relative performance. A digital holographic microscope is described and is used to record the light scattered by particles deposited on cover slides that are displaced between exposures. In this way, particle position and displacement are controlled and a numerical data set is generated. Data extraction using nearest neighbor analysis and correlation of either the reconstructed complex amplitude or intensity fields is then investigated.

Stereoscopic PIV on multiple color-coded light sheets and its application to axial flow in flapping robotic insect wings

Non-scanning volume flow measurement techniques such as 3D-PTV, holographic and tomographic particle image velocimetry (PIV) permit reconstructions of all three components (3C) of velocity and vorticity vectors in a fluid volume (3D). In this study, we present a novel 3D3C technique termed Multiple-Color-Plane Stereo Particle-Image-Velocimetry (color PIV), which allows instantaneous measurements of 3C velocity vectors in six parallel, colored light sheets. We generated the light sheets by passing white light of two strobes through dichroic color filters and imaged the slices by two 3CCD color cameras in Stereo-PIV configuration. The stereo-color images were processed by custom software routines that sorted each colored fluid particle into one of six gray-scale images according to its hue, saturation, and luminance. We used conventional Stereo PIV cross-correlation algorithms to compute a 3D planar vector field for each light sheet and subsequently interpolated a volume flow map from the six vector fields. As a first application, we quantified the wake and axial flow in the vortical structures of a robotic insect (fruit fly) model wing. In contrast to previous findings, the measured data indicate strong axial flow components on the upper wing surface, including axial flow in the leading-edge vortex core. Collectively, color PIV is robust against mechanical misalignments, avoids laser safety issues, and computes instantaneous 3D vector fields in a fraction of the time typical for other 3D systems. Color PIV might thus be of value for volume measurements of highly unsteady flows.

Dynamics of Flow Structures and Transport Phenomena, 1. Experimental and Numerical Techniques for Identification and Energy Content of Flow Structures

Most chemical engineering equipment is operated in the turbulent regime. The flow patterns in this equipment are complex and are characterized by flow structures of wide range of length and time scales. The accurate quantification of these flow structures is very difficult and, hence, the present design practices are still empirical. Abundant literature is available on understanding of these flow structures, but in very few cases efforts have been made to improve the design procedures with this knowledge. There have been several approaches in the literature to identify and characterize the flow structures qualitatively as well as quantitatively. In the last few decades, several numerical as well as experimental methods have been developed that are complementary to each other with the onset of better computational and experimental facilities. In the present work, the methodologies and applications of various experimental fluid dynamics (EFD) techniques (namely, point measurement techniques such as hot film anemometry, laser Doppler velocimetry, and planar measurement techniques such as particle image velocimetry (PIV), high speed photography, Schlieren shadowgraphy, and the recent volume measurement techniques such as holographic PIV, stereo PIV, etc.), and the computational fluid dynamics (CFD) techniques (such as direct numerical simulation (DNS) and large eddy simulation (LES)) have been discussed. Their chronological developments, relative merits, and demerits have been presented to enable readers to make a judgment as to which experimental/numerical technique to adopt. Also, several notable mathematical quantifiers are reviewed (such as quadrant technique, variable integral time average technique, spectral analysis, proper orthogonal decomposition, discrete and continuous wavelet transform, eddy isolation methodology, hybrid POD-Wavelet technique, etc.). All three of these tools (computational, experimental, and mathematical) have evolved over the past 6-7 decades and have shed light on the physics behind the formation and dynamics of various flow structures. The work ends with addressing the present issues, the existing knowledge gaps, and the path forward in this field.

Optical diffraction tomography in fluid velocimetry: the use of a priori information

Holographic particle image velocimetry (HPIV) has been used successfully to make three-dimensional, three-component flow measurements from holographic recordings of seeded fluid. It is clear that measurements can only be made in regions that contain particles, but simply adding more seeding results in poor quality images due to the effects of multiple scattering. In this paper, we describe optical diffraction tomography (ODT) techniques and consider its use as a means to overcome the problems of multiple scattering in HPIV. We consider several approaches to tomographic reconstruction that are essentially based on linear and nonlinear combinations of holographic reconstructions of the scattered fields observed under varied illuminating conditions. We show that linear reconstruction provides images of highest fidelity, but none of the methods properly accounts for the effects of multiple scattering. We go on to consider nonlinear optimization methods in ODT that attempt to minimize the error between the scattered field computed from an estimate of the particle distribution and that measured in practice. We describe an optimization procedure that is based on the conjugated gradient method (CGM) that makes use of a priori information (the size and refractive index of the seeding particles) to effectively reduce the problem to that of finding the set of particle locations. Some 2D numerical experiments are computed and some promising results are shown.

Digital holographic particle image velocimetry: eliminating a sign-ambiguity error and a bias error from the measured particle field displacement

In a typical digital holographic PIV recording set-up, the reference beam and the object beam propagate towards the recording device along parallel axes. Consequently, in a reconstructed volume, the real image of the recorded particle field and the speckle pattern that originates from the virtual image of the recorded particle field overlap. If the recorded particle field experiences a longitudinal displacement between two recordings and if the two reconstructed complex-amplitude fields are analysed with a 3D correlation analysis, two separate peaks appear in the resulting correlation-coefficient volume. The two peaks are located at opposite longitudinal positions. One peak is related to the displacement of the real image and the other peak is related to the displacement of the speckle pattern that originates from the virtual image. Because both peaks have a comparable height, a sign ambiguity appears in the longitudinal component of the measured particle field displacement. Additionally, the measured longitudinal particle field displacement suffers from a bias error. The sign ambiguity and the bias error can be suppressed by applying a threshold operation to the reconstructed amplitude. The sign ambiguity, characterized by Γ, is suppressed by more than a factor of 60. The dimensionless bias error is reduced by a factor of 5.

Digital holographic particle validation via complex wave

The inability to distinguish between particle images and noise in holographic reconstruction of dense particle fields hampers the advancement of holographic particle diagnostic techniques including holographic particle image velocimetry. We developed a method to separate particles from the noise by unlocking a unique particle signature in the complex reconstructed field. This complex-wave signature is present in digital particle holograms recorded at any scattering angle. Simulations of single and multiple particle holograms, as well as preliminary laboratory particle-field experiments, not only demonstrated the existence of the particle signature but also evaluated its ability to remove noise. Regardless of particle seeding density, scattering angle of hologram recording and particle size range, the particle identification/validation routine consistently provides >50% removal of "bad" particles and <8% of good particles.

Holographic Particle Image Velocimetry and its Application in Engine Development

This paper reviews Holographic Particle Image Velocimetry (HPIV) as a means to make three-component velocity measurements throughout a three-dimensional flow-field of interest. A simplified treatment of three-dimensional scalar wave propagation is outlined and subsequently used to illustrate the principles of complex correlation analysis. It is shown that this type of analysis provides the three-dimensional correlation of the propagating, monochromatic fields recorded by the hologram. A similar approach is used to analyse the Object Conjugate Reconstruction (OCR) technique to resolve directional ambiguity by introducing an artificial image shift to the reconstructed particle images. An example of how these methods are used together to measure the instantaneous flow fields within a motored Diesel engine is then described.