Compressed holographic particle tracking velocimetry for microflow measurements

Optical Review - We have established a holographic particle tracking velocimetry (HPTV) technique based on compressed sensing (CS) for measurement of the velocity field of microflows in this study....     

Study of particle tracking algorithms based on neural networks for stereoscopic tracking velocimetry

Stereoscopic-tracking velocimetry can offer an excellent potential for continuously monitoring three-dimensional flow fields for all three-component velocities in near-real-time. Requiring only the deployment of two solid-state cameras with directional freedom in test-section illumination and observation, the system can be built to be compact and robust. For flow velocimetry measurement, increasing the number density in particle seeding is much desirable for maximizing spatial resolution, that is, number of velocity data points of the captured field. The challenge, however, is how to successfully track numerous crisscrossing particles with speed and reliability. In our approach, the task of particle tracking is converted to an optimization problem for which neural networks are applied. Here we present the design and development of the neural networks for particle tracking as well as the investigation results based on both computer simulations and real experiments. The approach appears to be appropriate for near-real-time velocity monitoring, being able to provide reliable solutions achieved by the massive parallel-processing power of the neural networks.     

Processing of three-dimensional particle tracking velocimetry data

There is a growing necessity to develop advanced data analysis methods capable of dealing with three dimensional data sets, both scalar and vector quantities. In fluid mechanics there are being developed particle tracking methods which allow the determination of the three dimensional spatial distribution of velocity vectors. Most of these methods yield data which is nonuniformly distributed in space causing severe problems with data analyses. In this paper a versatile interpolation method is presented which allows the specification of the data field onto an arbitrary grid. Moreover, the local partial derivatives can be evaluated from the local functional representation which is continuous up to the second derivative throughout the region of interest. The errors associated with the procedure are illustrated relative to the data density and can be expected to be less than 1% for velocity vector data and less than 5% for vorticity.     

Particle filtering for passive fathometer tracking

Seabed interface depths and fathometer amplitudes are tracked for an unknown and changing number of sub-bottom reflectors. This is achieved by incorporating conventional and adaptive fathometer processors into sequential Monte Carlo methods for a moving vertical line array. Sediment layering information and time-varying fathometer response amplitudes are tracked by using a multiple model particle filter with an uncertain number of reflectors. Results are compared to a classical particle filter where the number of reflectors is considered to be known. Reflector tracking is demonstrated for both conventional and adaptive processing applied to the drifting array data from the Boundary 2003 experiment. The layering information is successfully tracked by the multiple model particle filter even for noisy fathometer outputs.     

A novel particle tracking velocimetry method for complex granular flow field

Particle tracking velocimetry(PTV) is one of the most commonly applied granular flow velocity measurement methods. However, traditional PTV methods may have issues such as high mismatching rates and a narrow measurement range when measuring granular flows with large bulk density and high-speed contrast. In this study, a novel PTV method is introduced to solve these problems using an optical flow matching algorithm with two further processing steps. The first step involves displacement correction, which is used to solve the mismatching problem in the case of high stacking density.The other step is trajectory splicing, which is used to solve the problem of a measurement range reduction in the case of high-speed contrast The hopper flow experimental results demonstrate superior performance of this proposed method in controlling the number of mismatched particles and better measuring efficiency in comparison with the traditional PTV method.     

Particle imaging velocimetry measurements in a heart simulator

In vitro experiments are often unable to reproduce all the complexities of biological flows observed in vivo. The in vitro models are often rigid, use Newtonian fluids, and/or some ideal geometry tested under ideal physiological parameters. The study presented in this article describes the in vitro assessment of mitral prosthetic heart valves in a setup able to simulate the pulsatile blood flow in a model of the left heart with moving walls. The specific laboratory mockup built for these experiments consists in a Dual Activation Simulator (DAS) that provides a realistic simulation of the atrial and ventricular flow in anatomically shaped silicone models cavities. This mockup, initially designed for ultrasonic velocity measurements took recently advantage of the use of particle image velocimetry. We present here some aspects of flow visualization and phase averaged two-dimensional PIV measurements which can provide new insight in the interaction between the flow dynamics and the heart valves.     

Particle image velocimetry analysis of IC engine in-cylinder flows

This paper discusses the use of particle image velocimetry for measuring in-cylinder flows in multi-valve IC engines. The techniques and their limitations are discussed with special reference to the study of large-scale flow structures in a four valve optical IC engine exhibiting significant barrel swirl. Examples of velocity vector maps derived by digital autocorrelation are presented for a range of crank angles through the induction and compression strokes from both horizontal and vertical measurement planes. The evident strengths and limitations of the current technique for in-cylinder applications are discussed with respect to spatial resolution, velocity gradients and dynamic range. Recent developments for overcoming the limitations are also reviewed.     

Particle filtering for dispersion curve tracking in ocean acoustics

A particle filtering method is developed for dispersion curve extraction from spectrograms of broadband acoustic signals propagating in underwater media. The goal is to obtain accurate representation of modal dispersion which can be employed for source localization and geoacoustic inversion. Results are presented from the application of the method to synthetic data, demonstrating the potential of the approach for accurate estimation of waveguide dispersion characteristics. The method outperforms simple time-frequency analysis providing estimates that are very close to numerically calculated dispersion curves. The method also provides uncertainty information on modal arrival time estimates, typically unavailable when traditional methods are used.     

Particle image velocimetry measurements of wave-current interaction in a laboratory flume

The hydrodynamics of wave-current interaction is of interest to those concerned with marine and offshore structures. In particular the fluid loading characteristic may be radically altered in a sea state consisting of a mean current flow mixed with freely propagating gravity waves.

The present paper describes water flume experiments, using Particle Image Velocimetry (PIV), executed to examine hydrodynamics of wave-current interaction. A variety of wave and current conditions were investigated to determine the major influences on the combined flow.

This paper describes the experimental procedures used to obtain simultaneous measurements of the resulting wave velocity vectors over an extended region of the wave. It also describes how the directional ambiguity inherent in the basic PIV method was resolved by ‘pulse tagging’ technique.

Velocity vectors under waves at various phase points for different current and wave conditions are presented and compared in some cases with measurements derived using Laser Doppler Anemometry (LDA). The resulting velocity vectors are used to estimate how the mutual interaction, between wave and current, effect the calculation of structural loads using Morrison's equation.     

A method to determine the measurement volume for particle shadow tracking velocimetry (PSTV)

Journal of Visualization - A method to determine the depth of detection (DOD) for particle shadow tracking velocimetry (PSTV) is presented. In contrast with other image-based velocimetry...     

Defocus and binocular vision based stereo particle pairing method for 3D particle tracking velocimetry

We propose a new method, based on the depth-from-defocus technique and binocular vision, for solving the stereo particle pairing problem in 3D particle tracking velocimetry (PTV). Firstly, the apparent particle depth is measured with a single camera, using the depth-from-defocus technique. Secondly, a strict mathematical model of the particle-to-particle correspondence relationship between the left and right images, taking into account the refractions at the interfaces in the optical path, is presented, with the assumption that the apparent particle depth is measured. Thirdly, based on the apparent particle depth and particle-to-particle correspondence relationship, the epipoplar line is truncated into a short line segment by cutting off, where the apparent particle depth extends beyond its estimated range. For the first time, the range of the blur circle radius is employed as an additional stereo particle pairing constraint. Finally, the optimal pairing particle is selected by applying the epipolar line segment and blur circle radius constraints. The experimental results show that the rate of correct pairing is significantly improved compared with the epipolar line nearest neighbor analysis, especially when the particle density is increasing.     

Particle image velocimetry: Estimation of measurement confidence at low seeding densities

In order to optimise the spatial resolution of particle image velocimetry, it is often necessary to take measurements from regions of the photographic record which contain few particle images. If Young's fringe analysis is used in these cases, the observed fringe pattern is confused by extraneous spatial frequency components or speckle noise. If spatial correlation analysis is employed, spurious correlation peaks occur. In this paper we introduce a definition of signal to noise ratio appropriate to particle image velocimetry and investigate the statistical variation of this ratio as a function of the seeding particle size and concentration.     

Particle image velocimetry in aerodynamics: Technology and applications in wind tunnels

Particle image velocimetry (PIV) is increasingly used for aerodynamic research and development. The PIV technique allows the recording of a complete flow velocity field in a plane of the flow within a few microseconds. Thus, it provides information about unsteady flow fields, which is difficult to obtain with other experimental techniques. The short acquisition time and fast availability of data reduce the operational time, and hence cost, in large scale test facilities. Technical progress made in the last years allowed DLR to develop a reliable, modular PIV system for use in industrial wind tunnels. The features of this system are summarized and results of recent PIV applications are presented.     

Particle tracking to reveal gelation of hectorite dispersions

Passive microrheological techniques using particle tracking have been developed for the study of the gelation of hectorite suspensions. By following the Brownian motion of the particles, it is possible to determine the increasing caging of the particles with time, as the system gels. Since only the Brownian motion is followed, the gelation process itself should not be affected by the measurement. As gelation proceeds the increasing heterogeneity of the particle environments can be monitored by a variety of measures, including kurtosis. An effective viscosity can be extracted from the measurements and used to indicate the gelation process.     

Particle tracking microrheology of gel-forming amyloid fibril networks

Microrheology is a technique that is increasingly used to investigate the local viscoelastic properties of complex fluids non-invasively, by tracking the motion of micron-sized probe spheres. In this work, passive Particle Tracking Microrheology (PTM) is used to study network formation in the milk protein -lactoglobulin at 80 ^° C and p H 2. In these conditions the protein aggregates to form thread-like structures known as amyloid fibrils, which can further aggregate into elastic networks. Using PTM, gels were observed to form at significantly lower concentrations than determined by bulk rheometry, where the oscillatory shear forces may disrupt either fibril or network formation. During incubation, the Mean Square Displacement (MSD) of the probe particles exhibited time-cure superposition, allowing the critical relaxation exponent to be calculated as ∼ 0.63 , consistent with other biopolymer gels. Combined with the gel-like appearance of the complex modulus at long incubation times, this confirms that a true gel is forming, with physical or chemical crosslinks forming between the fibrils, refining the conclusions of other workers in the field.     

Particle swarm optimization applied to automatic lens design

This paper describes a novel application of Particle Swarm Optimization (PSO) technique to lens design. A mathematical model is constructed, and merit functions in an optical system are employed as fitness functions, which combined radiuses of curvature, thicknesses among lens surfaces and refractive indices regarding an optical system. By using this function, the aberration correction is carried out. A design example using PSO is given. Results show that PSO as optical design tools is practical and powerful, and this method is no longer dependent on the lens initial structure and can arbitrarily create search ranges of structural parameters of a lens system, which is an important step towards automatic design with artificial intelligence.     

Particle tracking simulation in the CSRe stochastic cooling system

A stochastic cooling system is under design and construction at HIRFL-CSRe(Heavy Ion Research Facility in Lanzhou- experimental Cooling Storage Ring), with the aim of cooling secondary particles produced at HIRFL-RIBLL2(2nd Radioactive Ion Beam Line in Lanzhou).The optical layout of CSRe has been optimized to meet the requirements of a stochastic cooling system.In this paper, a particle tracking method is used to investigate both transverse and longitudinal cooling on the basis of the modified optical layout, demonstrating how it can be used to optimize stochastic cooling parameters.Simulation results indicate that the particle tracking method is an innovative and reasonable method to study stochastic cooling.It also has the advantage of discovering the influence of Twiss parameters at the pickups and kickers, which will be explored in further studies.     

Particle filter based visual tracking with multi-cue adaptive fusion

To improve the robustness of visual tracking in complex environments such as: cluttered backgrounds, partial occlusions, similar distraction and pose variations, a novel tracking method based on adaptive fusion and particle filter is proposed in this paper. In this method, the image color and shape cues are adaptively fused to represent the target observation; fuzzy logic is applied to dynamically adjust each cue weight according to its associated reliability in the past frame; particle filter is adopted to deal with non-linear and non-Gaussian problems in visual tracking. The method is demonstrated to be robust to illumination changes, pose variations, partial occlusions, cluttered backgrounds and camera motion for a test image sequence.     

基于动态特征融合的粒子滤波目标跟踪算法

提出一种基于动态特征融合的粒子滤波目标跟踪算法。选择具有互补性的灰度直方图和梯度直方图特征共同描述目标模型,然后在目标跟踪过程中,根据特征对目标和背景的区分程度动态地调整每个特征的置信度,对目标模型进行在线动态建模和更新,从而提高目标模型描述的准确度,并进一步提高粒子滤波算法的跟踪精度。实验结果表明:在对典型场景下的目标跟踪过程中,提出的算法比单独使用一种特征的粒子滤波算法具有更高的跟踪精度和更稳定可靠的跟踪性能。