Three-dimensional Particle Tracking Velocimetry Research Articles

Effect of the aspect ratio on the dynamics of air bubbles within Rayleigh–Bénard convection

Laboratory experiments and numerical simulations were performed to quantify the effect of the aspect ratio, Γ, in the dynamics of air bubbles within turbulent Rayleigh–Bénard (RB) convection. We explored four scenarios defined by Γ=1.25, 1.5, 2, and 2.5 under Rayleigh numbers ranging from 2.0×109 to 1.6×1010. Continuous 1-mm bubbles were released at two locations from the bottom along the roll path. Three-dimensional particle tracking velocimetry was used to track a large number of bubbles and determine features of the trajectories and pair dispersion, R2(t), for various initial separations, rp within H/10≤rp≤5H/10; here, H is the height. The R2(t) of the bubbles within a quiescent medium was included for reference. Characterization of the bubble streams, namely, the center of mass (Lc), mean deviation (Rc) to Lc, vertical (vz) and lateral (vL) velocities, and their ratios reveal the strong modulation of the roll structure and Γ. In particular, Lc exhibited an approximately symmetric distribution around the maximum, which occurred at the middle height only in the Γ=1.25 case. Maximum Lc was near the wall top with the highest aspect ratio. However, Rc did not vary substantially among the cases. Bubbles' lateral pair dispersion RL2 shows correlated trends with Γ, particularly at large initial separations and times, whereas the vertical pair dispersion is mainly dominated by buoyancy. The RL2 decreased as Γ increased. It indicates the effect of different-sized roll structures modulated by Γ. In general, R2 embodies distinct features of Γ-modulated bubble dynamics in RB convection.

Lagrangian coherent track initialization

Advances in time-resolved three-dimensional Particle Tracking Velocimetry (4D-PTV) techniques have consistently revealed more accurate Lagrangian particle motions. A novel track initialization technique as a complementary part of 4D-PTV, based on local temporal and spatial coherency of neighbor trajectories, is proposed. The proposed Lagrangian Coherent Track Initialization (LCTI) applies physics-based Finite Time Lyapunov Exponent (FTLE) to build four frame coherent tracks. We locally determine Lagrangian coherent structures among neighbor trajectories by using the FTLE boundaries (i.e., ridges) to distinguish the clusters of coherent motions. To evaluate the proposed technique, we created an open-access synthetic Lagrangian and Eulerian dataset of the wake downstream of a smooth cylinder at a Reynolds number equal to 3900 obtained from three-dimensional direct numerical simulation. Performance of the proposed method based on three characteristic parameters, temporal scale, particle concentration (i.e., density), and noise ratio, showed robust behavior in finding true tracks compared to the recent initialization algorithms. Sensitivity of LCTI to the number of untracked and wrong tracks is also discussed. We address the capability of using the proposed method as a function of a 4D-PTV scheme in the Lagrangian particle tracking challenge. We showed that LCTI prevents 4D-PTV divergence in flows with high particle concentrations. Finally, the LCTI behavior was demonstrated in a jet impingement experiment. LCTI was found to be a reliable tracking tool in complex flow motions, with a strength revealed for flows with high velocity and acceleration gradients.

Kalman filtering approach to particle track filtering and track uncertainty quantification for 3D PTV measurement

Three-dimensional Particle Tracking Velocimetry (3D-PTV) is a non-invasive flow measurement technique that computes the velocity field by reconstructing 3D particle positions of individual tracer particles and by subsequently tracking those positions. The particle velocity measurement accuracy depends on the faithful reconstruction of 3D particle positions. The complex measurement chain in 3D-PTV involves several steps, from calibration to 3D position reconstruction and particle position tracking, each having its own source of error. Additionally, higher seeding density increases the uncertainty in particle reconstruction and tracking, which in turn, increases the noise in the estimated tracks. A noisy track decreases the measurement accuracy and amplifies any noise in the PTV-derived quantities of interest, which includes acceleration, pressure and vorticity. Thus, track filtering techniques are critical in a 3D-PTV measurement. Track fitting using polynomial functions, filtering methods adopted from signal processing and object tracking are among the well-established techniques used to achieve smooth position, velocity estimates from reconstructed particle trajectories. The Kalman filter is one such filtering technique that is widely used in various applications. The strength of the Kalman filter lies in its ability to perform noise reduction that is informed by existing physical models and the uncertainty estimates of recorded measurements. However, the measurement uncertainty input to the Kalman filter needs to be known at priori, which in many cases may not be available or could be difficult to estimate. In the literature on Kalman filters and their variants applied to 2D-PIV/PTV, the position uncertainty data fed to the filter is either user-defined or estimated based on global noise levels in the PTV measurements. But instantaneous position and velocity uncertainty quantification for individual particle positions/tracks has been challenging in the 3D PTV community. Recent work by Bhattacharya and Vlachos (2020) provides an estimate of the uncertainty in the reconstructed particle positions for a 3D PTV measurement. This position uncertainty estimate dynamically updates the filter gain for each track and enables the evaluation of the performance of the Kalman filter in 3D PTV track filtering.

Three-Dimensional Particle Tracking Velocimetry using a Single Time-of-Flight Camera

Time of Flight (ToF) cameras are a type of range-imaging camera that provides three-dimensional scene information from a single camera. This paper assesses the ability of ToF technology to be used for threedimensional particle tracking velocimetry (3D-PTV). Using a commercially available ToF camera various aspects of 3D-PTV are considered, including: minimum resolvable particle size, environmental factors (reflections and refractive index changes) and time resolution. Although it is found that an off-the-shelf ToF camera is not a viable alternative to traditional 3D-PTV measurement systems, basic 3D-PTV measurements are shown with large (6mm) particles in both air and water to demonstrate future potential use as this technology develops. A summary of necessary technological advances is also discussed.

In situ color-to-depth calibration: toward practical three-dimensional color particle tracking velocimetry

We propose a seeding particle-based color-to-depth calibration methodology for three-dimensional color particle tracking velocimetry (3D color PTV) using a single camera and volumetric rainbow gradient illumination. The use of sheet-color illumination from a liquid crystal display projector enables in situ calibration, namely the color-to-depth relationships of particles seeded in a fluid are determined without inserting any calibration equipment or taking a different optical setup. That is, in this methodology, the calibration and application can be performed using the same optical configuration, and only the digital illumination patterns need to be changed. Adopting this calibration allows evaluating actual color-to-depth relationships of the particles in measurements. The calibration is conducted regarding the relationship between spatially distributed particle colors and their depth coordinates by support of an artificial neural network. By combining conventional PTV with the depth estimated by the color, particle trajectories in 3D real space can be reconstructed from the calibration. The performance of the proposed method was evaluated using a rotating flow in a cylindrical tank by comparing its results with the flow fields measured by conventional particle image velocimetry. Good accordance in the comparison at the highly 3D flow suggests the applicability of the present methodology for various flow configurations.

Sound pressure level spectrum analysis by combination of 4D PTV and ANFIS method around automotive side-view mirror models

This paper proposes a data augmentation method based on artificial intelligence (AI) to obtain sound level spectrum as predicting the spatial and temporal data of time-resolved three-dimensional Particle Tracking Velocimetry (4D PTV) data. A 4D PTV has used to measure flow characteristics of three side mirror models adopting the Shake-The-Box (STB) algorithm with four high-speed cameras on a robotic arm for measuring industrial scale. Helium filled soap bubbles are used as tracers in the wind tunnel experiment to characterize flow structures around automobile side mirror models. Full volumetric velocity fields and evolution of vortex structures are obtained and analyzed. Instantaneous pressure fields are deduced by solving a Poisson equation based on the 4D PTV data. To predict spatial and temporal data of velocity field, artificial intelligence (AI)-based data prediction method has applied. Adaptive Neural Fuzzy Inference System (ANFIS) based machine learning algorithm works well to find 4D missing data behind the automobile side mirror model. Using the ANFIS model, power spectrum of velocity fluctuations and sound level spectrum of pressure fluctuations are successfully obtained to assess flow and noise characteristics of three different side mirror models.

Full-Span Topology of Trailing-Edge Separation at Different Angles of Attack

The velocity field over a two-dimensional wing at Reynolds number of 672,000 was investigated to characterize the three-dimensional topology and evolution of the separate flow with variation of the angle of attack. Planar particle image velocimetry over the full span of the wing demonstrated that with increasing angle of attack, isolated pockets of backflow, which appeared near the trailing edge, merged and formed an asymmetric stall cell at angle of attack of 9.7°. The asymmetry was mainly associated with the dissimilar boundary layers developed on the wind tunnel walls at the spanwise ends of the wing. Secondary structures were also observed between the stall cell and the spanwise end. The stall cell topology was characterized using large-scale three-dimensional particle tracking velocimetry measurements using helium-filled soap bubbles. The results showed that the separation bubble had a small wall-normal height with two wall-normal counter-rotating vortices extended up to the edge of the separation bubble. In addition, the investigations demonstrated that vortex generators can induce a symmetric stall cell by removing the secondary structures and isolating the stall cell from the flows at the spanwise ends.

A novel single-camera approach to large-scale, three-dimensional particle tracking based on glare-point spacing

A novel method for three-dimensional particle tracking velocimetry (PTV) is proposed that enables flow measurements in large volumes [ $$V=\mathcal {O}(10$$ m $${^3}$$ )] using a single camera. Flow is seeded with centimeter-sized soap bubbles, when combined with suitable illumination, produce multiple glare points. The spacing between the two brightest glare points for each bubble is then utilized to reconstruct its depth. While the use of large soap bubbles comes at the expense of non-Stokesian behaviour, the excellent ray optics allow for large volume illumination when coupled with for instance pulsed LED banks. Possible error sources and the out-of-plane accuracy are discussed before the feasibility of the method is tested in an industrial-scale wind tunnel facility (test section of cross section 9.1 m $$\times$$ 9.1 m). In particular, the vortical structure in the wake of a 30%-scale tractor-trailer model at a $$9^{\circ }$$ yaw angle is captured in a 4.0 m $$\times$$ 1.5 m $$\times$$ 1.5 m measurement volume. Long tracks of up to 80 time steps are extracted in three-dimensional space via a single perspective. The successful proof-of-concept confirms the potential of the novel approach for three-dimensional measurements in volumes of industrial scale.

A spatial-temporal algorithm for three-dimensional particle tracking velocimetry using two-view systems

In the present study, a novel temporal three-dimensional particle tracking velocimetry (3D PTV) algorithm for flow measurements with only two views is developed and validated with synthetic particles. The spatial information in image and object spaces, as well as the temporal predictions, are strongly coupled to improve the particle tracking accuracy. A well-designed cost function, simultaneously penalizing the reconstruction and tracking processes, is minimized to determine the most reliable traces. The algorithm shows a correctness over 98% up to 0.0273 ppp (particles per pixel) when using ideal synthetic particle positions, which is superior to several artificial intelligence methods. Moreover, an improved particle identification algorithm is proposed to handle overlapped particles and reduce the error introduced into the 3D PTV scheme. The algorithm adopts a particle position shifting process to tackle the correct particle numbers iteratively, which shows better performance than some other methods. A comparative study indicates that particle identification accuracy has a significant effect on the subsequent 3D reconstruction and tracking processes. The 3D PTV and particle identification algorithms show good consistencies under two types of flow conditions: a homogeneous isotropic turbulent flow and a vortex ring flow. Comparing with multiple-view setups, two-view systems are more compact and cost-effective, especially in conditions requiring high-speed cameras. With the newly established algorithms, a two-view system is now able to handle higher particle-seeding densities and thus can resolve higher spatial resolutions, which is significant for applications in turbulent flow and particle motion measurements.

Lagrangian turbulence in the woods

Abstract

Volumetric measurement of turbulence and flow topology in an asymmetric diffuser

Three-dimensional particle tracking velocimetry is used to characterize the time-resolved turbulent flow in an asymmetric diffuser. The measurements cover the full diffuser and show that the separated flow consists of large-scale structures with a Strouhal number smaller than 0.03. Three large vortices are identified; two vortices originate from the wall with the largest diverging angle and the third vortex from the neighboring diverging wall.

Free fall of homogeneous and heterogeneous cones

The late stage of the freefall of homogeneous and heterogeneous cones and the induced flow are studied using three-dimensional particle tracking velocimetry and three-dimensional particle image velocimetry. Results showed four distinct patterns modulated by the degree of heterogeneity and specific gravity. They included straight fall, sinusoidal-like trajectories, inclined translations with large rotations, and tumbling followed by an irregular motion.

A Novel Estimation Approach of Pressure Gradient and Haemodynamic Stresses as Indicators of Pathological Aortic Flow Using Subvoxel Modelling.

The flow downstream from aortic stenoses is characterised by the onset of shear-induced turbulence that leads to irreversible pressure losses. These extra losses represent an increased resistance that impacts cardiac efficiency. A novel approach is suggested in this study to accurately evaluate the pressure gradient profile along the aorta centreline using modelling of haemodynamic stress at scales that are smaller than the typical resolution achieved in experiments. We use benchmark data obtained from direct numerical simulation (DNS) along with results from in silico and in vitro three-dimensional particle tracking velocimetry (3D-PTV) at three voxel sizes, namely 750 μm, 1mm and 1.5mm. A differential equation is derived for the pressure gradient, and the subvoxel-scale (SVS) stresses are closed using the Smagorinsky and a new refined model. Model constants are optimised using DNS and in silico PTV data and validated based on pulsatile in vitro 3D-PTV data and pressure catheter measurements. The Smagorinsky-based model was found to be more accurate for SVS stress estimation but also more sensitive to errors especially at lower resolution, whereas the new model was found to more accurately estimate the projected pressure gradient even for larger voxel size of 1.5mm albeit at the cost of increased sensitivity at this voxel size. A comparison with other methods in the literature shows that the new approach applied to in vitro PTV measurements estimates the irreversible pressure drop by decreasing the errors by at least 20%. Our novel approach based on the modelling of subvoxel stress offers a validated and more accurate way to estimate pressure gradient, irreversible pressure loss and SVS stress. We anticipate that the approach may potentially be applied to image-based in vivo, in vitro 4D flow data or in silico data with limited spatial resolution to assess pressure loss and SVS stresses in disturbed aortic blood flow.

Effect of Reynolds number on turbulent channel flow over a superhydrophobic surface

The slip boundary and the near-wall statistics of a fully developed turbulent channel flow over a superhydrophobic surface (SHS) was investigated in a low Reynolds number (Re) range. The Re was varied from 6200 to 9400, based on the bulk velocity and the full-channel height. The root-mean-square of the surface roughness, normalized by the inner flow scaling, varied from 0.26 to 0.35 with increasing Re. Time-resolved, two-dimensional particle tracking velocimetry (PTV) was used to obtain the mean velocity profile in the linear viscous sublayer. Furthermore, time-resolved three-dimensional PTV was applied to obtain the Reynolds stresses. The estimated wall shear stress showed that the drag reduction of the SHS increased slightly from 37% to 42% when Re increased. With increasing Re, the slip velocity increased linearly from 0.25 m/s to 0.34 m/s, and the slip length reduced from 97.5 μm to 69.6 µm. When normalized using inner scaling, slip velocity and length remained constant with increasing Re. The mean velocity of the SHS demonstrated a log-law with the universal von Kármán constant but shifted upward by an amount equal to the normalized slip velocity. The SHS increased the dimensional Reynolds stresses in the near-wall region and attenuated them farther away from the wall. With increasing Re, the differences between the dimensional Reynolds stresses of the smooth surface and the SHS increased. However, when Reynolds stresses were normalized using friction velocity, the Reynolds stresses of the SHS overlapped for all the investigated Re and were larger than the normalized Reynolds stresses of the smooth surface.

On the dynamics of air bubbles in Rayleigh–Bénard convection

The dynamics of air bubbles in turbulent Rayleigh–Benard (RB) convection is described for the first time using laboratory experiments and complementary numerical simulations. We performed experiments at and , where streams of 1 mm bubbles were released at various locations from the bottom of the tank along the path of the roll structure. Using three-dimensional particle tracking velocimetry, we simultaneously tracked a large number of bubbles to inspect the pair dispersion, , for a range of initial separations, , spanning one order of magnitude, namely ; here is the local Kolmogorov length scale. Pair dispersion, , of the bubbles within a quiescent medium was also determined to assess the effect of inhomogeneity and anisotropy induced by the RB convection. Results show that underwent a transition phase similar to the ballistic-to-diffusive ( -to- ) regime in the vicinity of the cell centre; it approached a bulk behavior in the diffusive regime as the distance away from the cell centre increased. At small , is shown in the diffusive regime with a lower magnitude compared to the quiescent case, indicating that the convective turbulence reduced the amplitude of the bubble’s fluctuations. This phenomenon associated to the bubble path instability was further explored by the autocorrelation of the bubble’s horizontal velocity. At large initial separations, was observed, showing the effect of the roll structure.

Iterative particle matching for three-dimensional particle-tracking velocimetry

A new evaluation scheme for double exposure three-dimensional particle-tracking velocimetry is proposed. Its main feature, a robust multi-pass matching algorithm, is presented and validated by investigating its performance when applied to a synthetic data set. To evaluate real measurement data, the approach is supplemented by an iterative triangulation scheme, in which the resulting particle positions are validated through the matching algorithm. The comparison with tomographic particle-image velocimetry data shows good agreement. The proposed algorithm allows this approach to be applied to volumetric measurements with seeding densities exceeding standard particle-tracking applications. Therefore, it can serve as a drop-in replacement for tomographic particle-image velocimetry at significantly reduced computational cost.Graphic abstract

Three-dimensional particle tracking velocimetry using shallow neural network for real-time analysis

Three-dimensional particle tracking velocimetry (3D-PTV) technique is widely used to acquire the complicated trajectories of particles and flow fields. It is known that the accuracy of 3D-PTV depends on the mapping function to reconstruct three-dimensional particles locations. The mapping function becomes more complicated if the number of cameras is increased and there is a liquid-vapor interface, which crucially affect the total computation time. In this paper, using a shallow neural network model (SNN), we dramatically decrease the computation time with a high accuracy to successfully reconstruct the three-dimensional particle positions, which can be used for real-time particle detection for 3D-PTV. The developed technique is verified by numerical simulations and applied to measure a complex solutal Marangoni flow patterns inside a binary mixture droplet.

基于光场成像的三维粒子追踪测速技术

基于光场成像的三维粒子追踪测速技术

Lagrangian coherent structures and entrainment near the turbulent/non-turbulent interface of a gravity current

In this paper, we employ the theory of Lagrangian coherent structures for three-dimensional vortex eduction and investigate the effect of large-scale vortical structures on the turbulent/non-turbulent interface (TNTI) and entrainment of a gravity current. The gravity current is realized experimentally and different levels of stratification are examined. For flow measurements, we use a multivolume three-dimensional particle tracking velocimetry technique. To identify vortical Lagrangian coherent structures (VLCSs), a fully automated three-dimensional extraction algorithm for multiple flow structures based on the so-called Lagrangian-averaged vorticity deviation method is implemented. The size, the orientation and the shape of the VLCSs are analysed and the results show that these characteristics depend only weakly on the strength of the stratification. Through conditional analysis, we provide evidence that VLCSs modulate the average TNTI height, consequently affecting the entrainment process. Furthermore, VLCSs influence the local entrainment velocity and organize the flow field on both the turbulent and non-turbulent sides of the gravity current boundary.

Performance analysis of the transcatheter aortic valve implantation on blood flow hemodynamics: An optical imaging-based in vitro study.

Cardiac implants may have a strong influence on the hemodynamics of the circulatory system. In this study, we aimed at investigating the impact of transcatheter aortic valve implantation (TAVI) devices on blood flow patterns that develop in the ascending aorta under physiological flow conditions in vitro. For this purpose, a noninvasive optical measurement tool, three-dimensional particle tracking velocimetry (3D-PTV), was used in a realistic compliant silicone aortic model. The performance and the influence of two TAVIs and one surgical valve on the aortic flow were investigated. Our results showed that valve design and materials may have a distinct influence on relevant hemodynamic properties, namely kinetic energy, production of turbulence, and shear stresses in the ascending aorta. All properties varied considerably between the different valve models. We found that the total aortic regurgitation composed of the closing volume, transvalvular and paravalvular leakages varied for the three valves investigated. Furthermore, peak mean kinetic energy (MKE) ranged from 61 to 116 J/m3 , whereas peak turbulent kinetic energy (TKE) ranged from 23 to 36 J/m3 . The analysis of shear showed that all the three studied devices had minimal overall risk for thrombus formation. We conclude that the characteristics and material designs of TAVI devices have strong influences on the hemodynamics in the ascending aorta.