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Particle movement in pebble bed has important applications in engineering. A fast region homogenization method based on experimental silo discharging process is proposed in this paper. It can obtain the particle information from the particle motion image, and quickly calculate the homogenization information of the region. Hough transform is applied to the image of silo unloading process in order to obtain the information of particle centroid and radius. The particle tracking velocimetry (PTV) algorithm processes two continuous images to realize particle matching. Based on the trajectories of the particle, a fast region homogenization method is developed to obtain the homogenization information of the region. By analyzing the possible relative geometric relationships between mesh elements and particles, the hash set is constructed in advance to quickly calculate the regional homogenization parameters. Compared with the traditional integral method, the calculation speed is greatly accelerated on the premise of ensuring the calculation accuracy. Finally, the particle area characteristics (average velocity and filling rate) of the near wall area and the central area of the pebble bed are compared.

This paper describes the use of a high-speed streaming camera combined with in-house image processing for real-time particle tracking velocimetry (PTV) above 1 kHz. The proposed system is evaluated by measuring the diameter and velocity of multiple free-falling droplets in a simultaneous manner. Two existing particle tracking methods are examined: median flow (MF) and fourframe best estimate (4BE). Area-limiting processing is newly added to MF and 4BE to reduce the region of interest (ROI) in which particles are detected in the next image, resulting in area-limiting MF (AMF) and area-limiting 4BE (A4BE). Except for MF, the rest three methods of AMF, 4BE, and A4BE are capable of 1-kHz real-time PTV for 1246 pixel × 600 pixel images, with 4BE and A4BE achieving even at 10 kHz for 1246 pixel × 100 pixel images. The processing times for the tracking and image preparation are measured, and the bottleneck is found to be the image acquisition and preparation, rather than the tracking. AMF achieves faster processing times than MF in all conditions, showing the effectiveness of the limited ROI, while 4BE and A4BE exhibit comparable performance. The measurement error is confirmed to be approximately 1% for the droplet velocity and diameter, demonstrating the high accuracy of the first in-situ real-time PTV exceeding 1 kHz.

Various drag models were implemented in a superquadric CFD-DEM code and validated for the simulation of spherical and ellipsoidal particles in spouted beds. The most suitable drag models were identified by comparing the predicted local particle velocity with those measured by particle tracking velocimetry (PTV). The model by Beetstra et al. is the one that best reproduces the experimental results for the spouting of spherical particles, whereas the one by Sanjeevi et al. is the most suitable for ellipsoidal irregular ones. Their capability for the prediction of key operating parameters was demonstrated in both conical and prismatic spouted beds, as they correctly predict the minimum spouting velocity (ums) and fountain height in different configurations (without draft tube and different draft tubes) for particles of different size and shape. The CFD-DEM model predicts the preferential orientation of ellipsoidal particles at each location in the bed and the influence of internal devices on this parameter, which is of the utmost importance in the design of reliable coating apparatuses in the pharmaceutical industry.

A new particle tracking velocimetry (PTV) algorithm, which has no interpolation process requirement, has been constructed. An affine transformation and a hybrid fitness function were used to obtain final vector fields. A match probability method (MPM)-based PTV algorithm was used to save calculation convergences. The constructed algorithm was tested with synthetic images using the numerical data of Taylor-Green vortex flow and experimental images for the flow of a rectangular body with Re = 5300. Results obtained by the constructed PTV algorithm were compared with those obtained by the conventional cross-correlation particle image velocimetry (PIV) and the MPM. Comparison results revealed that the constructed interpolation-free PTV (IFPTV) algorithm demonstrated better performance than the aforementioned PIV and PTV algorithms. Furthermore, the constructed PTV algorithm does not need an error removal and interpolation process, enabling easy processing in PTV calculations while providing high-resolution grid vectors.

Local scour is an important design factor for submerged weirs. This study conducted a clear-water scour experiment at a submerged weir, using the particle tracking velocimetry technique to measure ...

The Particle Tracking Velocimetry (PTV) has a wide range of applications in the field of fluid and particle flow measurement. Due to the uncertainty caused by the optimal probability in the matching algorithm, the long-term tracking of multiple particles will eventually lead to lower accuracy with increasing time. In this study, a full-field high-accuracy PTV algorithm for pebble flow measurement is developed. Based on a two-dimensional pebble flow experiment, improved matching algorithms for pebble flow is proposed. Analyzing two kinds of errors in the experimental data—unidentified centroids and misidentified centroids, two amending methods are developed. The original PTV algorithm for pebble flow reached an average accuracy of 90% under 5 different flowrates. After adopting the three-point co-circular amending method, the accuracy is increased to 98%. Finally, this value exceeds 99% when the LP polygon amending method is applied. The adaptability and stability of the algorithm have also been tested.

Spouted bed stability and operation is greatly affected by particle features. Accordingly, the hydrodynamic behaviour of conical spouted beds has been studied for fine particles differing in size and density in a wide range of inlet air flow rates. This knowledge is essential for a successful scaling up and industrial implementation of the spouted bed. Therefore, the effect air velocity and solid properties (density and size) have on local solid velocity has been ascertained in a fountain confined conical spouted bed using a borescope technique (Particle Tracking Velocimetry, P T V ) applied to several bed configurations. The results show a close relationship between the inlet air velocity and the local solid velocity, with the gas-solid contact being especially vigorous in the configurations without draft tube and with the open-sided draft tube. The solid circulation flow rate is lowest when a nonporous draft tube is used due to the low solid vertical velocities in the annulus, even at high air flow rates. Nevertheless, vertical velocities in the annular zone increase when particle size and density are increased, although these velocities are lower in the spout and fountain regions due to the higher momentum exchange required for their acceleration.

Particle distribution in the cross-section of the flighted rotating drum (FRD) is critical to the analysis of heat and mass transfer between gas and solids. In this work, the particle tracking velocimetry (PTV) method is applied to study the influence of the number of flights on the particle motion in FRDs. The drum, installed with 1, 4, 8, or 12 rectangular flights, is filled with plastic balls to 15% and operated at various rotating speeds ranging from 10 rpm to 30 rpm. The results show that the number of flights has different effects on the holdup ratio and cascading rate of single flight and active flights. With 8 and 12 flights, the FRD produces a larger and more stable particle ratio of the dilute phase. Moreover, DEM simulations agree with PTV measurements, whereas literature models show significant deviations.

A wavelet-based optical flow analysis (wOFA) method for processing background-oriented schlieren (BOS) images is presented and demonstrated on synthetic and experimental data. Optical flow is inher...

At voltages above a certain critical value, Vc ≈ 20 kT/e, a space charge layer forms near ion-selective interfaces in liquid electrolytes. Interactions between the space charge and an imposed electric field drives a hydrodynamic instability known as electroconvection. Through particle tracking velocimetry we experimentally study the structure and dynamics of the resultant electroconvective flow. Consistent with previous numerical simulations, we report that, following imposition of a sufficiently large voltage, electroconvection develops gradually as pairs of counter-rotating vortices, which nucleate at the interface between an ion-selective substrate and a liquid electrolyte. Depending on the imposed voltage and cell geometry, the vorticies grow to length scales of hundreds of micrometers. Electroconvective flows are also reported to be structured and multiscale, with the size ratio of the largest to the smallest observable vortices inversely proportional to the Debye screening length.

The unsteady flows produced over the stern of a Simple Frigate Shape 2 ship model are studied in a low-speed wind tunnel. Time-resolved particle image velocimetry (TR-PIV) measurements were perform...

To whom correspondence may be addressed. Email: wguo@magnet.fsu.edu.

We present an experimental facility for the validation of numerical simulations on atmospheric dust devils in a controlled laboratory experiment. Dust devils are atmospheric air vortices with a vertical axis, and are formed by intense solar radiation and the resulting vertical temperature gradient. The structure of a typical dust devil is dominated by a radial inflow near the surface and a vertical upward flow within the vortex. These vortices have been studied in recent years using field observations, in situ measurements, and large-eddy simulation (LES). Field tests suffer from the limited area and their unpredictable behavior, while the LES approach cannot resolve the dust devils well enough. Dust devil-like structures may also occur in direct numerical simulation (DNS) with a Rayleigh number of at least Ra=107$Ra=\nobreak 10^{7}$ in Rayleigh–Bénard convection, with the advantage that the structures can be resolved more precisely. In order to validate the DNS approach and provide measurement data, the airflow is measured inside of a large-scale Rayleigh–Bénard cell of similar geometry (i.e. inside the Barrel of Ilmenau) to the DNS set-up for Rayleigh numbers from Ra=106$\textit{Ra}=\nobreak 10^{6}$ to Ra=1012$\textit{Ra}=\nobreak 10^{12}$. For the measurement of the flow in a large volume, an optical measurement method is used to obtain the trajectories of single particles. Since there are no commercial systems that are suitable for such a large measurement volume, we developed our own system.

In this work, the discharging process of the binary mixture composed of sphere and sphere-paired particles in a two-dimensional silo was studied. High-speed camera and self-developed particle tracking velocimetry (PTV) program were used to capture the flow behaviors of all particles. The key parameters of mixed flow, including coordination number, horizontal displacement and mechanical energy loss in the discharge process, were highlighted. It was found that the increase of sphere-paired particles can decrease the average coordination number of particles during the discharging process. The analysis about the loss of mechanical energy and the horizontal displacement of particles indicated that sphere-paired particles preferentially squeezed out sphere particles from fast flow field above the outlet. Moreover, an empirical formula was proposed to assess the influence of the proportion of sphere-paired particles on the discharge flow rate. Sphere-paired particles tended to hinder the discharging process, which was caused by the rotation around their centroids and the angular deflection close to angle of the hopper.

The charge transferred between individual particles of varying materials (aluminum, PTFE and nylon) and sizes (3.2–4.8 mm) was investigated using a particle collision apparatus. The collisions were video-recorded and analyzed via a Particle Tracking Velocimetry software to determine the particles' impact velocities and angles. Glancing impacts were found to have a notable effect on charge transfer. Different-material collisions exhibited expected directions of charge transfer. Same-sized nylon collisions revealed that their charge transfer amplified the difference in the particles' initial charges in most cases. Different-sized nylon collisions suggested that size-dependent bipolar charging occurs in individual particle-particle collisions. However, the charging magnitude and direction did not correlate with their size differences, and so additional particle collision experiments with other material types and sizes are needed. This work should be considered as a steppingstone for future researchers to explore particle-particle charge transfer in their respective systems, and develop empirical particle charging models.

We propose a new type of microfluidic flow sensor, where the velocity measurements are not done on the fluid sample itself but on a second, immiscible fluid in contact with the sample. This allows us to use a low-cost, straight-forward, and well-developed particle tracking velocimetry on samples otherwise unsuitable for tracer particles. Our proof-of-concept experimental setup consists of a microfluidic device with the main channel filled with the sample and rectangular side-cavities, adjacent and opened to the main channel, filled with immiscible fluid with tracer particles. The flow in the main channel induces a circular secondary flow of the cavity liquid. We observed and analyzed the side-cavity particle movement and found that its characteristic parameters show a good linear correlation with flow velocity in the main channel over the whole observed range, from approx. $600~\mu \text{m}$ /s (volumetric flow rate $\Phi _{v} \cong 200$ nl/min, Reynolds number $\textit {Re} \cong 10^{-3}$ ) to approx. $3500 ~\mu \text{m/s}\left ({\Phi _{v} \cong 1200~ \text{nl/min}, ~\text{Re} \cong 10^{-2}}\right)$ .

This study proposed the fluidized particles with dielectric barrier discharge (DBD) plasma in a slot-rectangular divergent-base spouted bed and focused on the dynamics of solid particles with the plasma irradiation. Two bed materials (Polypropylene (PP) particles and Polyamide (PA) particles) with same diameter (3 mm) were fluidized in this study. Fluidization parameters included gas velocity (7.4–14.9 m/s), particle amount (100–500), and plasma parameter (apply voltage, 0 and 7 kV) as the applied voltage were investigated here. Particle velocity profiles were analyzed through the methods of particle image velocimetry (PIV) and particle tracking velocimetry (PTV). Results show that the particle velocity was increased with the plasma irradiation, mainly by the enhancement in the vertical direction. The location of the highest particle velocity area related to the fluidization behavior of particles. With the increase of superficial gas velocity, the location of the highest particle velocity area raised along the central line but not reached the top of the solid bed. While the electron temperature of Ar plasma decreased with the addition of particles. Two electric fields (external electric field and surface charge electric field) presenting in the system were assumed to give the reason for the changes of the particle fluid dynamics.

Objective: 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. Methods: 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 $\mu$ m, 1 mm and 1.5 mm. 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. Results: 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 1.5 mm 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%. Conclusion: 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. Significance: 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.

Abstract Over the past few decades, advances have been made in using particle image velocimetry (PIV) and particle tracking velocimetry (PTV) for mapping of Lagrangian velocity and acceleration flow fields. With PIV, Lagrangian trajectories are not measured directly; rather, hypothetical trajectories must be constructed from sequences of Eulerian velocity snapshots. Because PTV directly measures actual trajectories, it provides distinct advantages over PIV, especially for trajectories with abrupt changes in direction. In this work, a novel particle tracking algorithm is described, then applied to track trajectories of tracer particles in submerged turbulent jets. The Reynolds numbers ranged from 1000 to 25,000, thereby covering laminar, transitioning-to-turbulence, and fully turbulent flow regimes. The novel particle tracking algorithm is designed to handle flows with very high particle concentrations, thereby resolving small-scale flow structures. Trajectories are tracked with high velocity gradients, sharp curvatures, cycloids, abrupt changes in direction, and strong recirculation—all of which are inaccessible via construction from PIV sequences. Most trajectories measured in this work are at least 500 camera frames (time steps) long, with many being more than 3000 frames long. Graphic abstract

Ideally, nitric oxide (NO) production pathways would be measured individually to understand the formation mechanisms at a fundamental level. Unfortunately, the four production routes in hydrocarbon combustion cannot be fully decoupled. Hydrogen combustion at low flame temperatures eliminates prompt-NO and mitigates thermal production, such that only the N2O and NNH pathways remain as significant production routes. The H2/O2 system, whose base chemistry has been studied in great detail, offers an excellent platform to validate nitrogen chemistry by limiting the possibility of error propagation during model calibration. The current work presents measurements of velocity, temperature, and NO concentration in premixed, jet-wall stagnation, hydrogen–air flames at atmospheric pressure, diluted with argon to maintain adiabatic flame temperatures below 1800 K. Measurements of reference flame speeds, Su,ref, obtained with particle tracking velocimetry, highlight the modeling differences in H2/O2 chemistry from a selection of thermochemical mechanisms, especially in lean flames affected by preferential diffusion. Laser induced fluorescence measurements in lean-to-rich flames ( ϕ = 0.7 –1.5) yield concentrations of NO from 2 to 0.5 ppm, respectively. Simulated NO profiles cover one order of magnitude in predicted signal intensity. Fortunately, recent mechanisms with accurate descriptions of the N2O and NNH pathways predict NO concentrations within experimental uncertainties for multiple operating conditions.

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. In conventional HPTV, where the scattered light field is reconstructed via backpropagation calculations, the particle image spreads greatly in the depth direction and it is then difficult to perform three-dimensional three-component (3D3C) measurements with high accuracy. In the proposed method, CS is applied based on the spatial sparseness of the particle distribution and highly accurate 3D3C measurements are made possible by direct reconstruction of the particle distribution. In this paper, we explain the principle of HPTV based on CS and report the results of evaluation of the velocity vector distribution measurement of a micro linear channel. The experimental results indicate that the proposed method is effective for 3D3C measurements of microflows. Measurement of the velocity field of microflows is becoming increasingly important in the development of microfluidic devices and in the understanding of biological mechanisms. The proposed method is expected to provide an effective technique for use in these applications.

The dynamic mechanism of the vortex generation and evolution process in a fully developed turbulent boundary layer with Reθ =97–194 is experimentally investigated. In this study, a moving single-frame and long-exposure (MSFLE) imaging method and a moving particle image velocimetry/particle tracing velocimetry (M-PIV/PTV) are designed and implemented for measuring the temporal and spatial evolution of vortex cores in both qualitative and quantitative ways, respectively. On the other hand, the Liutex vector, which is a new mathematical definition and identification of the vortex core proposed by Liu’s group, is first applied in the experiment for the structural visualization and quantitative analysis of the local fluid rotation. The results show that an intuitional process of vortex evolution can be clearly observed by tracking the vortex using MSFLE and verify that the roll-up of the shear layer induced by shear instability is the origin of vortex formation in turbulence. Furthermore, a quantitative investigation in terms of the critical vortex core boundary (size) and its accurate rotation strength is carried out based on the Liutex vector field analysis by M-PIV/PTV. According to statistics of the relation between vortex core size and the rotation strength during the whole process, the phy sical mechanism of vortex generation and evolution in a turbulent boundary layer of low Reynolds number can be summarized as a four-dominant-state course consisting of the “synchronous linear segment (SL)-absolute enhancement segment (AE)-absolute diffusion segment (AD)-skewing dissipation segment (SD)”.

Granular flows of sintered bauxite proppants were examined along an inclined plane for solar thermal energy storage applications. Granular flow properties needed to drive numeric granular models were measured for improved numerical model predictions for Carbobead CP 50/140, 40/100, and 30/60 particles. Particle shape and size distributions were determined by coupling optical microscopy to an in-house image processing algorithm. The impulse excitation technique was used to measure elastic and shear moduli, and compute Poisson’s ratio. The coefficient of static sliding friction was measured using the slip-stick method, and the static rolling friction was determined from measured shear on particles positioned between two hot-pressed plates. The coefficient of restitution was measured by dropping particles on a surface and determining the kinetic energy before and after impact with the surface using high resolution particle tracking velocimetry. Particle size did not significantly impact the coefficients of restitution and static rolling friction, however, particle shape distribution resulted in a large variation in measurements. An inclined flow experiment was performed to characterize granular flows of Carbobead CP 30/60 particles using particle image velocimetry. Numerical models of the experiment using discrete element method were generated with the measured mechanical properties as inputs for comparison with experimental results. A constant directional torque rolling friction model best predicted bulk granular flow behavior. Good agreement between the model and experiment was achieved at ambient, steady state conditions, with average velocity differences

We detect the trajectory of particles using the feature matching method to improve the resolution of particle streak velocimetry (PSV), which is used to measure the velocity of particles from a visualized path line. PSV has a more reliable performance in particle matching as compared to particle tracking velocimetry and is therefore less likely to cause erroneous matching even in high-density images. The center of gravity of the first and last trajectories is obtained to calculate the displacement. The trajectory of the particle is illuminated using a diode laser and imaged using a digital single-lens reflex camera; the trajectory is then divided into three parts and recorded in a single frame using coded illumination. The first and second trajectories are short, and the third trajectory is long. The asymmetry of the trajectories is then used to determine the flow direction. We first evaluate the detection rate by increasing the trajectory density of synthetic images. The image size was fixed at 500 × 500 pixels, and the number of trajectories was increased from 28 to 280, and the detection rate was examined. Then, we evaluated the accuracy of detection of the center of gravity of the first and last trajectories using the root mean square error. Finally, we used the coded illumination method to visualize the swirling flow inside a device to examine its applicability to real flows.

Here the effect of contact properties on discrete element method (DEM) simulations of dry granular flow was investigated. The particle contact properties were first measured using particle tracking velocimetry. DEM simulations of flow from hoppers with outlet angles of 30°, 60° and 90° were then performed. The simulations were validated by comparison with experimental measurements of the flow rate from the hopper and magnetic resonance imaging (MRI) measurements of the velocities of the particles within the hopper. The mass flow rate predicted by DEM was insensitive to the contact properties used in the simulations, indicating flow rate is not a suitable parameter for validation. In contrast, the velocity of the particles in the central region of the hoppers was sensitive to the coefficients of friction. The best agreement between the simulations and the MRI measurements of the velocities of the particles was obtained using the a priori measured contact parameters.

Sediment transport is one key process in sedimentation problems. The dynamics of sediments in rivers will lead to an ecological change of the catchment. Among all complicated processes in sediment transport, the settling dynamics of solid particles in the water contribute to the water quality and geomorphology of a river channel directly. This paper aims at an investigation of the interaction between particle movement and water flow, with application to hydro-environment situations such as transport of fine sand sediment in natural streams. The Stokes number in this type of application is much smaller than unity at which enhancement of particle settling velocity by strong ambient turbulence has been observed in many numerical and laboratory studies. The present laboratory study is conducted to study the settling of sub-millimeter sized heavy particles in water with a relatively weak grid-generated turbulence. The two-phase flow is measured with the whole-field imaging techniques of particle image velocimetry (PIV) and particle tracking velocimetry (PTV). A two-camera PIV/PTV technique is used to obtain the instantaneous settling velocities of the solid particles and the turbulent water velocity field. Phase separation is based on an effective optical distinction of the two light scattering signals with fluorescent tagging on the solid particles. With this technique, it is found that in most cases of grid-generated turbulence the settling velocity of the heavy particles is slightly lower than the still water value. The falling heavy particles are also found to cause additional turbulence in the water with low ambient turbulence intensities. At one particular case of grid turbulence, the particles are found to fall with a depth-averaged settling velocity evidently higher than the still water value. The instantaneous turbulent fluid motions and particle trajectories tend to support the fast tracking effect to be related to the higher particle falling velocities.

This work introduces a 4D flow magnetic resonance imaging (MRI) pressure reconstruction method which employs weighted least-squares (WLS) for pressure integration. Pressure gradients are calculated from the velocity fields, and velocity errors are estimated from the velocity divergence for incompressible flow. Pressure gradient errors are estimated by propagating the velocity errors through Navier-Stokes momentum equation. A weight matrix is generated based on the pressure gradient errors, then employed for pressure reconstruction. The pressure reconstruction method was demonstrated and analyzed using synthetic velocity fields as well as Poiseuille flow measured using in vitro 4D flow MRI. Performance of the proposed WLS method was compared to the method of solving the pressure Poisson equation which has been the primary method used in the previous studies. Error analysis indicated that the proposed method is more robust to velocity measurement errors. Improvement on pressure results was found to be more significant for the cases with spatially-varying velocity error level, with reductions in error ranging from 50% to over 200%. Finally, the method was applied to flow in patient-specific cerebral aneurysms. Validation was performed with in vitro flow data collected using Particle Tracking Velocimetry (PTV) and in vivo flow measurement obtained using 4D flow MRI. Pressure calculated by WLS, as opposed to the Poisson equation, was more consistent with the flow structures and showed better agreement between the in vivo and in vitro data. These results suggest the utility of WLS method to obtain reliable pressure field from clinical flow measurement data.

The flow dynamics of binary particle mixtures in the fluidized bed needs to be monitored in order to optimize the related industrial processes. In this paper, electrostatic sensing and high-speed imaging are applied to measure the velocities of polyethylene and sand particles in the binary particle mixtures in fluidization. Experimental studies were conducted on a lab-scale cold circulating fluidized bed. Correlation function between electrostatic signals from upstream and downstream electrodes placed along the riser shows two peaks that represent transit times for the two types of particles. To verify the above results, high-speed imaging was adopted to capture the flow images of particle mixtures. Particle Image Velocimetry and Particle Tracking Velocimetry algorithms were utilized to process the resulted images in order to measure the velocities of polyethylene and sand particles. The reasons for two-peak correlation functions are illustrated based on the frequency spectrums of the mono-solid-phase electrostatic signals and the velocity difference between polyethylene and sand particles. Finally, comparisons on the velocities obtained from electrostatic sensing and high-speed imaging demonstrate the electrostatic sensor can roughly estimate the particle velocity of binary particle mixtures in the near wall region of the circulating fluidized bed.

We evaluate Beer-Lambert (BL) ray-tracing and Monte Carlo N-Particle (MCNP) photon tracking simulations for prediction and comparison of x-ray imaging system performance. These simulation tools can aid the methodical design of laboratory-scale x-ray particle image velocimetry (XPIV) experiments and tracer particles by predicting image quality. Particle image signal-to-noise ratio (SNR) is used as the metric of system performance. Simulated and experiment data of hollow, silver-coated, glass sphere tracer particles (AGSF-33) are compared. As predicted by the simulations, the AGSF-33 particles are visible with a SNR greater than unity in 100 ms exposure time images, demonstrating their potential as x-ray PIV or particle tracking velocimetry (XPTV) tracers. The BL approach predicts the image contrast, is computationally inexpensive, and enables the exploration of a vast parameter space for system design. MCNP simulations, on the other hand, predict experiment images slightly more accurately, but are more than an order of magnitude more computationally expensive than BL simulations. For most practical XPIV system design applications, the higher computational expense of MCNP is likely not justified by the modest accuracy improvement compared to BL.

The particle mass concentration and -mass flow rate are fundamental parameters for describing two-phase flows and are products of particle number, -size, -velocity, and -density. When investigating particle-induced heating augmentation, a detailed knowledge of these parameters is essential. In most of previous experimental studies considering particle-induced heating augmentation, only average particle mass flow rates are given, without any relation to measured particle sizes and -velocities within the flow or any indication of measurement uncertainty. In this work, particle number, individual particle sizes, and velocities were measured in a supersonic flow by means of shadowgraphy and particle tracking velocimetry (PTV). The goals are to determine measurement uncertainties, a particle velocity-size relation, and the spatial distribution of number, size, velocity, and mass flow rate across the nozzle exit. Experiments were conducted in a facility with a nozzle exit diameter of 30 mm, at Ma∞ = 2.1 and Re∞ = 8.2e7 1/m. Particles made of Al2O3 and up to 60 µm in size were used for seeding. Particle mass flow rates up to 50 kg/m2 s were achieved. It is shown that an additional correction procedure reduced common software uncertainties regarding shadowgraphy particle size determination from 14% to less than 6%. Discrepancies between calculated particle velocities and experimental data were found. In terms of spatial distribution, larger particles and a higher mass flow rate concentrate in the flow center. The determined particle mass flow rate uncertainty was up to 50% for PTV; for shadowgraphy, it was less than 17%. Graphical abstract

The paper addresses the shortcoming of current event-based vision (EBV) sensors in the context of particle imaging.Latency is introduced both on the pixel level as well as during read-out from the array and results in systemic timing errors when processing the recorded event data.Using pulsed illumination, the overall latency can be quantified and indicates an upper bound on the frequency response on the order of 10-20 kHz for the specific EBV sensor. In particle-based flow measurement applications, particles scattering the light from a pulsed light source operating below this upper frequency can be reliably tracked in time.Through the combination of event-based vision and pulsed illumination, flow field measurements are demonstrated at light pulsing rates up to 10 kHz in both water and air flows by providing turbulence statistics and velocity spectra.The described EBV-based velocimetry system consists of only an EBV camera and a (low-cost) laser that can be directly modulated by the camera, making the system compact, portable and cost effective.

Transient motion, turbulence and bubble dynamics make any velocity quantification extremely difficult in unsteady gas–liquid flows. In the present study, novel Eulerian and Lagrangian techniques of velocimetry were developed, using both intrusive and non-intrusive measurements. The selected unsteady gas–liquid flow was a breaking bore, featured with a transient motion, air entrainment and coherent structures. Intrusively, Eulerian probe measurements resulted to the development of a single bubble event detection (SBED) technique in unsteady air–water flows. Non-intrusively, the motion of air–water pattern was detected using a novel particle tracking velocimetry (PTV). Both velocities obtained using SBED and PTV techniques were validated against the established optical flow (OF) results, achieving consistent velocity data among the three techniques. The filtering criteria of the SBED and PTV techniques were discussed, showing the best options in the breaking bore. It is concluded that the most robust velocity measurements in gas–liquid flow are achieved with consistent velocity data between the SBED, PTV and OF techniques.

Observations of real-time ocean surface currents allow one to search and rescue at ocean disaster sites and investigate the surface transport and fate of ocean contaminants. Although real-time surface currents have been mapped by high-frequency (HF) radar, shipboard instruments, satellite altimetry, and surface drifters, geostationary satellites have proved their capability in satisfying both basin-scale coverage and high spatiotemporal resolutions not offered by other observational platforms. In this paper, we suggest a strategy for the production of operational surface currents using geostationary satellite data, the particle image velocimetry (PIV) method, and deep learning-based evaluation. We used the model scalar field and its gradient to calculate the corresponding surface current via PIV, and we estimated the error between the true velocity field and calculated velocity field by the combined magnitude and relevance index (CMRI) error. We used the model datasets to train a convolutional neural network, which can be used to filter out bad vectors in the surface current produced by arbitrary model scalar fields. We also applied the pretrained network to the surface current generated from real-time Himawari-8 skin sea surface temperature (SST) data. The results showed that the deep learning network successfully filtered out bad vectors in a surface current when it was applied to model SST and created stronger dynamic features when the network was applied to Himawari SST. This strategy can help to provide a quality flag in satellite data to inform data users about the reliability of PIV-derived surface currents.

The dynamics of wetting and dewetting is largely determined by the velocity field near the contact lines. For water drops it has been observed that adding surfactant decreases the dynamic receding contact angle even at a concentration much lower than the critical micelle concentration (CMC). To better understand why surfactants have such a drastic effect on drop dynamics, we constructed a dedicated a setup on an inverted microscope, in which an aqueous drop is held stationary while the transparent substrate is moved horizontally. Using astigmatism particle tracking velocimetry, we track the 3D displacement of the tracer particles in the flow. We study how surfactants alter the flow dynamics near the receding contact line of a moving drop for capillary numbers in the order of $10^{-6}$. Even for surfactant concentrations $c$ far below the critical micelle concentration ($c \ll$ CMC) Marangoni stresses change the flow drastically. We discuss our results first in a 2D model that considers advective and diffusive surfactant transport and deduce estimates of the magnitude and scaling of the Marangoni stress from this. Modeling and experiment agree that a tiny gradient in surface tension of a few $\mu N \, m^{-1}$ is enough to alter the flow profile significantly. The variation of the Marangoni stress with the distance from the contact line suggests that the 2D advection-diffusion model has to be extended to a full 3D model. The effect is ubiquitous, since surfactant is present in many technical and natural dewetting processes either deliberately or as contamination., Comment: 12 pages, 7 figure plus supporting information

International audience; Data collected by the Fast Imaging Plasma Spectrometer (FIPS) aboard the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft showed singly charged Na+-group ions at energies of between 1 and 13 keV in Mercury's northern planetary cusp. Most of these ions are likely formed by either photoionization or charge exchange of exospheric Na atoms, with initial energies of approximately 1 eV or less. FIPS observations did not establish which acceleration mechanism most reasonably accounts for this energy gain. Using the Adaptive Mesh Particle Simulator (AMPS) model, we undertake kinetic simulations of 1 eV Na+ test particles through the electric and magnetic fields output from the Block Adaptive Tree Solar wind Roe-type Upwind Scheme (BATSRUS) global magnetohydrodynamic (MHD) model of Mercury's magnetosphere, in search of plausible explanations for the source of this energization. We find that Na+ with initial energy of 1 eV are readily picked up by the Dungey cycle return flow in the dayside magnetosphere. In some cases, this flow provides the energy for the ions to escape into the magnetosheath, and in other cases it energizes the ions to hundreds of eV before they pass immediately into the cusp. Those that escape can be rapidly picked up into the magnetosheath flow, where they are accelerated by pickup again up to tens of keV. These one- and two-stage pickup processes on Mercury's dayside can account for the energies of many of the Na+ ions observed in Mercury's northern magnetospheric cusp by MESSENGER.

Fabrication of functional vascularised three-dimensional tissue constructs has been a long-standing objective in the field of tissue engineering. Currently, the main limitation in this field is the inability to produce fully vascularised tissue with an internal mass transport system (vascular network) that can provide cells with nutrients and oxygen while removing waste, to imitate the functions of human living tissue. Achieving such a system would allow the development of large-scale tissue constructs and increase the potential for in vivo integration. There are different approaches to attempt vascularisation, which use a diversity of techniques. Among these, one of the most promising is additive manufacturing due to its versatility, reproducibility, and compatibility with suitable materials. With the aim of contributing towards the efforts in this field, the present work presents a method for the automatic generation of physiologically-based vascular network structures as solid 3D models suitable for additive manufacturing technologies. Considering the natural hierarchical branching vasculature as an ideal solution, an algorithm was developed to generate branching tree structures connected at the ends to form vascular networks. The implementation is based on previous work in the field of computational bio-simulation of arterial tree growth. It consists of a space-filling algorithm that connects all given points to a growing tree within a defined three-dimensional volume, while fulfilling constraints associated with the physiological laws of circulation. The networks are generated using a CAD environment and thus can be used in additive manufacturing processes. An investigation was carried out on the effect of three input parameters (namely volumetric flow rate, pressure difference across the tree, and number of terminal points) in order to find a suitable combination of parameters that would produce networks with diameters above the fabrication threshold. In order to demonstrate feasibility and functionality of the networks fabricated using this proposed method, two network models were produced by 3D printing and subsequently used as a sacrificial structure to produce PDMS blocks with the hollow vascular networks embedded in it. Particle tracking was used to measure the flow velocity in the channels at two different inlet flow rates. Comparisons were made with theoretical values obtained from computational fluid dynamics simulations and show a good agreement between experiment and theory. From the measurements of maximum velocity, it was observed that at a lower flow rate, the experimental values were closer to the theoretical values than at a higher flow rate. This might be due to the challenges that higher flow rates represent, such as less accurate particle tracking. Given the overall agreement, it is concluded that computational fluid dynamics simulations are a fast and effective way to analyse flow in vascular network models produced by the method here proposed., The Cambridge Trust, CONACyT (Consejo Nacional de Ciencia y Tecnologia), EPSRC Cambridge & Cranfield Doctoral Training Centre in Ultra Precision

This paper presents a new framework for particle tracking based on a Gaussian Mixture Model (GMM). It is an extension of the state-of-the-art iterative reconstruction of individual particles by a continuous modeling of the particle trajectories considering the position and velocity as coupled quantities. The proposed approach includes an initialization and a processing step. In the first step, the velocities at the initial points are determined after iterative reconstruction of individual particles of the first four images to be able to generate the tracks between these initial points. From there on, the tracks are extended in the processing step by searching for and including new points obtained from consecutive images based on continuous modeling of the particle trajectories with a Gaussian Mixture Model. The presented tracking procedure allows to extend existing trajectories interactively with low computing effort and to store them in a compact representation using little memory space. To demonstrate the performance and the functionality of this new particle tracking approach, it is successfully applied to a synthetic turbulent pipe flow, to the problem of observing particles corresponding to a Brownian motion (e.g., motion of cells), as well as to problems where the motion is guided by boundary forces, e.g., in the case of particle tracking velocimetry of turbulent Rayleigh–Bénard convection.

We present a field study of snow settling dynamics based on simultaneous measurements of the atmospheric flow field and snow particle trajectories. Specifically, a super-large-scale particle image velocimetry (SLPIV) system using natural snow particles as tracers is deployed to quantify the velocity field and identify vortex structures in a 22 m $\times$ 39 m field of view centered 18 m above the ground. Simultaneously, we track individual snow particles in a 3 m $\times$ 5 m sample area within the SLPIV using particle tracking velocimetry (PTV). The results reveal the direct linkage among vortex structures in atmospheric turbulence, the spatial distribution of snow particle concentration, and their settling dynamics. In particular, with snow turbulence interaction at near-critical Stokes number, the settling velocity enhancement of snow particles is multifold, and larger than what has been observed in previous field studies. SLPIV measurements show higher concentration of snow particles preferentially located on the downward side of the vortices identified in the atmospheric flow field. PTV, performed on high resolution images around the reconstructed vortices, confirms the latter trend and provides statistical evidence of the acceleration of snow particles, as they move toward the downward side of vortices. Overall, the simultaneous multi-scale particle imaging presented here enables us to directly quantify the salient features of preferential sweeping, supporting it as an underlying mechanism of snow settling enhancement in the atmospheric surface layer., 16 pages and 7 figures, to be published in the Journal of Fluid Mechanics

Introduction Patients suffering from low-flow, low-gradient aortic stenosis present a decreased stroke volume due to decreased contraction or relaxation function of the left ventricle. As a low stroke volume tends to cause a low transvalvular flow, transvalvular pressure gradient (TVPG) and effective orifice area, the clinician cannot rely on those parameters with confidence for the evaluation of aortic stenosis severity. Hence new diagnostic parameters have to be developed. Energy loss through turbulence associated with aortic stenosis represented the wasted left ventricle work. Currently, echocardiographic measurement of the turbulence intensity is not validated for clinical evaluations of aortic stenosis. Methods Two porcine aortic valves were harvested and inserted in a flow loop that replicates the pulsatile flow of the heart. A stiffening of the valves was achieved by treating them with formaldehyde. The stiffening was externally confirmed by a custom-made force-displacement device quantifying the rigidity of the leaflet yielding two stiffness grades per valve. Each valve was tested under three different mean flow rates (1, 2.5, and 4 l/min) at each of the two stiffness grades. Moreover the pressure in the left ventricle chamber and in the aortic chamber was recorded to calculate the TVPG. Particle tracking velocimetry measurements into the transparent silicone ascending aorta phantom allowed the computation of the turbulent kinetic energy (TKE), to evaluate the energy loss due to turbulence. Results We could confirm the enhanced rigidity of the valve leaflets with our custom device (data not shown) and measure a consistent increase in TVPG across all mean flow rates between the two stiffness grades. Moreover, an explicit increase of the TKE in the aortic phantom could be measured after the stiffening process (73.1% under 1 l/min, and 43% under both 2.5 and 4 l/min). In addition, a good correlation (R = 0.86) between the mean TVPG and the TKE was found. Conclusions This project demonstrated the possibility of quantifying the energy loss attributed to turbulence for porcine valves in vitro for native and added stiffness grade. This project lays the foundation for the development of a new diagnostic tool for the assessment of stenosis severity in patients with low-flow, low-gradient aortic stenosis in cardiac imaging tool such as echocardiography. Funding Acknowledgement Type of funding sources: None. TVPG and its correlation with TKEIntensity graphs of the TKE

Deep ultrasound localization microscopy (deep-ULM) allows sub-wavelength resolution imaging with deep learning. However, the injection of contrast agents (CAs) in deep-ULM is debatable because of their potential risk. In this study, we propose a deep learning-based super-resolution ultrasound (DL-SRU), which employs the concept of deep-ULM and a convolutional neural network. The network is trained with synthetic tracer images to localize positions of red blood cells (RBCs) and reconstruct vessel geometry at high resolution, even for CA-free ultrasound (US) images. The proposed algorithm is validated by comparing the full width at half-maximum values of the vascular profiles reconstructed by other techniques, such as the standard ULM and the US average intensity under in silico and in vitro conditions. RBC localization by DL-SRU is also compared with that by other localization approaches to validate its performance under in vivo condition, especially for veins in the human lower extremity. Furthermore, a two-frame particle tracking velocimetry (PTV) algorithm is applied to DL-SRU localization for accurate flow velocity measurement. The velocity profile obtained by applying the PTV is compared with a theoretical value under in vitro condition to verify its compatibility with the flow measurement modality. The velocity vectors of individual RBCs are obtained to determine the applicability to in vivo conditions. DL-SRU can achieve high-resolution vessel morphology and flow dynamics in vasculature, mapping 110 super-resolved images per second on a standard PC, regardless of various imaging conditions. As a result, the DL-SRU technique is much more robust in localization compared with previous deep-ULM. In addition, the performance of DL-SRU is nearly the same as that of deep-ULM in rapid computational processing and high measurement accuracy. Thus, DL-SRU might become an effective and useful instrument in clinical practice.

High-gradient magnetic separation (HGMS) effectively separates fine weakly magnetic minerals using a magnetic matrix. The basic principle of single-wire capture of magnetic particles in HGMS has received considerable attention. In practice, however, a real matrix is made of numerous magnetic wires. Transport of magnetic particles inside a multiwire matrix under various operating conditions has not been sufficiently investigated, and it is not clear whether single-wire and multiwire matrices differ significantly. A fully coupled multiphysics model based on the idealized capture model was developed to investigate the 2D capture and accumulation of multiple types of particles in single-wire and multiwire matrices. In this model, the properties of multiple types of particles were defined. Then, particle tracing via the fluid flow model was used to calculate the dynamic capture and accumulation of particles under the determined magnetic and flow fields. The time-dependent dynamic capture mode used in this study can reveal the details of particle capture and accumulation in single-wire and multiwire matrices. All the calculations and analyses indicate that single-wire and multiwire matrices both exhibit basically the similar capture tendency as the particle size, slurry feed velocity, and magnetic induction are gradually increased, and a single-wire matrix always has a much higher capture selectivity than a multiwire matrix. This difference in selectivity between the single-wire and multiwire matrices results mainly from magnetic coupling between magnetic wires in the multiwire matrix, where the fluid flow is also quite complicated. In addition, adjacent columns of wires are staggered vertically, increasing the probability of collisions between the particles and the wires; thus, intergrowth particles that are not captured by the upstream wires are more easily captured by the downstream wires. By comparing the experimental results with the simulation results, the correctness of the HGMS recovery and grade prediction results was verified.

No domínio da hidráulica fluvial, é fundamental conhecer o campo de velocidades das fases sólida (sedimentos) e líquida (água). A partir do campo de velocidades instantâneas é possível quantificar diversas variáveis incluindo intensidades da turbulência e tensões de corte e identificar zonas de separação, recirculação, etc. O desenvolvimento de técnicas óticas permitiu o desenvolvimento de instrumentos de medição baseados na aquisição e no processamento de imagens, nomeadamente o PIV (particle image velocimetry) e o PTV (particle tracking velocimetry). Neste artigo, apresenta-se um algoritmo que combina ambas as técnicas, PIV e PTV, permitindo assim, juntar os pontos fortes de cada uma das técnicas e possibilitando a medição simultânea do campo de velocidades da água e dos sedimentos e estudar mais detalhadamente a interação fluido-sedimentos. As vantagens e limitações do algoritmo proposto são exploradas e discutidas com recurso a um conjunto de experiências laboratoriais., In the domain of fluvial hydraulics, it is critical to know the velocity field of both solid (sediments) and liquid phases (water). From the velocity field it is possible to determine different variables such as shear stresses, identify recirculation regions, etc. The development of optical techniques allowed for measurement techniques based on image acquisition and processing, namely PIV (particle image velocimetry) and PTV (particle tracking velocimetry). In this paper an algorithm combining both PIV and PTV techniques is presented, allowing in this way to profit from each technique strong points and allowing the simultaneous measurement of the water and sediment layer velocity fields and to obtain a better know how of the fluid-sediment interaction. The advantages and limitations of the proposed techniques are explored and discussed by means of a laboratory experiment., Este trabalho teve o apoio financeiro do Projeto PTDC/ ECM-HID/6387/2014 – POCI-01-0145- FEDER-016825 – financiado por fundos do FEDER através do COMPETE2020 – Programa Operacional Competitividade e Internacionalização (POCI) e por fundos nacionais através da FCT – Fundação para a Ciência e a Tecnologia, I.P

The flow dynamics in pipes is a very complex system because it is largely affected by flow conditions. The transport of crude oil in pipelines within unconsolidated petroleum reservoirs is associated with presence of solid particles. These particles are often transported as dispersed phases during crude oil production and are therefore detrimental to the pipe surface integrity. This could lead to the occurrences of crevice corrosion due to pipe erosion. In relation to the above discussion, this paper is aimed at analyzing crude oil dynamics during flow through pipeline and identifying erosion hotspot for different pipe elbow curvatures. Reynolds Averaging Navier-Stokes (RANS) and Particle Tracing Modeling (PTM) approach were used. The focus is to simulate fluid dynamics and particle tracing, respectively. Post-processed results revealed that the fluid velocity magnitude was relatively high at the region with minimum curvature radius. The maximum static pressure and turbulence dissipation rate were experienced in areas with low-velocity magnitude. Also, the rate of erosive wear was relatively high at the elbow and the hotspot varied with pipe curvature. The particle flow rate, mass, and size were varied and it was found that erosion rate increased with an increase in particle properties.

Purpose The purpose of this paper is to determine how the shape of the container affects the efficiency of a traveling magnetic field (TMF) stirring. Design/methodology/approach The modeling approach is based on finite element software Comsol which includes harmonic electromagnetic (EM), transient CFD and particle tracing modules. For evaluating efficiency of stirring the particle, homogenization parameter is used. Findings It has been determined that the use of an elliptical cylinder-shaped vessel allows better heat removal from the side surface and, at the same time, the stirring efficiency does not drop significantly. Practical implications The results of the work can be used in the design of EM stirring installations in which exothermic reactions occur. Originality/value The transient simulation of particle transport in a TMF-driven melt flow gives the opportunity to estimate the efficiency of stirring process in different vessel shapes.