Particle Velocity Measurements Research Articles

Particle velocity measurement in powder gas jets of coaxial powder nozzles for laser material deposition

Laser material deposition (LMD) is a process in which a laser beam creates a melt pool on the surface of a substrate while a powder nozzle delivers a powdered additive into the melt pool, where the powder material then melts. A dense, metallurgically bonded layer forms once the melt solidifies. The velocity of powder particles in LMD is one of the key factors that influence the amount of particles’ energy absorption (along their individual trajectories) through the laser beam on the way between the powder nozzle and the substrate. The amount of energy that is absorbed by the powder particles above the melt pool determines the temperature on the substrate surface and, hence, influences the formation of the melt pool and the deposition of the powder material. Data about the particle velocity are, therefore, essential for modeling the LMD process—not only for physical simulation where a particle’s energy input can be integrated along its trajectory, but also in an experimental environment of process parameter studies, where understanding the interdependencies between the process parameters is crucial. In this study, a setup using a high-speed camera and an illumination laser is used to measure the velocity of powder particles in the powder gas jet of a coaxial powder nozzle. Several parameters that are known to influence the particle velocity are varied: Feed gas rate, shielding gas rate, nozzle geometry (width of annular gap), and powder mass flow rate. In this study, four different powder types are used. The influence of these process parameters on the particle velocity is measured. Four different methods for tracking individual particles and calculating the velocity distribution within the powder gas jet are used and compared: Manual frame-by-frame particle tracking and manual evaluation from multiple exposures in single frames, as well as particle tracking velocimetry and particle image velocimetry (PIV), which incorporate region-of-interest boxes into the algorithm. Sufficient accordance as to the measurement results is found in comparing the four methods. Further, using the highly automatable PIV method, the influence of main process parameters on particle velocity is measured. Out of the examined parameters, the feed gas rate is found to have the most immediate impact with a linear correlation to particle velocity. A correlation between different powder particle size distributions and measured particle velocities is shown as well.

Drive-pressure optimization in ramp-wave compression experiments through differential evolution

Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. We solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closely reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.

On-Chip Multiple Particle Velocity and Size Measurement Using Single-Shot Two-Wavelength Differential Image Analysis.

Precise and quick measurement of samples’ flow velocities is essential for cell sorting timing control and reconstruction of acquired image-analyzed data. We developed a simple technique for the single-shot measurement of flow velocities of particles simultaneously in a microfluidic pathway. The speed was calculated from the difference in the particles’ elongation in an acquired image that appeared when two wavelengths of light with different irradiation times were applied. We ran microparticles through an imaging flow cytometer and irradiated two wavelengths of light with different irradiation times simultaneously to those particles. The mixture of the two wavelength transmitted lights was divided into two wavelengths, and the images of the same microparticles for each wavelength were acquired in a single shot. We estimated the velocity from the difference of its elongation divided by the difference of irradiation time by comparing these two images. The distribution of polystyrene beads’ velocity was parabolic and highest at the center of the flow channel, consistent with the expected velocity distribution of the laminar flow. Applying the calculated velocity, we also restored the accurate shapes and cross-sectional areas of particles in the images, indicating this simple method for improving of imaging flow cytometry and cell sorter for diagnostic screening of circulating tumor cells.

CFD-DEM simulation of Small-Scale Challenge Problem 1 with EMMS bubble-based structure-dependent drag coefficient

In this study, the energy minimization multi-scale (EMMS)/Bubbling model is coupled with the computational fluid dynamics/discrete element method (CFD-DEM) model via a structure-dependent drag coefficient to simulate the National Energy Technology Laboratory (NETL) small-scale challenge problem using the open-source multiphase flow code MFIX. The numerical predictions are compared against particle velocity measurements obtained from high-speed particle image velocimetry (HSPIV) and differential pressure measurements. The drag-reduction effect of the EMMS bubble-based drag coefficient is observed to significantly improve predictions of the horizontal particle velocity and granular temperature when compared to several other drag coefficients tested; however, the vertical particle velocity and pressure fluctuation characteristic predictions are degraded. The drag-reduction effect is characterized by a reduction in the sizes of slugs or voids, as identified through spectral decomposition of the pressure fluctuations. Overall, this study shows great promise in employing drag coefficients, developed via multi-scale approaches (such as the EMMS paradigm), in CFD-DEM models.

Measurement of velocity and concentration profiles of pneumatically conveyed particles in a square-shaped pipe using electrostatic sensor arrays

Cross-sectional measurement of particle velocity and concentration in a pneumatic conveying pipe is desirable for the characterisation of particle flow dynamics and determination of particle mass flow rate. In this study, an inner-inserted electrostatic sensor array consisting of nine pairs of electrodes is implemented to measure the cross-sectional velocity and concentration profiling of particles over the whole cross section in a square-shaped pipe. Experimental tests were conducted on both vertical and horizontal pipe sections on a test rig under dilute conditions with different air velocities and particle mass flow rates. Test results show that the slope-shaped particle concentration profile changes to an arch-shaped one when the particles flow from a horizontal pipe to a vertical one. The particle velocity profile is arch-shaped in both vertical and horizontal pipes. A comparative study of cross-sectional mean particle velocity and concentration measured by the developed electrostatic sensor arrays is conducted.

Accurately Mapping Image Charge and Calibrating Ion Velocity in Charge Detection Mass Spectrometry.

Image charge detection is the foundation of charge detection mass spectrometry (CDMS). The mass-to-charge ratio, m/z, of a highly charged ion or particle is determined by measuring the particle's charge and velocity. Charge is typically determined from a calibrated image charge signal, and the particle velocity is calculated using the peaks from the shaped signal as they relate to the particle position and time-of-flight through a detector of known length. Although much has been done to improve the charge accuracy in CDMS, little has been done to address the inconsistencies in the particle velocity measurements and the interpretation of peak position and effective electrode length. In this work, we combine SIMION ion trajectory software and the Shockley-Ramo theorem to accurately determine the effective electrode length, peak position, and shape of the signal peaks. Six model charge detector geometries were examined with this method and evaluated in laboratory experiments. Experimental results in all cases agreed with the simulations. Using a charge detector with multiple, 12.7 mm-long cylindrical electrodes, experimental velocities across and between electrodes agreed within 0.25% relative standard deviation (RSD) when this method was used to correct for effective electrode lengths, corresponding to an uncertainty in the effective electrode length of only 40 μm. For a detector with multiple electrodes and varied electrode spacing, experiments showed that the peak amplitude and shape vary with the geometry and with the particle path through the detector, whereas all peak areas agreed to within 2.3% RSD. For a charge detector made of two printed circuit boards, the velocities agreed within 0.44% RSD using the calculated effective electrode length.

Experimental Measurement of Particle Velocity in a High Reynolds Micro-channel Flow

The present work is to provide experimental measurements of particle velocity in a microchannel flow at the Reynolds number of 10 and their respective particle positions in the channel where the velocities were measured. The particle position measurements which includes their depths were realized without an intricate optical set-up by controlling the particle path with multiple flow rates. The experimental measurements of particle velocity combined with the position measurements were subsequently used to confirm accuracy of particle velocities numerically estimated by a flow simulation exclusive of particle migration. The numerical estimates and experimental measurements of particle velocity agree with a difference of only less than 5%. The agreement was also supported by a detailed quantification.

High-speed digital in-line holography for in-situ dust cloud characterization in a minimum ignition energy device

Precise measurement of the minimum ignition energy (MIE) of combustible dust is crucial to safety in the process industries. The development of comprehensive methods for MIE dust cloud characterization is therefore highly desirable. The objective of this study is to investigate the application of high-speed digital in-line holography (DIH) for volumetric and in-situ characterization of dust clouds near the ignition zone of a Kühner MIKE3 MIE device. The dispersion behavior of borosilicate glass and soda-lime glass dust clouds are studied at 20 kHz. Size measurements, with successful detection down to 13 μm, are compared with Beckman Coulter particle size analyzer results. The 5-ms hologram videos also yield new transient particle volume, concentration, and velocity measurements. Sample sizes of 15–150 mg of dust powder are sufficient for each high-speed run. This work showcases new diagnostic capabilities that are accessible to dust explosion research and identifies areas for future research.

Dynamics of dust particles confined in imposed potential structures in strongly magnetized, low-temperature plasmas.

A new phenomenon called imposed ordered structures has been of particular interest to the dusty plasma community within the past several years. These structures are a new type of pattern formation within a dusty plasma in which the dust particles become fixed to a background confining potential whose spatial structure is determined by some conducting element present in the plasma. In previous works, this element has typically been a conducting wire mesh. One of the unanswered questions is whether the dust particles become trapped beneath the conducting surface of the mesh or in the gaps (holes) between the wires. This work makes use of a new electrode whose shape is designed to mimic that of wire mesh, but with much larger dimensions to facilitate in situ diagnostic measurements. Observations of the dust show that particles become confined to the regions beneath the holes of this new electrode. Measurements of the dust particle velocities allow for a determination of the kinetic energy within the dust cloud which show that the particles are in an energetic steady state. Comparisons of spatial profiles of the particle velocities also show that the dust particles typically reside in areas of increased plasma glow, possibly being trapped by plasma filaments.

Illuminating the physics of dynamic friction through laboratory earthquakes on thrust faults

Large, destructive earthquakes often propagate along thrust faults including megathrusts. The asymmetric interaction of thrust earthquake ruptures with the free surface leads to sudden variations in fault-normal stress, which affect fault friction. Here, we present full-field experimental measurements of displacements, particle velocities, and stresses that characterize the rupture interaction with the free surface, including the large normal stress reductions. We take advantage of these measurements to investigate the dependence of dynamic friction on transient changes in normal stress, demonstrate that the shear frictional resistance exhibits a significant lag in response to such normal stress variations, and identify a predictive frictional formulation that captures this effect. Properly accounting for this delay is important for simulations of fault slip, ground motion, and associated tsunami excitation.

A Novel Fiber Optic Sensor for Microparticle Velocity Measurement Using Multicore Fiber

A novel fiber optic sensor is proposed to achieve the measurement of single microparticle velocity in a two-dimensional space by translating the cores of a multicore fiber in their respective directions into independent spatial filters. The measurement of particle velocity with the accuracy of better than 2% and direction angles in a range from 0° to 120° is achieved. Compared with the previous method by means of manual-assembled fiber array, the measurement accuracy can be increased by using only one multicore fiber probe with the features of compact size and low cost. The technique has potential particle velocity measurement applications in environmental monitoring, biological study and combustion research.

Electro-exchange in the system of the condensed dispersed phase and a heated titanium particle

The results of studies of titanium particles with diameters from 10 to 100 microns heated above the melting point in air are presented. A diagram and photographs of an experimental facility are shown. It consists of a generator of heated titanium particles, a temperature measurement unit, which includes a photoelectric temperature sensor for moving particles, an electric charge measurement unit, consisting of vertical flat parallel charged metal plates, and a unit for measuring particle velocity. It has been experimentally established that around such particles when they move in air a condensed dispersed phase – c-phase – consisting of titanium oxides nanoparticles is formed. The results of electron microscopy studies of the condensed dispersed phase has shown that the particle size of the condensed dispersed phase lies in the range of 5 - 100 nm and depends on the initial conditions. Theoretical calculations that determine the electro-exchange in the system of a heated spherical particle and the condensed dispersed phase surrounding it has shown the agreement with the experimental data within the measurement error, and the particle charge was on the order of hundreds of thousands – a million of electron charges. A theoretical study of the kinetics of thermionic charging of titanium particles has shown that the accumulation time of 95% of the equilibrium particle charge at temperatures of 3000–2200 K was 14 ns – 33 μs, respectively. At the temperature of 2000 K, the accumulation time of 85% of the equilibrium charge was 240 μs. At the temperature of 1400 K, the accumulation time of 91% of the equilibrium charge of the same particle was 610 μs. Estimates have shown that during a charge relaxation time for a titanium particle at temperatures greater than 1400 K the time of charging practically does not change. This allows us to consider the process of thermionic charging of particles under these conditions as quasistationary. The results can be used in studies of the processes of electro-exchange in aerodispersive systems at high temperatures. The developed model of thermionic charging of particles allows its further use to simulate the behavior of the c-phase around heated particles, as well as for other purposes. The obtained results show a satisfactory agreement between the experimental and calculated values of the charge.

Numerical Modelling of Detonation Reaction Zone of Nitromethane by EXPLO5 Code and Wood and Kirkwood Theory

The detonation reaction zone of nitromethane (NM) has been extensively studied both experimentally and theoretically. The measured particle velocity profile of NM shows the existence of a sharp spike followed by a rapid drop over the first 5-10 ns (fast reaction). The sharp spike is followed by a gradual decrease (slow reactions) which terminate after approximately 50-60 ns when the CJ condition is attained. Based on experimental data, the total reaction zone length is estimated to be around 300 μm. Some experimental observations, such as the reaction zone width and the diameter effect, can be satisfactorily reproduced by numerical modelling, provided an appropriate reaction rate model is known. Here we describe the model for numerical modelling of the steady state detonation of NM. The model is based on the coupling thermochemical code EXPLO5 with the Wood-Kirkwood detonation theory, supplemented with different reaction rate models. The constants in the rate models are calibrated based on experimentally measured particle velocity profiles and the detonation reaction zone width. It was found that the model can describe the experimentally measured total reaction time (width of reaction zone) and the particle velocitytime profile of NM. It was found also that the reaction rate model plays a key role on the shape of the shock wave front. In addition, the model can predict the detonation parameters (D, pCJ, TCJ, VCJ, etc.) and the effect of charge diameter on the detonation parameters.

Cross-Correlation Sensitivity-Based Electrostatic Direct Velocity Tomography

Electrostatic tomography (EST) has been widely used in gas–solid two-phase flows to measure particle velocity in many industrial processes. However, EST is a passive measurement technique, and this results in rare independent measurements compared with other tomographic modalities. In this article, an electrostatic direct velocity tomography (EDVT) method is proposed to increase the number of independent measurements and to improve the accuracy of velocity estimation. For a two-plane electrostatic sensor, the cross-correlation (CC) velocities between the electrodes from the two planes at different circumferential positions can represent the particle velocities in different regions. First, the CC velocities between the electrodes on different planes are calculated and used as new measurements. In this way, the number of independent measurements of a 16-electrode EST sensor can be easily increased from 16 to 120. Second, by analyzing the relationship between the CC velocities and the particle charge and particle velocity distribution, a CC sensitivity matrix is established. Finally, a tomographic model to represent the velocity distribution of charged particles can be established based on the new measurements and the CC sensitivity matrix. Simulation and experimental results show that the velocity distribution reconstructed by EDVT can represent the particle velocity distribution in the pipeline and is promising to provide a method to study the mechanism of gas–solid two-phase flows.

Morphology and volume fraction of biomass particles in a jet flow during devolatilization

Particle size, aspect ratio (AR, defined here as major over minor dimension), orientation and volume fraction have been measured for a stream of pulverized biomass particles undergoing devolatilization. Milling of raw biomass for thermochemical conversion yields elongated particles with high AR. Particle shape affects the heat and mass transfers and motion of particles within a jet, potentially shifting the particle group regimes. Therefore, the effects of carrier gas flow and fuel AR on the devolatilization behavior of biomass particles streams have been addressed experimentally. Two shapes of dried Norwegian Spruce have been used: one nearly equant (AR = 1.8 ± 0.64) and the other elongated (AR = 3.8 ± 2.9), both derived from the same sieve size of 200–250 μm. Experiments were performed in a laboratory-scale flat-flame assisted laminar drop tube reactor, where similar mass flows of particles (10–16 g⋅h−1) were injected with two different flow rates of CO2 to a high temperature flame zone (methane flame at O2-to-fuel equivalence ratio of λ = 0.63). Time and space-averaged measurements of particle morphology and velocity during conversion were obtained with 2D particle tracking velocimetry (PTV) together with image analysis. Carrier gas flow acted as thermal ballast, affecting the heating rate to the gas and particles. Heterogeneity in morphological changes was observed, and the behavior was affected by heating rate, particle shape and carrier gas flows. This paper describes phenomena relevant for the understanding of biomass devolatilization under very fast heating rates, such as shrinking, transient swelling, spherodization and lateral migration, and relates them to differences in heating rate and particle shape.

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

A method to determine the depth of detection (DOD) for particle shadow tracking velocimetry (PSTV) is presented. In contrast with other image-based velocimetry techniques, PSTV is capable of measuring particle velocity in a volume of the flow. However, a precise methodology to determine the size of the measurement volume was not available (in particular, for internal flows in tubes with circular cross sections). To correct this shortcoming, we determined the range of distances in which the particles could be clearly identified. This was accomplished by displacing a calibration target across the camera’s field of view and by implementing appropriate filtering algorithms. The method was tested with a polydispersed gas-particle flow inside a tube. We found that the significantly improved particle count resulted in an unbiased statistical convergence of the data. .

67P/Churyumov–Gerasimenko’s dust activity from pre- to post-perihelion as detected by Rosetta/GIADA

ABSTRACT We characterized the 67P/Churyumov–Gerasimenko’s dust activity, by analysing individual dust particle velocity and momentum measurements of Grain Impact Analyser and Dust Accumulator (GIADA), the dust detector onboard the ESA/Rosetta spacecraft, collecting dust from tens to hundreds of kilometres from the nucleus. Specifically, we developed a procedure to trace back the motion of dust particles down to the nucleus, identifying the surface’s region ejecting each dust particle. This procedure has been developed and validated for the first part of the mission by Longobardo et al. and was extended to the entire GIADA data set in this work. The results based on this technique allowed us to investigate the link between the dust porosity (fluffy/compact) and the morphology of the ejecting surface (rough/smooth). We found that fluffy and compact particles, despite the lack of correlation in their coma spatial distribution (at large nucleocentric distances) induced by their different velocities, have common ejection regions. In particular, the correlation between the distributions of fluffy and compact particles is maintained up to an altitude of about 10 km. Fluffy particles are more abundant in rough terrains. This could be the result of past cometary activity that resurfaced the smooth terrains and/or of the comet formation process that stored the fluffy particles inside the voids between the pebbles. The variation of fluffy particle concentration between rough and smooth terrains agrees with predictions of comet formation models. Finally, no correlation between dust distribution on the nucleus and surface thermal properties was found.

Particle velocity measurement of binary mixtures in the riser of a circulating fluidized bed by the combined use of electrostatic sensing and high-speed imaging

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.

Design and application of an algorithm for measuring particle velocity based on multiple characteristics of a particle

During the post-processing of PIA images, correctly pairing the particles in two frames is the basic premise underlying the accurate measurement of particle velocity. The traditional particle pairing algorithm is designed according to the characteristics of particle morphology, but this method could result in a considerable number of wrong pairings when dealing with areas having particles of large density and similar shape, thus, calculate the particle velocities incorrectly. In this paper, the behavior characteristics of particles are analysed, and a new particle pairing algorithm based on multiple characteristics of a particle is proposed. In this algorithm, the similarities of basic particle features, adjacent particle motion directions and particle neighbourhood space are considered and analysed. A brand-new formula is established to calculate the overall feature similarity of the pairing particle and each searching particle. After the particles in two frames are paired, the particle velocities can be calculated. In this paper, the new algorithm was used to measure the particle velocity under high ambient pressure and cross flow respectively. The particle velocity is similarly to normally distribution. In D(40), the particles with the velocity of 0.8–0.9 m/s are the most, and in D(60), the particles with velocity of 1.6–1.7 m/s are the most, The mean velocity of particles at C(10,25) is 60.07 m/s. In C(20,50), the mean particle velocity is 52.01 m/s. The experimental results show that the new algorithm has a high precision rate of particle pairing, and can accurately measure particle velocities under different experimental conditions.

Numerical Simulation of the Fluid–Solid Coupling Mechanism of Internal Erosion in Granular Soil

Internal erosion involves migration and loss of soil particles due to seepage. The process of fluid–solid interaction is a complex multiphase, coupled nonlinear dynamic problem. In this study, we used Particle Flow Code (PFC3D, three-dimensional PFC) software to model solid particles, and we applied computational fluid dynamics (CFD) and the coarse mesh element method to solve the local Navier–Stokes equations. An information-exchange process for the PFC3D and CFD calculations was used to achieve fluid–solid coupling. We developed a numerical model for internal erosion of the soil and conducted relevant experiments to verify the usability of the numerical model. The mechanism of internal erosion was observed by analyzing the evolution of model particle migration, contact force, porosity, particle velocity, and mass-loss measurement. Moreover, we provide some ideas for improving the calculation efficiency of the model. This model can be used to predict the initiation hydraulic gradient and skeleton-deformation hydraulic gradient, which can be used for the design of internal erosion control.