Model Of Particle Motion Research Articles

OS0201 微粒子ピーニングにおける投射粒子挙動の観察

A large number of tiny particles hit the specimen to improve the mechanical properties of treated materials in Fine Particle Peening (FPP) process. The induced surface modification is influenced by many parameters such as material properties, particle size, particle amount, air pressure and so on. Especially, it is well known that particle velocity significantly influences the results of surface modification. Thus, we focused on the particle velocity and measured it by a high-speed camera. Also, we developed the model of particle motion by considering the effect of jet flow and calculated the particle velocity after spouting from the nozzle. Then, we compared the experimental results with the calculated results and those agreed well each other. It is concluded that the particle velocity can be estimated by our proposed model and it is helpful information when one decides the process condition on FPP treatment.

Adapting Data Processing To Compare Model and Experiment Accurately: A Discrete Element Model and Magnetic Resonance Measurements of a 3D Cylindrical Fluidized Bed.

Discrete element modeling is being used increasingly to simulate flow in fluidized beds. These models require complex measurement techniques to provide validation for the approximations inherent in the model. This paper introduces the idea of modeling the experiment to ensure that the validation is accurate. Specifically, a 3D, cylindrical gas-fluidized bed was simulated using a discrete element model (DEM) for particle motion coupled with computational fluid dynamics (CFD) to describe the flow of gas. The results for time-averaged, axial velocity during bubbling fluidization were compared with those from magnetic resonance (MR) experiments made on the bed. The DEM-CFD data were postprocessed with various methods to produce time-averaged velocity maps for comparison with the MR results, including a method which closely matched the pulse sequence and data processing procedure used in the MR experiments. The DEM-CFD results processed with the MR-type time-averaging closely matched experimental MR results, validating the DEM-CFD model. Analysis of different averaging procedures confirmed that MR time-averages of dynamic systems correspond to particle-weighted averaging, rather than frame-weighted averaging, and also demonstrated that the use of Gaussian slices in MR imaging of dynamic systems is valid.

A comprehensive model of magnetic particle motion during magnetic drug targeting

Magnetic drug targeting (MDT) is a noninvasive medical technique that has been proposed for treating localized diseases. An ideal treatment would involve chemically binding the drug to magnetic particles, injecting the particles into the bloodstream, magnetically steering them through the arterial network, and trapping them near the diseased area. With the goal of understanding and optimizing magnetic particle control, a model was developed to describe the motion of a cluster of small magnetic particles in blood. All forces expected to significantly affect the particles were incorporated, including interparticle magnetic force, dispersion due to collisions between particles and blood cells, and complex viscous force accounting for the shear thinning nature of blood. The model was used to simulate the motion of a cluster of particles in two artery-inspired geometries: a straight tube and an asymmetric bifurcation. The results showed that it is possible to slow down a particle cluster in a straight tube but not stop it completely. Particle diffusion plays a key role in limiting the magnetic control effectiveness. Steering the cluster down a selected branch of a bifurcation is more successful. Practical magnetic field gradients can produce large increases in the probability that particles will enter the desired branch.

Multiple Hypothesis Tracking for Cluttered Biological Image Sequences

In this paper, we present a method for simultaneously tracking thousands of targets in biological image sequences, which is of major importance in modern biology. The complexity and inherent randomness of the problem lead us to propose a unified probabilistic framework for tracking biological particles in microscope images. The framework includes realistic models of particle motion and existence and of fluorescence image features. For the track extraction process per se, the very cluttered conditions motivate the adoption of a multiframe approach that enforces tracking decision robustness to poor imaging conditions and to random target movements. We tackle the large-scale nature of the problem by adapting the multiple hypothesis tracking algorithm to the proposed framework, resulting in a method with a favorable tradeoff between the model complexity and the computational cost of the tracking procedure. When compared to the state-of-the-art tracking techniques for bioimaging, the proposed algorithm is shown to be the only method providing high-quality results despite the critically poor imaging conditions and the dense target presence. We thus demonstrate the benefits of advanced Bayesian tracking techniques for the accurate computational modeling of dynamical biological processes, which is promising for further developments in this domain.

The model of particle motion in a magnetic hydrocyclone

The model of curvilinear motion of particles in a hydrocyclone with a radial magnetic field. As the force acting on the particle considered the following: the centrifugal force, drag force, including taking into account changes of drag coefficient from the walls of the cyclone, the magnetic force, the gravitational force, the Archimedes force, the lift force acting on a rotating particle (the Magnus effect); lifting force, which arises due to the shift of the field of fluid flow (Saffman force), the force generated an additional (virtual) weight, the traction force generated by the pressure gradient; Basset force which arises due to the delay of the boundary layer of the liquid at the change of the relative velocity particles. The analysis of forces is contained numerical formulas for calculating them and images; allocated the forces which have significant effect in the dynamics of a particle. The model is based on the Lagrange approach and is made in a cylindrical coordinate system. The numerical solution of systems of differential equations, performed with use of the program MathCAD.

Application of POD-based dynamical systems to dispersion and deposition of particles in turbulent channel flow

This paper concerns the numerical modeling of heavy particle motion in a turbulent flow. Instantaneous fluid velocity is simulated by low-order dynamical systems based on Proper Orthogonal Decomposition (POD), or the eigenfunction expansion, which is a mathematical tool that can be used to identify the most energetic structures of the flow. The POD basis was built using two-point velocity correlations obtained from the Direct Numerical Simulation (DNS) of a channel flow. In addition to the two proposals already described from the literature, a new dynamical system with considerably less modes was constructed. The dynamical systems were assessed by comparing the resulting fluid velocity statistics with the DNS data. The Lagrangian approach was used to track inertial particles, which were one-way coupled to the velocity field generated by these dynamical systems. In the dispersion study, where the particles are allowed to collide elastically with the walls, the particle number density profiles and velocity statistics were compared to the available DNS benchmark. In the case of particle wall separation, the results for deposition velocity were evaluated with experimental data. The characteristic features of the POD-based simulations of dispersed turbulent flows are shown, potential areas of application are suggested, and the limitations of the approach are discussed.

Direct numerical simulation of sediment entrainment in turbulent channel flow

In this paper, the entrainment and movement of coarse particles on the bed of an open channel is numerically investigated. Rather than model the sediment transport using a concentration concept, this study treats the sediment as individual particles and investigates the interaction between turbulent coherent structures and particle entrainment. The applied methodology is a combination of the direct numerical simulation of turbulent flow, the combined finite-discrete element modeling of particle motion and collision, and the immersed boundary method for the fluid-solid interaction. In this study, flow over a water-worked rough-bed consisting of 2-3 layers of densely packed spheres is adopted and the Shields function is 0.065 which is just above the entrainment threshold to give a bed-load regime. Numerical results for turbulent flow, sediment entrainment statistics, hydrodynamic forces acting on the particles, and the interaction between turbulence coherent structures and particle entrainment are presented. It is shown that the presence of entrained particles significantly modifies the mean velocity and turbulence quantity profiles in the vicinity of a rough-bed and that the instantaneous lift force can be larger than a particle's submerged weight in a narrow region above the effective bed location, although the mean lift force is always smaller than the submerged weight. This, from a hydrodynamic point of view, presents strong evidence for a close cause-and-effect relationship between coherent structures and sediment entrainment. Furthermore, instantaneous numerical results on particle entrainment and the surrounding turbulent flow are reported which show a strong correlation between sediment entrainment and sweep events and the underlying mechanisms are discussed.

Turbulence effects on the granular model of particle motion in a boundary layer flow

AbstractPrediction of particle velocity in a dilute turbulent gas–particle flow nearby a flat solid boundary is investigated numerically using a fully Eulerian two‐fluid model. The particulate phase model is based on the kinetic theory of granular flow. The turbulence in both phases is modelled. Inter‐particle and particle‐wall inelastic collisions are considered. Effects of presence/absence of particulate phase turbulence modelling on velocity of particles are investigated. Results indicate that turbulence modelling is necessary for particulate phase, but conventional models should be modified to consider particulate flow nature. Effects of free stream velocity and particle diameter on turbulence modelling results have been discussed.

The aerosol particle collision kernel considering the fractal model of particle motion

A method is presented in which the fractal model of particle motion, distinct from the Langevin equation of motion, has been used to determine the collision kernel of particles. The collision kernels, valid in the continuum and free molecular regions, are reformulated to be dependent on one sixth of the mean square displacement of a particle divided by time instead of diffusion coefficient and the root mean square displacement divided by time instead of the mean velocity. One generalized formula for collision kernels in the transition regime is obtained by equating the two expressions for kernels. The approaching time is calculated using equation describing the particle trajectory. For condensation and monodisperse aggregation the calculated collision kernel is the harmonic average of limiting kernels valid in continuum and free molecular regimes. It is in agreement with the experimentally verified formula of Fuchs–Sutugin. The results for polydisperse aggregation are close to those obtained by the widely accepted method of Fuchs. The obtained formula can also be used to approximate the drag force on particles in the transition regime.

Computer model of particle motion in the chopping unit

Influence of cutting angles of plain knifes and under-knife blocks setting on particle descent angle and specific energy intensity of chopping was estimated with the help of computer model. Findings of investigation are given.

On the construction of effective metrics in a relational model of space-time

Within the scope of the relational model of spacetime developed by Yu.S. Vladimirov, we consider a toy model of test particle motion in an effective gravitational field described in terms of the modified Fokker-Feynman-Wheeler direct particle interaction formalism. It is shown that an agreement with the classical GR result (perihelion shift of a planetary orbit) can be obtained in the minimal nonlinear approximation in G under some simple assumptions.

Particle trajectories in a four rod crab cavity

As part of the HL-LHC upgrade it is planned that crab cavities will be installed into the machine to control and increase the luminosity. Of crucial importance to the dynamics of crab cavities in the LHC machine is the modelling of the particle motion through the cavity structure, which, in some studies, has been done using thin lens kicks derived from a thin lens Hamiltonian. In this paper we study particle trajectories using field fitted vector potentials in the four rod crab cavity and make a comparison to the dynamics generated using the thin lens model.

Particle dynamics in cyclone tribochargers

Triboelectric separation is of increasing importance in a number of industries. The initial tribocharging process is poorly understood, with tribocharger design and operation dominated by trial and error. Better physical understanding of tribocharger operation would be invaluable for the optimization of triboelectric separation processes. Cylindrical pneumatic cyclones are highly suitable for continuous-flow mineral separation applications. Charge measurements, trajectory modelling and high-speed video footage of particle motion have been combined to understand charging in terms of particle dynamics in a cylindrical cyclone. These observations are interpreted in terms of cyclone tribocharger design and operation.

Direct particle motion and interaction modeling method applied to simulate propellant burn

A direct particle motion and particle interaction modeling method was developed to provide an alternative means of capturing the fundamental phenomena occurring during the burning of propellant grains. Individual propellant grains and other moving components are directly incorporated into the computational domain, removing the need for correlations for particle drag and interaction effects. The motion of the individual particles is calculated from the locally acting fluid induced and collision effect forces and moments. Particle/object interactions are handled through a soft particle collision algorithm. Localized mass and energy sources, accompanied by a shrinking particle size, simulate the effects of the combustion process.The method is applied to the burning of propellant in a two-dimensional planar gun type system. Parametric studies were performed varying the parameters related to the propellant and projectile to explore the capabilities of the current modeling method and to determine the sensitivity of the gas, propellant, and projectile conditions. The model captured the local pressure waves moving between the breech and the bullet base not observed using a bulk effect model. The results also indicated that the conditions in the system that are most sensitive to the burn rate exponent where a 24% increase in the exponent produced a 200% increase in the peak pressure at the breech. The study demonstrated the utility of this new model in exploring in particular the localized phenomena and conditions that develop during the burning of propellant.

Optimal tracking of a Brownian particle

Optical tracking of a fluorescent particle in solution faces fundamental constraints due to Brownian motion, diffraction, and photon shot noise. Background photons and imperfect tracking apparatus further degrade tracking precision. Here we use a model of particle motion to combine information from multiple time-points to improve the localization precision. We derive successive approximations that enable real-time particle tracking with well controlled tradeoffs between precision and computational cost. We present the theory in the context of feedback electrokinetic trapping, though the results apply to optical tracking of any particle subject to diffusion and drift. We use numerical simulations and experimental data to validate the algorithms' performance.

Mathematical Modeling of Mixing and Flow Phenomena of Municipal Solid Waste on the Grate

The recovery of energy from the municipal solid wastes (MSW) is an effective process for the large-scale MSW, the mixing and flow of MSW particles on the grate impact the combustion efficiency in combustion chamber. The travel of MSW on the grate depends on the physical characteristics of the solid wastes and the grate properties. The MSW is a more complex and non-homogeneous, so it is difficult to simulate the particle motion by mathematical model based on contact theory. The MSW particle motion model based on the Markov chain of stochastic process for new type forward-reverse acting grate is built and simulated the MSW particle motion in computer by MATLAB 7 in this paper according to the full-scale experiment. The computer simulation and experimental results suggest that the degree of the forward acting grate inclining to horizontal has an effect on the flow and mixing of the MSW particles.

Hydrodynamics of the motion of spherical particles, droplets, and bubbles in a non-Newtonian liquid: Analytical methods of investigation

This work provides a review of the development of concepts and approaches used in the analytical modeling of particle motion in non-Newtonian liquids, copvering the period between the late 1950s and the present time. The logical interpretation of the results obtained with respect to whether they correspond to the physical essence of the phenomenon or process under consideration is given. Special attention is paid to analyzing the rheological models of non-Newtonian media and their effect on the calculation results.

A New Framework for Particle Detection in Low-SNR Fluorescence Live-Cell Images and Its Application for Improved Particle Tracking

Image denoising and signal enhancement are two common steps to improve particle contrast for detection in low-signal-to-noise ratio (SNR) fluorescence live-cell images. However, denoising may oversmooth features of interest, particularly weak features, leading to false negative detection. Here, we propose a robust framework for particle detection in which image denoising in the grayscale image is not needed, so avoiding image oversmoothing. A key to our approach is the new development of a particle enhancement filter based on the recently proposed particle probability image to obtain significantly enhanced particle features and greatly suppressed background in low-SNR and low-contrast environments. The new detection method is formed by combining foreground and background markers with watershed transform operating in both particle probability and grayscale spaces; dynamical switchings between the two spaces can optimally make use the information in images for accurate determination of particle position, size, and intensity. We further develop the interacting multiple mode filter for particle motion modeling and data association by incorporating the extra information obtained from our particle detector to enhance the efficiency of multiple particle tracking. We find that our methods lead to significant improvements in particle detection and tracking efficiency in fluorescence live-cell applications.

Investigations on the Trajectory of Large Sandbags in Open Channel Flow

AbstractInvestigations undertaken to understand the mechanics of the motion of large sandbags and to compute their trajectories are reported in this paper, along with the details of the experimental setup and procedures. The motion of sandbags is recorded from the side of a flume by a high-definition charge-coupled device (CCD) camera, and the digital particle tracking velocimetry (DPTV) technique is used to track the motion of the bags. An equation is developed for the normalized maximum horizontal settling distance from the experimental data. It is found that the particle velocity normal to the flow depends mainly on the characteristic diameter of the particle and the Froude number of the flow, whereas the particle velocity in the streamwise direction shows lower dependency on the Froude number. Analysis of the particle tumbling shows that the Magnus force may be neglected for the purpose of modeling the trajectories of sandbags in uniform flows. A model of particle motion is developed by solving the La...

Simulation for the Microstructure and Rheology in Bidisperse Magnetorheological Fluids

There are many ferromagnetic particles dispersed in carrier oil in magnetorheological fluids. Assuming Newtonian motion, the forces between particles of different radius, including magnetic interaction, viscous force and contact interaction, are obtained, and the corresponding model for motion of particles is proposed. Under an external magnetic field, the microstructures in bidisperse magnetorheological fluids are simulated, and the mechanical properties under both external magnetic field and macroscopic shear strain are investigated. The influence of attached particles on the side of dipolar chains is analyzed. It shows that particle size ratio in bidisperse suspensions can influence the performance of MR fluids.