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Particles LaGrangian tracking

In this approach, the particle equation of motion is solved, mostly in a precalculated gas flow field. The particle position and velocity are calculated after successive short time intervals, and in this way the particle is tracked through the cyclone or swirl tube. [Pg.148]

Once the particle enters a particular cell with a given velocity relative to the gas UIq, for instance), its velocity after a short time interval At can be calculated from Eq. (2.2.5)  [Pg.148]

Knowing the gas velocity in the cell, the absolute particle velocity can be calculated from its velocity relative to the gas. The position of the particle after At can also be calculated by integrating the absolute particle velocity over At, since the distance traveled equals U dt. [Pg.148]


P 62] A Lagrangian particle tracking technique, i.e. the computation of trajectories of massless tracer particles, which allows the computation of interfacial stretching factors, was coupled to CFD simulation [47]. Some calculations concerning the residence time distribution were also performed. A constant, uniform velocity and pressure were applied at the inlet and outlet, respectively. The existence of a fully developed flow without any noticeable effect of the inlet and outlet boundaries was assured by inspection of the computed flow fields obtained in the third mixer segment for all Reynolds numbers under study. [Pg.194]

J. H. Dunn and S. G. Lambrakos, Calculating Complex Interactions in Molecular Dynamics Simulations Employing Lagrangian Particle Tracking Schemes, J. Comput. Phys., Ill (1994), 15-23. [Pg.275]

Eulerian grid box or Lagrangian particle tracking methods using turbulence models (not suitable for real time emergency response computation), above canopy. Input from obstacle or continuum scale data (for local sources). Upwind data for distant sources. [Pg.54]

Before we finish this subsection, we would like to discuss the practical limitations of the Poincare sections, which require Lagrangian particle tracking for extended times. In reality. Fig. 2 presents stroboscopic images of the same four particles passing through thousands of mixing block boundaries. This has two basic implications. First, numerical calculation of the Poincare sections requires either analytical solutions or high-order accurate discretizations of the velocity field. Otherwise, the results may suffer from numerical diffusion and dispersion errors, and the KAM boundaries may not be identified accurately. Second, it is experimentally difficult, if not impossible, to track particles (in three-dimensions) beyond a certain distance allowed by the field of view of the microscopy technique. Despite these... [Pg.264]

Figure 3.16 Comparison of the confocal micrographs of Stroock et al. [58] (left) with the Poincare sections obtained from Lagrangian particle tracking by Kang and Kwon [60] (right). Figure 3.16 Comparison of the confocal micrographs of Stroock et al. [58] (left) with the Poincare sections obtained from Lagrangian particle tracking by Kang and Kwon [60] (right).
The analysis of mass transfer based on Lagrangian particle tracking has shown that for suitable values of the pressure excitation amplitude and frequency chaotic mixing is induced [63]. [Pg.57]

To analyze the individual heat transfer kinetics of droplet clusters within the spray of twin-fluid atomizers, the local correlations between the droplet concentration and the heat and flow conditions are evaluated. Numerical simulations of the spray flow analyzed in this paper have been carried out with Large-Eddy-Simulation (LES) models with Lagrangian particle tracking (discrete particle method) for the droplet motion. A synthetic perturbation generator [30] for the inflow conditions for the gas flow and simple perturbations are added to the dispersed phase to induce realistic vortex patterns at the nozzle and in the consequent spray. [Pg.754]

In order to investigate the influence of the numerical settings on this phenomenon, the two-way coupling parameters were checked. The droplet concentration density was varied systematically and the number of iterations per time step for the continuous phase and the number of inner iterations for the Lagrangian particle tracking have been increased. Despite these measures, which increased the computational demand by a factor of about 10, the same tendency for the relative velocity and the temperature difference could be detected. [Pg.790]

The flow of the particles was studied by Lagrangian particle tracking as... [Pg.151]

This is a standard technique in Lagrangian particle tracking in order to reduce the number of trackings necessary... [Pg.156]


See other pages where Particles LaGrangian tracking is mentioned: [Pg.177]    [Pg.509]    [Pg.56]    [Pg.22]    [Pg.260]    [Pg.270]    [Pg.196]    [Pg.196]    [Pg.54]    [Pg.54]    [Pg.55]    [Pg.56]    [Pg.57]    [Pg.57]    [Pg.57]    [Pg.65]    [Pg.680]    [Pg.827]    [Pg.134]    [Pg.190]    [Pg.141]    [Pg.271]    [Pg.326]    [Pg.775]    [Pg.1344]    [Pg.35]    [Pg.139]    [Pg.148]    [Pg.148]    [Pg.149]    [Pg.49]   
See also in sourсe #XX -- [ Pg.196 ]

See also in sourсe #XX -- [ Pg.55 ]




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