STRANGE NUMBERS FOUND IN PARTICLE COLLISIONS

Keyword(s):  
2010 ◽  
Vol 20 (1) ◽  
pp. 31-40 ◽  
Author(s):  
Shengdong Gao ◽  
Udo Fritsching
Keyword(s):  

2021 ◽  
Vol 87 (3) ◽  
Author(s):  
R.A. López ◽  
S.M. Shaaban ◽  
M. Lazar

Space plasmas are known to be out of (local) thermodynamic equilibrium, as observations show direct or indirect evidences of non-thermal velocity distributions of plasma particles. Prominent are the anisotropies relative to the magnetic field, anisotropic temperatures, field-aligned beams or drifting populations, but also, the suprathermal populations enhancing the high-energy tails of the observed distributions. Drifting bi-Kappa distribution functions can provide a good representation of these features and enable for a kinetic fundamental description of the dispersion and stability of these collision-poor plasmas, where particle–particle collisions are rare but wave–particle interactions appear to play a dominant role in the dynamics. In the present paper we derive the full set of components of the dispersion tensor for magnetized plasma populations modelled by drifting bi-Kappa distributions. A new solver called DIS-K (DIspersion Solver for Kappa plasmas) is proposed to solve numerically the dispersion relations of high complexity. The solver is validated by comparing with the damped and unstable wave solutions obtained with other codes, operating in the limits of drifting Maxwellian and non-drifting Kappa models. These new theoretical tools enable more realistic characterizations, both analytical and numerical, of wave fluctuations and instabilities in complex kinetic configurations measured in-situ in space plasmas.


Author(s):  
Marion W. Vance ◽  
Kyle D. Squires

An approach to parallel solution of an Eulerian-Lagrangian model of dilute gas-solid flows is presented. Using Lagrangian treatments for the dispersed phase, one of the principal computational challenges arises in models in which inter-particle interactions are taken into account. Deterministic treatment of particle-particle collisions in the present work pose the most computationally intensive aspect of the simulation. Simple searches lead to algorithms whose cost is O(N2p) where Np is the particle population. The approach developed in the current effort is based on localizing collision detection neighborhoods using a cell-index method and spatially distributing those neighborhoods for parallel solution. The method is evaluated using simulations of the gas-solid turbulent flow in a vertical channel. The instantaneous position and the velocity of any particle is obtained by solving the equation of motion for a small rigid sphere assuming that the resulting force induced by the fluid reduces to the drag contribution. Binary particle collisions without energy dissipation or inter-particle friction are considered. The carrier flow is computed using Large Eddy Simulation of the incompressible Navier-Stokes equations. The entire dispersed-phase population is partitioned via static spatial decomposition of the domain to maximize parallel efficiency. Simulations on small numbers of distributed memory processors show linear speedup in processing of the collision detection step and nearly optimal reductions in simulation time for the entire solution.


Author(s):  
H. Nasr ◽  
G. Ahmadi ◽  
J. B. McLaughlin

This study is concerned with the effect of inter particle collisions on the particle concentration in turbulent duct flows. The time history of the instantaneous turbulent velocity vector was generated by the two-way coupled direct numerical simulation (DNS) of the Navier-Stokes equation via a pseudospectral method. The particle equation of motion included the Stokes drag, the Saffman lift, and the gravitational forces. The effect of particles on the flow is included in the analysis via a feedback force on the grid points. Several simulations for three classes of particles (28 μm Lycopodia, 50μm glass and 70μm copper) and different mass loadings were performed, and the effect of inter particle collisions on the particle concentration was evaluated and discussed. It was found that the particle-particle collisions reduce the tendency of particles to accumulate near the wall. This might be because collisions decorrelate particles with coherent eddies which are responsible for accumulation of particles near the wall. The spatial distribution of particles at the channel centerplane was compared with the experimental results of Fessler et al. (1994). The simulation results showed that the copper and glass particles had a random distribution while Lycopodium particles showed a non-random distribution with bands of particles that were preferentially concentrated.


2017 ◽  
Vol 27 (1) ◽  
pp. 181-194 ◽  
Author(s):  
Yiran Xue ◽  
Peng Liu ◽  
Ye Tao ◽  
Xianglong Tang

Abstract In the field of intelligent crowd video analysis, the prediction of abnormal events in dense crowds is a well-known and challenging problem. By analysing crowd particle collisions and characteristics of individuals in a crowd to follow the general trend of motion, a purpose-driven lattice Boltzmann model (LBM) is proposed. The collision effect in the proposed method is measured according to the variation in crowd particle numbers in the image nodes; characteristics of the crowd following a general trend are incorporated by adjusting the particle directions. The model predicts dense crowd abnormal events in different intervals through iterations of simultaneous streaming and collision steps. Few initial frames of a video are needed to initialize the proposed model and no training procedure is required. Experimental results show that our purpose-driven LBM performs better than most state-of-the-art methods.


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