Direct simulation of particle dispersion in a decaying isotropic turbulence

1992 ◽  
Vol 242 ◽  
pp. 655-700 ◽  
Author(s):  
S. Elghobashi ◽  
G. C. Truesdell
Keyword(s):  
Particle Motion ◽  
Isotropic Turbulence ◽  
Particle Dispersion ◽  
Time Development ◽  
Solid Particles ◽  
Mean Square ◽  
Lagrangian Velocity ◽  
The Mean ◽  
Simulation Results ◽  
Surrounding Fluid

Dispersion of solid particles in decaying isotropic turbulence is studied numerically. The three-dimensional, time-dependent velocity field of a homogeneous, non-stationary turbulence was computed using the method of direct numerical simulation (DNS). A numerical grid containing 963 points was sufficient to resolve the turbulent motion at the Kolmogorov lengthscale for a range of microscale Reynolds numbers starting from Rλ = 25 and decaying to Rλ = 16. The dispersion characteristics of three different solid particles (corn, copper and glass) injected in the flow, were obtained by integrating the complete equation of particle motion along the instantaneous trajectories of 223 particles for each particle type, and then performing ensemble averaging. The three different particles are those used by Snyder & Lumley (1971), referred to throughout the paper as SL, in their pioneering wind-tunnel experiment. Good agreement was achieved between our DNS results and the measured time development of the mean-square displacement of the particles.The simulation results also include the time development of the mean-square relative velocity of the particles, the Lagrangian velocity autocorrelation and the turbulent diffusivity of the particles and fluid points. The Lagrangian velocity frequency spectra of the particles and their surrounding fluid, as well as the time development of all the forces acting on one particle are also presented. In order to distinguish between the effects of inertia and gravity on the dispersion statistics we compare the results of simulations made with and without the buoyancy force included in the particle motion equation. A summary of the significant results is provided in §7 of the paper.The main objective of the paper is to enhance the understanding of the physics of particle dispersion in a simple turbulent flow by examining the simulation results described above and answering the questions of how and why the dispersion statistics of a solid particle differ from those of its corresponding fluid point and surrounding fluid and what influences inertia and gravity have on these statistics.

Optical studies on the turbulent motion of solid particles in a pipe flow

1991 ◽  
Vol 231 ◽  
pp. 665-688 ◽  
Author(s):  
James B. Young ◽  
Thomas J. Hanratty
Keyword(s):  
Diffusion Coefficient ◽  
Particle Velocity ◽  
Turbulent Diffusion ◽  
Slip Velocity ◽  
Rate Of Change ◽  
Solid Particles ◽  
Mean Square ◽  
Turbulent Diffusion Coefficient ◽  
Fluid Turbulence ◽  
The Mean

An extension of an axial viewing optical technique (first used by Lee, Adrian & Hanratty) is described which allows the determination of the turbulence characteristics of solid particles being transported by water in a pipe. Measurements are presented of the mean radial velocity, the mean rate of change radial velocity, the mean-square of the radial and circumferential fluctuations, the Eulerian turbulent diffusion coefficient, and the Lagrangian turbulent diffusion coefficient. A particular focus is to explore the influence of slip velocity for particles which have small time constants. It is found that with increasing slip velocity the magnitude of the turbulent velocity fluctuations remains unchanged but that the turbulent diffusivity decreases. The measurements of the average rate of change of particle velocity are consistent with the notion that particles move from regions of high fluid turbulence to regions of low fluid turbulence. Measurements of the root-mean-square of the fluctuations of the rate of change of particle velocity allow an estimation of the average magnitude of the particle slip in a highly turbulent flow, which needs to be known to analyse the motion of particles not experiencing a Stokes drag.

Study about influence of doors’ opening degree on crowd evacuation based on simulation

2019 ◽  
Vol 30 (11) ◽  
pp. 1950096
Author(s):  
Yuanchun Ding ◽  
Falu Weng ◽  
Lizhong Yang
Keyword(s):  
Linear Relationship ◽  
Flow Rate ◽  
Saving Rate ◽  
Mean Square ◽  
Mean Flow ◽  
Time Saving ◽  
Evacuation Time ◽  
Crowd Evacuation ◽  
The Mean ◽  
Simulation Results

Based on simulation, the influence of the doors’ opening degree (DOD) on crowd evacuation is investigated in this paper. First of all, an evacuation model, which has one exit with two doors, is established by utilizing the software Pathfinder. Then, based on the obtained model, some evacuation scenarios are considered. The simulation results indicate, when the DOD is within 115∘–135∘, the time saving rate is more than 13%, and the maximum time saving rate is achieved when the DOD is 125∘. Furthermore, there is a linear relationship between the mean square error and the number of the evacuees. For a small number of evacuees, the total evacuation time is mainly influenced by the distributions of the evacuees, however, as the number of the evacuees increases, it is mainly influenced by the number of the evacuees. Moreover, when the DOD is 125∘, the mean flow rate per unit width (MFRPUW) decreases along with the increasing of exit’s width, however, it increases along with the increasing of exit’s width while the DOD is 180∘. Compared with the 180∘ DOD, the 125∘ DOD can always achieve a higher MFRPUW, and the narrower the exit is, the higher MFRPUW the 125∘ DOD achieves.

scholarly journals Vertical dispersion by stratified turbulence

2008 ◽  
Vol 614 ◽  
pp. 303-314 ◽  
Author(s):  
E. LINDBORG ◽  
G. BRETHOUWER
Keyword(s):  
Cox Model ◽  
Mean Square Displacement ◽  
Particle Dispersion ◽  
Unit Mass ◽  
Finite Limit ◽  
Mean Square ◽  
Stratified Turbulence ◽  
Vertical Diffusion ◽  
The Mean ◽  
Decaying Turbulence

We derive a relation for the growth of the mean square of vertical displacements, δz, of fluid particles of stratified turbulence. In the case of freely decaying turbulence, we find that for large times 〈δz2〉 goes to a constant value 2(EP(0) + aE(0))/N2, where EP(0) and E(0) are the initial mean potential and total turbulent energy per unit mass, respectively, a < 1 and N is the Brunt–Väisälä frequency. In the case of stationary turbulence, we find that 〈δz2〉 = 〈δb2〉/N2 + 2εPt/N2, where εP is the mean dissipation of turbulent potential energy per unit mass and 〈δb2〉 is the Lagrangian structure function of normalized buoyancy fluctuations. The first term is the same as that obtained in the case of adiabatic fluid particle dispersion. This term goes to the finite limit 4EP/N2 as t → ∞. Assuming that the second term represents irreversible mixing, we show that the Osborn & Cox model for vertical diffusion is retained. In the case where the motion is dominated by a turbulent cascade with an eddy turnover time T ≫ N−1, rather than linear gravity waves, we suggest that there is a range of time scales, t, between N−1 and T, where 〈δb2〉 = 2πCPLεPt, where CPL is a constant of the order of unity. This means that for such motion the ratio between the adiabatic and the diabatic mean-square displacement is universal and equal to πCPL in this range. Comparing this result with observations, we make the estimate CPL ≈ 3.

Parameters Selection and Application of LS-SVM Based on Chaotic Ant Swarm Algorithm

2011 ◽  
Vol 204-210 ◽  
pp. 423-426
Author(s):  
Chun Li Xie ◽  
Dan Dan Zhao ◽  
Juan Wang ◽  
Cheng Shao
Keyword(s):  
Support Vector Machines ◽  
Nonlinear Systems ◽  
Fitness Function ◽  
Selection Method ◽  
Support Vector ◽  
Mean Square ◽  
Parameters Selection ◽  
Vector Machines ◽  
The Mean ◽  
Simulation Results

Parameters selection plays an important role for the performance of least squares support vector machines (LS-SVM). In this paper, a novel parameters selection method for LS-SVM is presented based on chaotic ant swarm (CAS) algorithm. Using this method, the optimization model is established, within which the fitness function is the mean square error (MSE) index, and the constraints are the ranges of the designing parameters. The proposed method is used in the identification for inverse model of the nonlinear systems, and simulation results are given to show the efficiency.

scholarly journals Developing a real time navigation for the mobile robots at unknown environments

2020 ◽  
Vol 20 (1) ◽  
pp. 500
Author(s):  
Sarah Haider Abdulredah ◽  
Dheyaa Jasim Kadhim
Keyword(s):  
Mobile Robot ◽  
Mean Square ◽  
Matlab Simulation ◽  
Robot Operating System ◽  
Unknown Environments ◽  
Localization And Mapping ◽  
Software Platforms ◽  
The Mean ◽  
Simulation Results ◽  
Robot Platform

<p><span>This research deals with the feasibility of a mobile robot to navigate and discover its location at unknown environments, and then constructing maps of these navigated environments for future usage. In this work, we proposed a modified Extended Kalman Filter- Simultaneous Localization and Mapping (EKF-SLAM) technique which was implemented for different unknown environments containing a different number of landmarks. Then, the detectable landmarks will play an important role in controlling the overall navigation process and EKF-SLAM technique’s performance. MATLAB simulation results of the EKF-SLAM technique come with better performance as compared with an odometry approach performance in terms of measuring the mean square error, especially when increasing the number of landmarks. After that, we simulate and evaluate a mobile robot platform named TurtleBot2e in Gazebo simulator software to achieve the using of the SLAM technique for a different environment using the Rviz library which was built on Robot Operating System in Linux. The main conclusion comes with this work is the simulation and implementation of the SLAM technique using two software platforms separately (MATLAB and ROS) in different unknown environments containing a different number of landmarks so a few number of landmark will make the mobile robot loses its path.</span></p>

Turbulent Dispersion of Heavy Particles With Nonlinear Drag

1997 ◽  
Vol 119 (1) ◽  
pp. 170-179 ◽  
Author(s):  
Renwei Mei ◽  
R. J. Adrian ◽  
T. J. Hanratty
Keyword(s):  
Isotropic Turbulence ◽  
Fluid Velocity ◽  
Interpolation Formula ◽  
Mean Value ◽  
Particle Dispersion ◽  
Turbulent Dispersion ◽  
Heavy Particles ◽  
Time Constants ◽  
The Mean ◽  
Drag Law

The analysis of Reeks (1977) for particle dispersion in isotropic turbulence is extended so as to include a nonlinear drag law. The principal issue is the evaluation of the inertial time constants, βα−1, and the mean slip. Unlike what is found for the Stokesian drag, the time constants are functions of the slip velocity and are anisotropic. For settling velocity, VT, much larger than root-mean-square of the fluid velocity fluctuations, u0, the mean slip is given by VT. For VT→0, the mean slip is related to turbulent velocity fluctuation by assuming that fluctuations in βα are small compared to the mean value. An interpolation formula is used to evaluate βα and VT in regions intermediate between conditions of VT→0 and VT≫ u0. The limitations of the analysis are explored by carrying out a Monte-Carlo simulation for particle motion in a pseudo turbulence described by a Gaussian distribution and Kraichnan’s (1970) energy spectrum.

scholarly journals On the strength of the nonlinearity in isotropic turbulence

2013 ◽  
Vol 733 ◽  
pp. 158-170 ◽  
Author(s):  
W. J. T. Bos ◽  
R. Rubinstein
Keyword(s):  
Nonlinear Term ◽  
Isotropic Turbulence ◽  
Stokes Equations ◽  
Direct Interaction ◽  
Inertial Range ◽  
Gaussian Field ◽  
Mean Square ◽  
Closed Expression ◽  
Gaussian Estimate ◽  
The Mean

AbstractTurbulence governed by the Navier–Stokes equations shows a tendency to evolve towards a state in which the nonlinearity is diminished. In fully developed turbulence, this tendency can be measured by comparing the variance of the nonlinear term to the variance of the same quantity measured in a Gaussian field with the same energy distribution. In order to study this phenomenon at high Reynolds numbers, a version of the direct interaction approximation is used to obtain a closed expression for the statistical average of the mean-square nonlinearity. The wavenumber spectrum of the mean-square nonlinear term is evaluated and its scaling in the inertial range is investigated as a function of the Reynolds number. Its scaling is dominated by the sweeping by the energetic scales, but this sweeping is weaker than predicted by a random sweeping estimate. At inertial range scales, the depletion of nonlinearity as a function of the wavenumber is observed to be constant. At large scales it is observed that the mean-square nonlinearity is larger than its Gaussian estimate, which is shown to be related to the non-Gaussianity of the Reynolds-stress fluctuations at these scales.

The effect of velocity sensitivity on temperature derivative statistics in isotropic turbulence

1971 ◽  
Vol 48 (4) ◽  
pp. 763-769 ◽  
Author(s):  
J. C. Wyngaard
Keyword(s):  
Temperature Gradient ◽  
Temperature Sensor ◽  
Isotropic Turbulence ◽  
Mean Square ◽  
Temperature Derivative ◽  
Spectral Form ◽  
Temperature Spectrum ◽  
Velocity Sensitivity ◽  
The Mean ◽  
Third Moment

The velocity sensitivity of a resistance-wire temperature sensor is expressed in terms of sensor parameters, and the resulting errors in temperature derivative moments in isotropic turbulence are evaluated. It is shown that velocity sensitivity of a degree completely negligible for most purposes causes severe contamination of the measured third moment. The contamination terms are shown to be production rates of the mean square temperature gradient and vorticity, respectively, and therefore create positive values of measured derivative skewness. The dominant contamination term is related to the temperature spectrum through the balance equation for the mean-square temperature gradient, and calculations based on an assumed spectral form show that under typical conditions the measured skewness is large. This mechanism could provide an alternative to anisotropy as an explanation of the positive skewnesses recently measured in the atmosphere.

Numerical study of vertical dispersion by stratified turbulence

2009 ◽  
Vol 631 ◽  
pp. 149-163 ◽  
Author(s):  
G. BRETHOUWER ◽  
E. LINDBORG
Keyword(s):  
Potential Energy ◽  
Numerical Simulations ◽  
Turbulent Flows ◽  
Time Scale ◽  
Numerical Study ◽  
Turnover Time ◽  
Particle Dispersion ◽  
Stratified Turbulence ◽  
The Mean ◽  
Simulation Results

Numerical simulations are carried out to investigate vertical fluid particle dispersion in uniformly stratified stationary turbulent flows. The results are compared with the analysis of Lindborg & Brethouwer (J. Fluid Mech., vol. 614, 2008, pp. 303–314), who derived long- and short-time relations for the mean square vertical displacement 〈δz〉 of fluid particles. Several direct numerical simulations (DNSs) with different degrees of stratification and different buoyancy Reynolds numbers are carried out to test the long-time relation 〈δz2〉 = 2ϵPt/N2. Here, ϵP is the mean dissipation of turbulent potential energy; N is the Brunt–Väisälä frequency; and t is time. The DNSs show good agreement with this relation, with a weak dependence on the buoyancy Reynolds number. Simulations with hyperviscosity are carried out to test the relation 〈δz2〉 = (1+πCPL)2ϵPt/N2, which should be valid for shorter time scales in the range N−1 ≪ t ≪ T, where T is the turbulent eddy turnover time. The results of the hyperviscosity simulations come closer to this prediction with CPL about 3 with increasing stratification. However, even in the simulation with the strongest stratification the growth of 〈δz2〉 is somewhat slower than linear in this regime. Based on the simulation results it is argued that the time scale determining the evolution of 〈δz2〉 is the eddy turnover time, T, rather than the buoyancy time scale N−1, as suggested in previous studies. The simulation results are also consistent with the prediction of Lindborg & Brethouwer (2008) that the nearly flat plateau of 〈δz2〉 observed at t ~ T should scale as 4EP/N2, where EP is the mean turbulent potential energy.

MMSE Beamforming Design for IoT MIMO SWIPT System

2018 ◽  
Vol 4 (1) ◽  
pp. 28
Author(s):  
Nguyen Duy Nhat Vien
Keyword(s):  
Internet Of Things ◽  
Human Services ◽  
Large Scale ◽  
Device Simulation ◽  
Mean Square ◽  
Wireless Devices ◽  
The Mean ◽  
Simulation Results ◽  
Iot Devices ◽  
Smart Infrastructure

Internet of Things (IoT) is a smart infrastructure of the unique identification device capable of wireless communication with each other, and human services on a large scale through the Internet. The IoT devices themselves must self-aware and harvest the energy they need from ambient sources. Simultaneous wireless information and power transfer (SWIPT) is a promising new solution to provide an opportunity for energy-restrained wireless devices to operate uninterruptedly. In this paper, we propose a beamforming approach for Internet of Things (IoT) multi-input multi-output (MIMO) SWIPT downlink systems, which minimizes the mean square error (MSE) of the information decode (ID) device while satisfying the energy constraint of the energy harvesting (EH) device. Simulation results are provided to evaluate the performance and confirm the efficiency of the proposed algorithm.

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