Simulation of Corona Electrostatic Separator for End-of-Life Management in Printed Circuit Boards

Printed circuit boards (PCBs) are made of several materials, including platinum, gold, silver, and rare earth elements, which are very valuable from a circular economy perspective. The PCB end of life management starts with the component removal, then the PCBs are shredded into small particles. Eventually, different separation methods are applied to the pulverized material to separate metals and non-metals. The corona electrostatic separation is one of the methods that can be used for this purpose since it is able to separate the conductive and non-conductive materials. However, the lack of knowledge to set the process parameters may affect the efficiency of the corona electrostatic separation process, ultimately resulting in the loss of valuable materials. The simulation of particle trajectory can be very helpful to identify the effective process parameters of the separation process. Thus, in this study, a simulation model to predict the particles trajectories in a belt type corona electrostatic separator is developed with the help of COMSOL Multiphysics and MATLAB software. The model simulates the particle behavior taking into account the electrostatic, gravitational, centrifugal, electric image, and air drag forces. Moreover, the predicted particles trajectories are used to analyze the effects of the roll electrode voltage, angular velocity of roll electrode, and size of the particles on the separation process.

Self-diffusion in nanofluids of nonelongated particles in the dilute limit

The dynamic features of a dilute suspension of nanoparticles (nanofluid) are fully modified depending on the dominant particles slip mechanism acting in the suspension. Self-diffusion effects in highly sheared diluted suspensions (entrance conditions and microapplications) can lead to a particles distribution fully different from the bulk one. The reported investigation proposes a model to determine the self-diffusion of three-planes symmetric nonelongated particles inmersed in a sheared Stokes flow. The model is based on the real displacements between any pair of particles and an statistical approach to determine contact kinematic irreversibilities. According to the proposed model, the source of hydrodynamic irreversibility is closely related to the particles shape. This is clearly demonstrated through the application of the model to cubic particles. The main conclusion is that the particles shape plays a significant role in the dynamic behavior of the suspension and, as a result, in the self-diffusion coefficient. The reported results arising from the cubic particles trajectories in a Stokes flow are reasonably close to the ones reported by Brady and Morris (J Fluid Mech, 348:103–139, 1997) for suspensions under high Pe number, and Zarraga and Leighton (Phys Fluids 13(3):565-577, 2001).

Evaluation of bulk material behavior control method in technological units using DEM. Part 2

The research is dedicated to the development of special devices (capsules) that can be used to control the mining ore behavior in the technological unit in order to increase processes efficiency. In the first part of the article, the choice of the discrete element method for generating various particle trajectories in the unit (drum pelletizer) was substantiated. This part describes the specific technologies that were used to recognize the pelletizing mode. In particular, conversation of paths to sensor readings is implemented using the Matlab Sensor Fusion and Tracking Toolbox. The obtained readings were processed using two neural network classifiers (DNN and LSTM). As a result, stable models for recognizing the pelletizing modes of the unit were obtained. LSTM recognition accuracy is greater than DNN. The developed approach can be used to recognize the operating modes of other technological units. In addition, data on particles trajectories can be used to improve DEM models of technological processes. Future work consists of the capsule physical implementation and testing the recognition algorithm on a real unit.

Particle size effect on sorting with optical lattice

Transport of mesoscale particles due to driving flow fields or external forces on a periodic surface appears in many areas. Geometrical and physical characteristics of particles affect the velocities of the particles in these periodic landscapes. In this paper, we present a numerical simulation based on solving the Langevin equation for the meso-size particles subjected to the thermal fluctuations in a periodic array of optical traps. We consider the real-size particles which cause the partial trapping of particles in the optical traps. The particles are sorted for the size-dependency of particles’ trajectories. Our results are in good agreement with experiments.

Perfectly parallel cosmological simulations using spatial comoving Lagrangian acceleration

Context. Existing cosmological simulation methods lack a high degree of parallelism due to the long-range nature of the gravitational force, which limits the size of simulations that can be run at high resolution. Aims. To solve this problem, we propose a new, perfectly parallel approach to simulate cosmic structure formation, which is based on the spatial COmoving Lagrangian Acceleration (sCOLA) framework. Methods. Building upon a hybrid analytical and numerical description of particles’ trajectories, our algorithm allows for an efficient tiling of a cosmological volume, where the dynamics within each tile is computed independently. As a consequence, the degree of parallelism is equal to the number of tiles. We optimised the accuracy of sCOLA through the use of a buffer region around tiles and of appropriate Dirichlet boundary conditions around sCOLA boxes. Results. As a result, we show that cosmological simulations at the degree of accuracy required for the analysis of the next generation of surveys can be run in drastically reduced wall-clock times and with very low memory requirements. Conclusions. The perfect scalability of our algorithm unlocks profoundly new possibilities for computing larger cosmological simulations at high resolution, taking advantage of a variety of hardware architectures.

Swirling Effects in Atmospheric Plasma Spraying Process: Experiments and Simulation

Experimental evidence of swirling effects in 3D trajectories of in-flight particles is presented based on static and dynamic footprints analysis as a function of stand-off distance of Al2O3 deposited employing a Metco-9MB torch. Swirling effects were validated with a proprietary computational fluid dynamics (CFD) code that considers an argon-hydrogen plasma stream, in-flight particles trajectories, both creating the spray cone, and particle impact to form a footprint on a fixed substrate located at different distances up to 120 mm. Static and dynamic footprints showed that swirl produces a slight deviation of individual particle trajectories and thus footprint rotation, which may affect coating characteristics.

Simulation of un industrial waste treatment tank

The objective of the present work was to evaluate the operation of an industrial sedimentation tank used in the separation of solid waste from the petrochemical industry. The depth data were obtained through a “interface float”, while the diameters and the positions of the particles through the CFD simulation. The computational fluid dynamics simulator (FLUENT 6.3.26) was used to perform a multiphase simulation using the Euler-Lagrange approach and was used to determine the particles trajectories and cotours of solids accumulated in the bottom of the tank. This allowed a better understanding of solids accumulation and improvement of the cleaning process. In the simulation of the tank a large computational mesh comprising 464,094 computational nodes was designed. The use of the Euler-Lagrange approach meant that a discrete phase model had to be established and the parameters of Rosin-Rammler solids distribtion model for the boundary conditions of the simulation had to be determined.