DEM‐CFD modeling of particle systems with long‐range electrostatic interactions

Chen, Pei; Wu, Chuan‐Yu; England, David E.; Byard, Stephen J.; Berchtold, Harald; Adams, M.J.

doi:10.1002/aic.14768

Cited by 40 publications

(24 citation statements)

References 36 publications

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“…For unbounded domains, recent approaches of Pei et al or Liu et al could be used. Pei et al computed the mean charge in the cell in a similar manner to that in this study, but used Coulomb's law to compute the forces from the cells to particles as opposed to the Poisson equation employed here. Liu et al used multipole expansion in conjunction with the boundary element method to obtain forces on particles.…”

Section: Mathematical Modelingmentioning

confidence: 99%

“…As a result, studies in the literature on the effect of electrostatic forces on granular and gas-solid flows have either assumed a constant pre-specified level of charge on particles [14][15][16][17][18] or examined effective work function models for tribocharging. 7,[19][20][21][22][23] Laurentie et al 24 proposed an electron transfer model based on effective work function, and calibrated the effective work function by comparing discrete element method (DEM) simulations of tribocharging in a vibrated bed with experimental data. Essentially, the same electron transfer model was used in recent papers by Naik et al 20,25 to model tribocharging of pharmaceutical powders flowing in a chute.…”

Section: Introductionmentioning

confidence: 99%

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Triboelectric charging of monodisperse particles in fluidized beds

et al. 2016

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To investigate the interplay between particle charging and hydrodynamics in fluidized beds, models for triboelectric charging and electrostatic forces were built into a computational fluid dynamics‐discrete element method model. Charge transfer was governed by the difference in effective work function between contacting materials as well as the electric field at the point of contact. Monodisperse particles were fluidized with an effective work function difference between the particles and the conducting walls. For smaller work function differences, hydrodynamics were not changed significantly as compared with an uncharged case. In these simulations, the average charge saturated at a value much lower than the value anticipated based on the work function difference, and a unimodal distribution of charges was observed. For larger work function differences, particles stuck to walls and bed height oscillations due to slugging were less pronounced. For these cases, a bimodal distribution of charges emerged due to effects from strong electric fields. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1872–1891, 2017

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Section: Mathematical Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Triboelectric charging of monodisperse particles in fluidized beds

et al. 2016

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“…Contact electrification is referred to as the charge transfer process between objects (particle-particle & particle-wall) during collisions. Once the net charge transferred onto particles are strong enough, the induced repulsive and attractive electrostatic forces between objects can cause agglomeration [2,3], dispersion [4] and segregation [5], which will significantly affect the dynamic behaviours of particles and the performance of the fluidisation process.…”

Section: Introductionmentioning

confidence: 99%

DEM-CFD analysis of contact electrification and electrostatic interactions during fluidization

Chen

Adams

2016

Powder Technology

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Contact electrification and electrostatic interactions often occur in the fluidization process, which can significantly influence the dynamic behaviour of particles and the fluidization performance. In this study, a discrete element method coupled with computational fluid dynamics (DEM-CFD) is developed by implementing contact electrification and electrostatic interaction models and the combined effects of contact electrification and electrostatic interaction on fluidization are analysed. It is found that the charge of the particle system increase with the superficial gas velocity. Particles of different material properties (especially work function) can be bi-charged and form agglomerates. At low superficial gas velocities, the particle bed cannot be fully fluidized and the pressure drop tends to be stable rather than fluctuating as the gas flows through the micro-channels of agglomerates. However, at high superficial gas velocities, the agglomerates can break, inducing strong fluctuation of pressure drop. Clearly, the electrostatic phenomena and fluidization behaviour can mutually influence each other during the process

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“…The electrostatic force is the force acting on the charged particles. Generally, the electrostatic force (Fe) between particles is determined based on the Coulomb’s law, which can be expressed by the following equation as a function of the charge of particles and the distance between particles [98,99]:Fe=14πε0q1q2d2trued^ where ε0 is the permittivity of free space; d is the distance between the particle’s center; q1 and q2 are the charges of particle 1 and particle 2, respectively. The explanations of these parameters have been discussed in detail in previous studies [100,101].…”

Section: Comprehensive Theory Of Discrete Element Methodsmentioning

confidence: 99%

Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry

Yeom

Kim

et al. 2019

Pharmaceutics

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Process simulation using mathematical modeling tools is becoming more common in the pharmaceutical industry. A mechanistic model is a mathematical modeling tool that can enhance process understanding, reduce experimentation cost and improve product quality. A commonly used mechanistic modeling approach for powder is the discrete element method (DEM). Most pharmaceutical materials have powder or granular material. Therefore, DEM might be widely applied in the pharmaceutical industry. This review focused on the basic elements of DEM and its implementations in pharmaceutical manufacturing simulation. Contact models and input parameters are essential elements in DEM simulation. Contact models computed contact forces acting on the particle-particle and particle-geometry interactions. Input parameters were divided into two types—material properties and interaction parameters. Various calibration methods were presented to define the interaction parameters of pharmaceutical materials. Several applications of DEM simulation in pharmaceutical manufacturing processes, such as milling, blending, granulation and coating, were categorized and summarized. Based on this review, DEM simulation might provide a systematic process understanding and process control to ensure the quality of a drug product.

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DEM‐CFD modeling of particle systems with long‐range electrostatic interactions

Cited by 40 publications

References 36 publications

Triboelectric charging of monodisperse particles in fluidized beds

Triboelectric charging of monodisperse particles in fluidized beds

DEM-CFD analysis of contact electrification and electrostatic interactions during fluidization

Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry

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